ISSN 1198-6727

Number2012 VolumeFisheries Centre Research Reports

CatCh reConstruCtion for the red sea large marine eCosystem by

Countries (1950-2010)

20 1

ISSN 1198-6727

Fisheries Centre, University of British Columbia, Canada

Fisheries Centre Research Reports

2012 Volume Number

CatCh reConstruCtion for the red sea large marine

eCosystem by Countries (1950-2010)

Edited by

Fisheries Centre Research Reports 20(1)244 pages © published 2012 by

The Fisheries Centre,University of British Columbia

2202 Main MallVancouver, B.C., Canada, V6T 1Z4

ISSN 1198-6727

Dawit Tesfamichael and Daniel Pauly

Contents

A Research Report from the Fisheries Centre at UBC

fisheries Centre researCh reports are abstraCted in the fao aquatiC sCienCes and fisheries abstraCts (asfa)issn 1198-6727

Fisheries Centre Research Reports 20(1)244 pages © Fisheries Centre, University of British Columbia, 2012

Fisheries Centre Research Reports 20(1)2012

Edited byDawit Tesfamichael and Daniel Pauly

Preface iIntroduction to the Red Sea ecosystem and its fisheries 1

Dawit Tesfamichael and Daniel Pauly

Reconstructing Red Sea fisheries of Egypt: Heavy investment and fisheries 23Dawit Tesfamichael and Sahar Fahmy Mehanna

Reconstructing Red Sea fisheries of Sudan: foreign aid and fisheries 51Dawit Tesfamichael, Abdalla Nassir Elawad

Reconstructing Red Sea fisheries of Eritrea: a case study of the relationship between political stability and fisheries development 71

Dawit Tesfamichael, Sammy Mohamud

The marine fisheries of Yemen with emphasis on the Red Sea and cooperatives 105Dawit Tesfamichael, Peter Rossing and Hesham Saeed

Reconstructing Red Sea fisheries catches of Saudi Arabia: National wealth and fisheries transformation 153

Dawit Tesfamichael and Peter Rossing

Preliminary reconstruction of fisheries catches of Jordan and Israel in the inner Gulf of Aqaba, Red Sea, 1950-2010 179

Dawit Tesfamichael, Rhona Govender and Daniel Pauly

Common names of exploited fish and invertebrates of the Red Sea 205Dawit Tesfamichael and Hesham Saeed

Appendix - Reconstructing the fishing effort of Red Sea fisheries, 1950-2010 239Dawit Tesfamichael

i

We are pleased to present herewith the first report ever on the history and catches of all fisheries of the Red Sea, including the commonly overlooked activities of various small-scale fisheries.

The period covered here, 1950 to 2010, is long enough for detecting and illustrating major trends, such as the trend toward motorization of artisanal fisheries and industrial fisheries– notably the use of trawlers– that are radically transforming Red Sea fisheries.

The fishery catches were ‘reconstructed’ for each Red Sea country, i.e., Egypt, Sudan, Eritrea, Yemen, Saudi Arabia, Jordan and Israel and thus can be compared with the landings reported on their behalf by the Food and Agriculture Organization of the United Nations (FAO), of which they are all members. These reconstructed catches are overall 1.5 times higher than reported by FAO, essentially because they cover mainly industrial landings while the reconstruction also include artisanal, subsistence and recreational catches, as well as trawlers’ discards.

This catch was, as far as possible, disaggregated to species level, such that analysis of their different contribution to Red Sea catches can be conducted. To facilitate these further, this report includes a list of the common names of fishes and common marine invertebrates in Arabic, as spoken all along Red Sea coasts. A preliminary ‘reconstruction’ of the fishing effort exerted in the Red Sea by country and gear type is also presented.

The national catch reconstructions underlying the core of this report were performed as part of a global project of the Sea Around Us, i.e., to re-estimate the catch of the world’s marine fisheries. However, these reconstructions should also be useful in each of the Red Sea countries as a starting point for ecosystem-based management of fisheries and of more detailed research or publication on various aspects of Red Sea fisheries.

The contributions that constitute the body of this report were nearly completed by late 2012, and thus it was prematurely given a publication number and cited as such in various works. Thus, we decided to retain this date of publication number. We apologize for any confusion this may have caused.

All that is left to us is the pleasant task of acknowledging our co-authors in this endeavor, many of them from the Red Sea countries, and who contributed their local knowledge. The institutions and personnel who helped us with this work are acknowledged in each respective chapter. We also thank the Pew Charitable Trust for their support of the Sea Around Us.

The EditorsJuly 2014

prefaCe

Introduction - Tesfamichael and Pauly 1

introduCtion to the red sea eCosystem and its fisheries1

Dawit Tesfamichaela,b and Daniel Paulya

aSea Around Us, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada

bDepartment of Marine Sciences, University of Asmara, Asmara, Eritrea.d.tesfamichael @fisheries.ubc.ca d.pauly @fisheries.ubc.ca

abstraCt

The Red Sea, characterized by a number of unique oceanographic and biological features, provided for humans for millennia, from the earliest record of human consumption of seafood to its current state as an important fishing ground for the seven countries along its shores. Contemporary fisheries need monitoring and management, and catch data are crucial for both. However, reliable time-series of catch data are lacking for most Red Sea Fisheries. Here, the catches of Red Sea fisheries are ‘reconstructed’ from 1950 to 2010 by country (i.e., Egypt, Sudan, Eritrea, Yemen, Saudi Arabia, Jordan and Israel) and sector (artisanal, subsistence, industrial and recreational), and in terms of their species composition. Historical documents, published and unpublished reports and other grey literature, databases, field surveys, anecdotal information, interviews, and information on processed seafood products were used as sources. When reliable data were available for a number of years, they were used as anchor points, and missing years were interpolated, based on assumptions of continuity, and given the best knowledge of the fisheries available. The reconstructed catches (which also include discards) were compared to the statistics submitted by the above-mentioned countries to the Food and Agricultural Organization (FAO) of the United Nations. Overall, the total Red Sea catch was low (around 50,000 t·year-1) until 1960, increased to its peak (around 177,000 tonnes) in 1993, and is declining since. Overall, it was 1.5 times higher than the catch officially submitted to FAO by the countries bordering the Red Sea. Artisanal fisheries generally contributed about half of the total Red Sea catch, while the composition of the catch was extremely varied, with no single species or even family dominated. In addition to the national catch reconstructions, the local (Arabic) names of common commercial fishes and a brief reconstruction of the effort are also presented. The resulting catch trends provide crucial historical records and important guidance for the development of future fisheries management policies aiming at resource conservation and sustaining the livelihoods of the coastal communities.

introduCtion

The Red Sea is an elongated narrow sea between Northeastern Africa and the Arabian Peninsula, ranging from 300N to 12030’N and from 320E to 430E with a length of 2,000 km and an average width of 208 km (Figure 1). The maximum width is 354 km in the southern part (Morcos 1970), and the total area is 4.51 x 105 km2. The Red Sea is connected to the Indian Ocean in the south through the narrow strait of Bab al Mandab, the door of fortune. Bal al Mandab, which is only 29 km wide, has a sill 137 m below sea level, which limits the circulation of water between the Red Sea and the Gulf of Aden. The Red Sea is also connected to the Mediterranean Sea through the Suez Canal since its opening in 1869. The average depth of the Red Sea is 491 m, with a maximum of 2850 m. In the north, the Red Sea is divided into the Gulfs of Suez and Aqaba. The Gulf of Suez is generally wide, shallow and muddy, while the Gulf of Aqaba is narrow and deep.

Geological evolution

The Red Sea was formed by plate tectonics, i.e., by the African and Arabian plates drifting apart, and is part of a larger tear that includes the Dead Sea and the East African rift systems. Geologically, the Red Sea is a young ocean that is still growing or 1 Cite as: Tesfamichael, D. and Pauly, D. (2012) Introduction to the Red Sea ecosystem and its fisheries. pp. 1-22. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosysytem by countries (1950-2010). Fisheries Centre Research Reports 20(1). Fisheries Centre, University of British Columbia [ISSN 1198-6727].

Figure 1. The Red Sea and the surrounding countries, including their Exclusive Economic Zones (EEZs) and shelf areas.

2

spreading (Braithwaite 1987). The zone was already structurally weak during the Pan-African orogeny 600 Ma. The separation of the Arabian and African plates is believed to have started in the Tertiary period, between the Eocene and Oligocene periods; it accelerated during the late Oligocene, with intense magmatic activity and the development of a continental rift (Makris and Rihm 1991). The Red Sea depression is believed to have been flooded by the Mediterranean as a result of extensive sinking in the early Miocene (Girdler and Southren 1987). Since its inception, the Red Sea went through a series of connections and disconnections with the Mediterranean in the North and the Indian Ocean in the south. At the end of Miocene, upheaval of land occurred and the Red Sea was disconnected from the Mediterranean to become a separated salty lake. At the beginning of the Pliocene, the Red Sea was reconnected with the Mediterranean, and for the first time, it was also connected with the Indian Ocean, but at the end of Pliocene, the northern connection with the Mediterranean was closed off due to crustal plate movement. The connection with the Indian Ocean was closed off during the Pleistocene, when the Red Sea again became an isolated sea. At the end of the Pleistocene, a glacial period, its connection with the Indian Ocean was re-established, whereas the connection with the Mediterranean remained closed until it was artificially opened via the Suez Canal in 1869 (Goren 1986; Getahun 1998). The Red Sea being young and still expanding is used as a case study to understand and explain plate tectonics, mid ocean ridges and formation of oceans.

Physical oceanography

The Red Sea area is generally arid, rainfall is very sparse with annual average ranging from 1 mm to 180 mm (Edwards 1987). Evaporation, with an annual average of 2 m (Morcos 1970), largely exceeds precipitation, and the deficiency is made up by the flow of water from the Indian Ocean through Bab al Mandab. In winter, warmer and less saline water flows into the Red Sea in the surface layer; while cooler and saltier water flows into the Gulf of Aden in the lower layer. In summer, there are three layers of water flow in the strait. In addition to the two flows of winter, warm water flows on the surface from the Red Sea to the Gulf of Aden (Smeed 2004). Sea and air temperatures are high in the Red Sea with mean annual sea surface temperature of 28oC. Additionally, the Red Sea is undergoing an intense and rapid increase in temperature, which is attributed to climate change (Raitsos et al. 2011). Another remarkable characteristics of the Red Sea is its high salinity, about 35 psu on average at the surface; readings as high as 40.5 psu are also reported. The high salinity of the Red Sea is due to the combination of its geological history and its location in dry and hot environment. Though originally the Red Sea depression was flooded with Mediterranean water, it soon started to become more saline due to high evaporation. Later during the glacial period, the Red Sea was an isolated salty lake with salinity higher than the present by a value of 10 psu. The highly saline water was diluted by water from Indian Ocean when the Red Sea was reconnected with the Indian Ocean (Thunell et al. 1988). However, it is still more saline than the Indian Ocean water due to high evaporation (Morcos 1970).

Biological oceanography and origin of the biota

The Red Sea is not very productive, mainly due to lack of nutrient-rich terrestrial run off; also, there is almost no upwelling to lift nutrient-rich deep water to the surface where photosynthesis can occur. Moreover, the vertical mixing of water is prevented by a permanent thermocline as the temperature of the sub-surface water is always lower than the warm surface temperature. The depth of the thermocline is deeper in winter than summer (Edwards 1987). Generally, the southern part of the Red Sea is more productive than the northern part due to the flow of nutrient rich water from the Indian Ocean, the main nutrient input, and the re-suspension of nutrients from the bottom sediments by turbulent mixing over shelf areas (Sheppard et al. 1992). The shallow Gulf of Suez is also productive and supports many exploited fish populations.

The high and relatively stable temperature of the Red Sea favours the formation of coral reefs, which are well developed in its northern part, starting from the tip of Sinai Peninsula. The longest continuous fringing reef in the Red Sea extends from Gubal, at the mouth of the Gulf of Suez, to Halaib, at the Egyptian border with Sudan (Pilcher and Alsuhaibany 2000). In the south, more patchy reefs are observed as the turbid waters of the shallow shelf prevent the formation of extensive reefs. Sanganeb Atoll, located in Sudan near the border with Egypt, is the only atoll in the Red Sea; it raises from 800 m depth to form a structure that has been recognized as regionally important conservation, and proposed to UNESCO as a World Heritage Site in the 1980s (Pilcher and Alsuhaibany 2000). Coral reefs recycle their nutrients, which enable them to maintain a high productivity, much like an oasis in a desert. They attract fisheries, mainly small-scale artisanal, and tourists.

The connections of the Red Sea with the Mediterranean in the north and the Indian Ocean in the south account for the kind of species that colonized it at different times. Though the Red Sea was first populated by Mediterranean species, its current biota resembles that of the Indian Ocean. When the Red Sea was disconnected from Mediterranean and for the first time connected with the Indian Ocean in the beginning of the Pliocene period (about 5 – 6 million years ago), it was populated by Indian Ocean fauna. Later during the glacial period of the Pleistocene, the level of the world’s oceans was low. The Red Sea was isolated with high level of salinity (about 50 psu at the surface) and low temperature (about 20C lower than the present) (Thunell et al. 1988). This resulted in the extinction of many species. Later, when it was reconnected with the Indian Ocean at the end of the glacial period, 10 – 12 thousand years ago, an opportunity was created for Indian Ocean species to re-populate the Red Sea (Goren 1986).

As a result of its connection to the speciose Indo-Pacific fauna, the Red Sea has a very high fish diversity, with more than 1,400 species of fishes are reported in FishBase (www.fishbase.org). It is also characterized by high degree of endemism, due to the closures alluded to above, with estimates of endemic fish species reaching 10–17% (Ormond and Edwards 1987). Because the Red Sea has very low nutrient input, as explained above, species that can survive

Introduction - Tesfamichael and Pauly 3

its extreme environments have very good chance to dominate, as there are fewer competitors. One example is the phytoplankton Trichodesmium erythraeum, a blue-green alga (cynobacterium) that can overcome nitrate depletion by fixing atmospheric nitrogen dissolved in the water. In calm waters, its filaments float to the sea surface of the Red Sea and form a rather reddish scum, the likely origin of the name ‘Red Sea’ (and incidentally, of Eritrea’s as well).

On the shores of coastal lagoons and sheltered bays mangroves are common. The most common species is Avicennia marina. Bruguiera gymnorhiza and Ceriops tagal also occur, though they are less common. The shallow waters of the lagoons and bays are home to seagrass beds. About 500 species of algae are reported from the Red Sea. Most algae in the north and central part are macroscopic, non-calcareous, brown, green and red algae. In the south, large brown algae such as Sargassum dominate (Walker 1987).

Five sea turtle species are reported from the Red Sea: hawksbill, green, olive ridley, loggerhead and leatherback. Hawksbill and green turtles are the most common, and are reported to nest along Red Sea beaches (Frazier et al. 1987). There is no active hunting for sea turtles in the Red Sea, but they are accidentally caught in fishing nets. The rich seagrass beds support dugongs, which are reported from Gulf of Suez in the north to Eritrea’s Dahlak Archipelago in the south (Preen 1989). The reports of cetaceans from the Red Sea are sparse. Seven species of dolphins are commonly reported, as well as occasional spotting of killer whale and false killer whale. Frazier et al. (1987) suggested that the narrow strait of Bab al Mandab and the low productivity in the Red Sea as reasons for the scarcity of cetaceans. As far as seabirds are concerned, the enclosed nature of the Red Sea acts as a barrier for pelagic fishes on which many seabirds feed. As a result pelagic seabirds, such as shearwaters and petrels, are poorly represented. Because of its elongated shape, the Red Sea has high coast to sea area ratio and its seabird fauna is dominated by coastal species (Evans 1987).

Human settlements

According to archeological evidence, human settlement on the Red Sea coast started millennia ago (Horton 1987) and the Red Sea has the oldest records of human use of marine resources, in the form of giant clam and other shell middens (Walter et al. 2000). The Red Sea was also used as an important trade route between the Indian Ocean and the Mediterranean. However, in contrast with the rest of the world, where most of the population lives in a narrow strip of land along the coast (Edgren 1993), the population density on the Red Sea coast is still very low, except for very few major ports and cities. This is mainly due to the arid and hot climate, which resulted in most of the settlements being farther inland, in milder climate and where freshwater is less scarce. This has greatly limited the degree of coastal shoreline alteration, pollution and resource extraction. Thus, many Red Sea communities still depend on harvesting marine resources for subsistence using traditional methods of shell collection and fishing.

However, in the last few decades, the wider availability of technology coupled with cheap oil, at least for the oil producing countries, is changing the demography of the Red Sea coast. The major port cities are metropolitan hubs, with diverse economic activities, and fishing has become marginal. Egypt has a strong recreational and tourism industry, and its coast is quite populated, creating pressure on the coastal ecosystems. Air conditioners and desalination plants are making life easier. A typical example is the Saudi Arabia coast where vibrant cities, such as Jeddah, have grown fast and new cities (e.g., Yanbu) are developing. In such cities, coastal reclamation and dredging are becoming common for residential, commercial and industrial purposes. Pollution is prevalent around urban areas and ports, and lack of sewage treatment is a serious problem throughout the Red Sea, as is the pollution from oil refineries. Overall the impact of human activities is growing (Frihy et al. 1996).

Research expeditions

One of the earliest scientific expeditions to the Red Sea is the Danish Arabia Felix of 1761 – 1767, which spent October 1762 – August 1763 in the Red Sea area. It included the Swedish naturalist Peter Forsskål, a student of Linnaeus, who made an extensive collection of plants and animals, and particularly fish. His report was published posthumously by Carsten Niebuhr, the sole survivor (Forsskål 1775). There were many fragmented accounts of expeditions, most of them unsuccessful, to the Red Sea in the 18th and 19th centuries. One important and outstanding work in describing the Red Sea ecosystem and its organisms is that of Carl Benjamin Klunzinger, a German medical doctor who worked as a quarantine inspector in the Egyptian Red Sea port of Qusier from 1863 to 1869 and 1872 to 1875. His descriptions include coral fauna, fish, crustacea, hemichordates and also meteorological (Klunzinger 1870, 1872), and cultural observations (Klunzinger 1878). An Austrian research vessel, the Pola, conducted an expedition in 1895 – 1896 to the northern Red Sea (Luksch 1898) and 1897 – 1898 to the south (Luksch 1900), including the first oceanographic studies and sampling of deep sea life up to 2000 m (Head 1987a). The specimens from the expedition are kept in the Natural History Museum in Vienna (Stagl et al. 1996).

More recent expeditions include the John Murray expedition carried out using the Egyptian research vessel Mabahiss 1933 – 1934 (Tesfamichael 2005), which collected oceanographic and biological samples throughout the Red Sea and the Arabian Sea (Norman 1939). From 1959 to 1964, the International Indian Ocean Expedition brought some vessels to sample the Red Sea, whose oceanography was compiled by Morcos (1970). An Israeli expedition to the southern Red Sea in 1962 and 1965 (Ben-Tuvia 1968), and the Israeli Marine Biological Station at Eilat, which was opened in 1968, also contributed to the knowledge of the Red Sea. At present, a lot of initiatives are taken by the countries bordering the Red Sea and new information is collected.

4

fisheries

The Red Sea has multiple uses, the major one being as a route from the Indian Ocean to Europe. Recently, interest in the tourism industry has been increasing, notably in Egypt, which has a well-developed marine tourism industry, especially along its northern coast. As far as resource extraction is concerned, however, fishery is still the most important sector in Red Sea. The Red Sea has a long history (and prehistory) of resource exploitation by humans. Archaeological studies of middle stone age middens from the Eritrean Red Sea coast indicate that humans were eating giant clams and other molluscs about 125,000 years ago, possibly the most ancient such practice on record in the world (Walter et al. 2000). The artisanal fisheries have traditionally operated in harmony with the ecosystem because of low population; non-destructive traditional fishing technology; and poor communication and infrastructure. However, recently, more advanced and destructive methods are being used. Currently, fishing operations in the Red Sea range from foot fishers catching fish mainly for their own consumption, to very large trawlers with freezing facilities.

The fisheries in the Red Sea are typical tropical fisheries, multi-gear and multi-species. Most fishing is performed from wooden boats ranging from 5 to 18 meters, locally called ‘Sambuk’ and ‘Houris’. Sambuks are larger, and have inboard engines; Houris are smaller and use outboard engines. Both Sambuks and Houris use similar fishing gears, mostly handlining and gillnet. The main difference in the operation of Sambuk and Houri are length of the fishing trip, crew size and capacity (Tesfamichael and Pitcher 2006).

Total annual potential landings from the Red Sea were estimated once at 360,000 t·year-1 (Gulland 1971), but this value needs further scrutiny. Though the Red Sea accounts for 0.12% of the total world ocean area, its contribution to the world catch is only 0.07% (Head 1987b). Nevertheless, it is important to the countries in the region. Fishery produces a cheap source of animal protein and provides livelihood for the communities on the coast. Since the countries on the Red Sea coast are generally less industrialized, fisheries can provide multiple livelihoods.

Of the seven countries that border the Red Sea, Jordan and Israel have too small coastlines to support any major fishery. Of the other countries, Egypt and Yemen have well established fisheries and have been utilizing their resource for a long time. Egyptian and Yemen fishermen also fish in other countries’ waters. Sudan is the country which utilize its fisheries resources the least, besides Jordan and Israel. Saudi Arabia has recently established an industrial fisheries, in addition to the artisanal fishery that has been active for many years. Eritrea had a strong small pelagic fishery in the past, then the fishery was dormant until it resumed after the country’s independence in 1991.

Fishery data and assessment

A key part of documenting a fishery is reporting its catches. Given the catch level of a fishery, inferences can be drawn on the intensity of the pressure it exerts, and the approximate number of people involved in, and/or dependant on that fishery. Also, from additional information on the catch composition, inferences can be drawn on the technology that is deployed, the trade linkages that a fishing community has with its neighbours, its income from fishing, etc. In fact, reliable catch data are the most straightforward source of information for a variety of disciples, ranging from history and maritime anthropology to fisheries economics (Pauly 2006).

For fisheries scientists, the value of catch data is even greater. Indeed, catch data are crucial to their main task, which is to perform fish stock assessments in support of fisheries management. Herein, the key feature of stock assessments is to evaluate the status or level of fishing activity in relation to the productivity of the ecosystem, so that fish from a given stock can be caught in such a manner that the various components of the ecosystem and its regeneration potential are not compromised. If these conditions are met, the ecosystem will sustain fishing for a long time. To accomplish this task, there are two different subtasks to be considered: first establishing the potential of the ecosystem and second establishing where the fishery is relative to that potential. Many assessment tools have been developed to estimate the biological potential of a fishery system and use them as benchmarks for the level of exploitation. Maximum sustainable yield (MSY), and the ratio between the estimated original (un-fished) biomass and the current biomass are two of the many metrics used globally to establish levels beyond which the catch is not advised to go (Beverton and Holt 1957; Hilborn and Walters 1992). Of course, there are criticisms of those approaches, the assumptions they use and their applicability to different ecosystems, and they even share part of the blame for the decline of many fisheries (Larkin 1977; Punt and Smith 2001). However, until better alternatives are available to replace the traditional stock assessment tools, they will be used, despite their limitations. Moreover, while new approaches are being developed, many fisheries in the world do not even have estimates of those metrics and/or are not managed at all.

Overall, reliable catch data, jointly with the methods to estimate the biomass of fish and their productivity, are crucial components of effective assessment and management of fisheries. Time series of total catch, preferably by species, is thus the most basic and important information that can be gathered about a fishery (Caddy and Gulland 1983; Pauly and Zeller 2003). It is even more useful when coupled with fishing effort data. Notably, catch and effort data can help with preliminary assessment of the status of population upon which fisheries depend. However, this should be done with caution (Harley et al. 2001), because catch per unit of effort (CPUE), although an indicator of fish biomass, is not always proportional to abundance. CPUE can remain more or less stable while abundance is declining, a phenomenon called ‘hyperstability’, observed on schooling pelagic fish and spawning aggregations (Hilborn and Walters 1992; Pitcher 1995; Sadovy and Domeier 2005). On the other hand, CPUE can decline more than the actual decline of abundance called ‘hyperdepletion’ (Hilborn and Walters 1992). This can occur, for example, when only a portion of the population is vulnerable to the fishery (Walters and Bonfil 1999; Kleiber and Maunder 2008). However, for many fisheries, CPUE is the best type of information available for assessment, and not using it is short-sighted.

Introduction - Tesfamichael and Pauly 5

the rationale for CatCh reConstruCtion

There are many ways catch data can be collected. The most common are log books filled in by fishers, the records of observers onboard fishing vessels and data collection at the landing sites and on markets (e.g., auction and exports). For the Red Sea countries, many of these methods are very difficult to implement. Most of the local (artisanal) fishers are illiterate. The communities are predominantly based on oral traditions, thus logbooks are out of question. The majority of the boats are small, and on-board observers are impractical to deploy. Data recording at landing sites, although still arduous, is the most practical for routine catch and effort data collection. The challenge here is that the number of landing sites along the coast is quite large, and some of them are not even known to the fisheries administrations. Setting up proper data collection systems is thus not straightforward, given the complexity of fisheries and fish marketing.

There are many fates of a fish following its encounter with fishing gear (Figure 2). The actual effect of fishery in an ecosystem should be measured by the amount of fish killed (rather than fish landed). The actual measure of fishing mortality can be concealed by lack of data on the mortality of the fish at the different parts of Figure (2). For example, for some Red Sea countries, more than half of the fish catch does not go through fish market, where official recording occurs (Chakraborty 1983). If only the data from landing sites is used to calculate the fishing mortality, this will underestimate its actual magnitude. Thus, proper planning and systematic collection procedures are needed (Gulland 1975; Sparre 2000) and for the Red Sea, it is urgent (Tesfamichael 2012). Systematic data collection requires resources, and thus developed countries usually have better catch and related statistics than developing countries (Alder et al. 2010), while the latter also have to contend with a generally higher biodiversity, which makes the catch highly diverse, and hence comprehensive catch statistics difficult to produce (Pauly and Watson 2008). Note, however that even in developed countries with better statistics, overfishing is rampant, e.g., in the North Atlantic (see e.g., Christensen et al. 2003).

The Food and Agricultural Organization (FAO) of the United Nations assembles annual catch data submitted by member countries and harmonizes and disseminates them since 1950 (Garibaldi 2012; Pauly and Froese 2012), and Garibaldi (2012) gives a comprehensive description of the FAO database and its evolution. Because it consists of continuous, long time series and is easy to access, the FAO database is used extensively for research and policy at regional or international scales. Thus, 600 articles in peer-reviewed journals cited the FAO database in the last 15 years, notably because its standardized data makes comparisons straightforward (Garibaldi 2012).

FAO’s mandate is very broad, and when it comes to fishery data, it can only compile what is submitted to it. This is the main bottleneck to the quality of the data. Countries do not necessarily have the incentive to submit reliable data, except as moral obligation to contribute to a global system. Thus, it is not uncommon for countries to send incorrect or incomplete fishery data (Pauly and Froese 2012), and FAO does not have a legal or procedural mandate to refuse such data. Even more problematic, the technical reports produced by FAO staff or consultants are not reflected in the database. Thus, the global estimates of discards documented in successive Technical Papers and other FAO documents were never included in the FAO statistics (Zeller and Pauly 2005).

Figure 2. Possible fates of fish following an encounter with a fishing gear, based on Mohammed (2003).

6

Another example, applying specifically to the Red Sea, is that most of the early fishery data for the Red Sea comes from national or regional projects executed by FAO, especially the project ‘Development of fisheries in areas of the Red Sea and Gulf of Aden’, which ran from the late 1970s to the mid-1980s under United Nations Development Programme (UNDP and FAO. Among other things, the projects surveyed the fisheries and estimated national catches (Chakraborty 1984), but they were not incorporated into the FAO catch database. Moreover, while the countries around the Red Sea are all members of FAO, and hence they send their fishery data to FAO, many suffer from political and institutional instability, which affects their fishery agencies, and thus there are gaps and inconsistencies in the data supplied to FAO.

FAO’s mandate, while broad, does not include detailed analysis and review of the data supplied by member countries, which thus remain limited in their reliability and usefulness. It is assessed by FAO itself that the catch data it receives from over half of its developing country members, and one quarter of developed country members are unreliable (Garibaldi 2012). The following are the major constraints with the fishery statistics in the FAO database, and affect all countries, and not only those around the Red Sea:

1. The FAO database reports global marine catches spatially only to the extent that they are allocated to 19 giant ‘statistical areas’. In the cases of Red Sea catches, this is area 51, the ‘Western Indian Ocean’, extending from the tip of the Gulf of Suez in the North to the Antarctic Convergence in the South, and from Sri Lanka in the East to South Africa in the West;

2. The level of taxonomic aggregation of the catch is usually very high, and a large part of the catch is reported as ‘miscellaneous’ or ‘unidentified species’, which masks qualitative changes occurring within the ecosystem;

3. FAO’s member countries often send in catch data (usually emanating from a Department of Fisheries or similar institution) through their Ministry of Trade, or some central statistics office or other government agency not directly connected with fisheries, where they are often over-aggregated and/or otherwise modified before being sent off;

4. Some countries may have political reasons to misreport their catch, including over-reporting of catches as China did to FAO for at least two decades (Watson and Pauly 2001) and, gravest of all:

5. When data for certain fisheries are not available (because the fisheries in question were not monitored), no estimate for the missing catch data are submitted. Subsequently, absent catch data for a given year become an annual catch of precisely ‘0’ tonne (Pitcher et al. 2002). Thus, the FAO database does not account for illegal, unreported and unregulated (IUU) catch (Alverson et al. 1994; Kelleher 2004), nor does it suggest where gaps in its coverage may occur.

FAO has taken initiatives to improve the content of its catch database, and indeed, it has improved over time. Also, there is a university-based research project, the Sea Around Us (www.seaaroundus.org), which aims to improve the quality of global marine fishery data. Being non-governmental, Sea Around Us is not limited by formal procedures. Hence, country catch reports can be critically examined, and when fisheries where omitted, their catch can be estimated using the best available knowledge. In effect, the major issues with the FAO database can be overcome through reconstructing historical catch time series (Pauly 1998; Pauly and Zeller 2003; Pauly and Froese 2012). Reconstructed time series of catch (and effort) data from the past are not merely useful for historical purposes. Rather, they provide a basis for overcoming the shifting baseline syndrome (Pauly 1995), i.e., for improved assessment of past and current impacts of fishing on marine ecosystems, and for ecological restoration (Scott Baker and Clapham 2004; Pitcher 2005). The lessons learned from catch reconstruction in different circumstances of the fisheries can be informative, similar to ‘scenarios’ in adaptive management of resources (Walters 1986).

Catch reconstruction involves quantifying the catch of each fishery known to have existed, based either on ‘hard’ catch data, or when such data are not available, on the ‘shadow’ that the fishery – a social activity–throws on the society in which it is embedded. This shadow may consist of household fish consumption figures, number and income of fishers, export figures, etc… (Pauly 1998). Estimates from catch reconstruction, while approximate, will generally be closer to reality than the misreported catches, e.g., the precise estimate of zero in the official databases alluded to in the above (Pitcher et al. 2002; Zeller et al. 2007).

The main objective of this report is to reconstruct catches of the Red Sea fisheries from 1950, the year FAO started to publish annual statistical reports on the fisheries of the world, up to 2010. . Included here are all the Red Sea countries: Egypt, Sudan, Eritrea, Yemen, Saudi Arabia, Jordan and Israel and all the fishing sectors of these countries. The major outputs are a time series of standardized fishery catch for the Red Sea, by sector and species or other groupings. We do not claim these catch reconstructions data to be final. Rather, we see them as the start of an iteration, and as a basis to kick start the discussion on how to improve fishery data for the Red Sea, and ultimately, the management of its fisheries resources.

sourCes and CatCh reConstruCtion proCedures

The main procedure in catch reconstruction is digging into different sources reporting the catches of the countries, critically analyzing them, and organizing them to a common standard, which can be used for comparison and carrying out analysis for the assessment of the resources (Mohammed 2003; Tesfamichael and Pauly 2011). The sources used here include peer-reviewed published papers, grey literature (mainly government, consultant, and FAO reports), and national databases, complemented by field trips by the first author to Egypt, Sudan, Eritrea, and Yemen from

Introduction - Tesfamichael and Pauly 7

December 2006 to September 2007. The information collected was enriched by the insights of local experts and colleagues who provided data through personal communications. The catch reconstruction for the whole Red Sea was first compiled in the form of individual country reports, co-authored by country experts: Egypt (Tesfamichael and Mehanna 2012), Sudan (Tesfamichael and Elawad 2012), Eritrea (Tesfamichael and Mohamud 2012), Yemen (Tesfamichael et al. 2012b), Saudi Arabia (Tesfamichael and Rossing 2012), and Jordan and Israel (Tesfamichael et al. 2012a), which give country-specific details (see also www.seaaroundus.org/eez/). Here, a summary of the general methodology and the procedure to establish one coherent data set for the whole Red Sea are described.

Sources

The earliest data sources for the Red Sea countries were technical reports of the assessments of the fishery resources for planning the development of the fishing industry, starting in the decades following WWII. The 1950s was also a period where several of these countries became independent and started to run their national economies, and food security became a critical issue. These assessments/surveys were made by foreign experts (except for Egypt), usually recruited through the FAO. The earliest sources available were for Saudi Arabia (El-Saby and Farina 1954), Sudan (Kristjonsson 1956), Eritrea (Ben-Yami 1964), Egypt (Al-Khol and El-Hawary 1970) and Yemen (Lisac 1971; Losse 1973). Other early assessments were performed through bilateral arrangements or consultants hired directly by the countries (e.g. see Ben-Yami 1964; Atkins 1965; Grofit 1971 for Eritrea). In the 1970s and 1980s, in part because of the Cold War and ensuing East-West competition, development aid was pouring into the Red Sea countries. A fraction of these funds were assigned to fisheries development projects, which led to an improvement in documented knowledge about the fisheries (catches, catch composition, gear, etc). A regional project for the Red Sea area, ‘Development of fisheries in areas of the Red Sea and Gulf of Aden’, was carried out from the end of the 1970s until the mid-1980s and led to an improvement of the quality (comprehensiveness and taxonomic resolution) of fishery catch data. Additional sources were also used, notably tax offices and export records. For example, the catch of the Eritrean beach seine small pelagic fishery was reconstructed from export figures for fish meal, which was the output of the fishery (Ben-Yami 1964).

Organized databases and/or annual fishery statistical reports are a relatively new development for the Red Sea countries. The oldest database is that of Egypt, which starts in 1979, while Saudi Arabia started publishing its annual fishery statistics in the 1980s. Eritrea has had annual reports since its independence in 1991, but its fishery database started only in 1996. Sporadic annual reports are available for Yemen and a database system is being established. Sudan does not have any fishery data reporting system yet; however, daily catch data are collected at the main fishing market of Port Sudan, which are stored, but not issued as annual reports. All these sources were accessed for the catch reconstruction of the respective countries.

Once the sources were accessed, their contents were analyzed for their spatial, temporal and sectoral coverage. Some reports were written only for a certain section of the countries or only a specific sector of the fisheries. Then, the sources were critically examined with regards to the method(s) and assumptions used in collecting their data. For some years, data were available from different sources, some simply regurgitating previously reported data. In such cases, an effort was made to locate the original reports. When there were multiple independent sources, the ones which have detailed explanations of the methodology and comprehensive coverage were selected. In a few cases, the information from one source was used to correct data from another.

Interviews

Field interviews were conducted by the first author with fishers ranging from 15 to 82 years of age, and with fishing village elders and the employees of fisheries administrations (Tesfamichael et al. in press). The main goal of the interviews was to assess long-term change in fisheries productivity by accessing fishers’ memories, which provided two major inputs to the catch reconstructions. First, the interviews were very useful in filling data gaps. For some periods there were no records at all, so interviewees were asked to explain what occurred during those periods, i.e., whether the catches were higher or lower than, or about equal, to the adjacent periods with records. The other type of information supplied by the interviews was the unreported catch, i.e., the catch missed by official records. For many artisanal fisheries in the Red Sea, this included the catch given freely to some members of the community and the catch landed at remote landing places, away from data collectors. Regarding the former, there is a strong tradition, shared by the maritime cultures of Red Sea countries, that part of the catch is expected to be given freely to family, friends and people who need assistance (e.g., the elderly, disabled, and widows). The amount given freely is called ‘kusar’ and is a form of food security social network. Not to give ‘kusar’ leads to loss of prestige, which may have serious consequences, e.g., with regards to market transactions and eventual marriages. The amount was about half of the total catch in the 1950s and 1960s; however, as the catches started to decrease and the fish accrued market value, the proportion of the catch devoted to kusar started to decrease.

Another input from the interviews was explanations of discrepancies among reports. The insights from older fishers and people who have been involved in the management of fisheries helped resolve ambiguities in reports and/or records. Although they did not give specific quantitative values, their ability to give comparative qualitative information helped to base the assumptions used in quantifying the catch. In the absence of any other source, anecdotal information can be a good starting point (Pauly 1995) and quantitative data can be inferred from qualitative information, given some anchoring (Tesfamichael and Pitcher 2007).

8

Missing data

For the years data were missing, interpolations or extrapolations were made to fill in the data gaps. These were made on the basis of explicitly stated assumptions, given the best knowledge of the fisheries available at the time. Population size and per capita consumption were frequently used as a proxy for inferring catches. In a few instances, information from one country was used for another country with a similar fishery, particularly in the case of catch composition data.

Comparison and compilation

Using the different sources and procedures, the catches of each country were reconstructed by sector, and the catch compositions were inferred. Then, the reconstructed catches were compared to the catch data reported to FAO by the respective country. The FAO data is used a reference for comparison because it is a good source of time series catch data for the Red Sea countries and is used by many organization (local and foreign) for analysis and planning. Thus, the part of the reconstructed catch of a given taxon that was accounted for in the FAO data was assigned as ‘reported’ catch in our analysis and results. When the reported catch of a taxon was higher than what is reported for that taxon in the FAO database, the difference was assigned to the ‘unreported’ catch; in contrast, when the FAO catch for a taxon was higher than the reconstructed catch, it was assigned as ‘over-reported’ catch. As will be seen in the country chapters, reported and unreported catches are identified separately in the catch reconstruction. Note that if there was a part of the catch that was not reported (e.g., catches were sold outside landing sites where catch data recordings are carried out and we managed to get an estimate of the amount), then that part of the catch is referred as ‘unreported’ catch in our computations. This should not be confused with the reported and unreported catches of the results as compared to the FAO data. Once the catches were reconstructed for each country, by sector and the catch composition calculated, they added up to represent the catches of the Red Sea as a whole, i.e., as a Large Marine Ecosystem (see also www.seaaroundus.org/lme/33.aspx).

summary results and disCussion

The total reconstructed catch from the Red Sea from 1950 to 2010 was 6,333,000 tonnes, 1.5 times higher than what is reported to FAO by the surrounding countries for the same period. The total catch was low (around 50,000 t·year-1) until 1960, when it started its first increase until a decline in the early 1970s (Figure 3, Appendix Table A1), due to the war between Israel and the Arab countries in the region. The catch increased again from the mid-1970s, until it reached its peak of 177,000 tonnes in 1993. This phase is characterised by massive boat motorization and the introduction of industrial fishing by several Red Sea countries. This increased the effort and also allowed the expansion of the fisheries to areas they did not access previously. The total catch remained high, with some fluctuations, until the mid-2000s when it started to decline. This decline is here interpreted as a sign of resource depletion, especially in Yemen (Tesfamichael et al. 2012b).

The reconstructed catch was higher than the FAO data, except for the last few years. An obvious reason why the reconstructed catch is generally higher is that we included discards, subsistence and recreational fisheries, which are not usually included in FAO data for the Red Sea. The higher FAO catch in the last few years of our analysis was caused by double counting of some fishery catches in the FAO database. This is due mainly to Egypt fishing outside its EEZ in the waters of Sudan, Eritrea and Yemen, and reporting all their catches as Egyptian, while Sudan, Eritrea and Yemen report some of these same catches to FAO as well, as they are taken within their EEZ. One can argue this catch should be reported by area, i.e., by the EEZ it was taken from, or by the country that has taken it. Here, in view of the current emphasis on ecosystem-based fisheries management, we focused on the area, i.e., the EEZ from which the catch originates, as it provides the spatial context for fisheries management. For completeness, we also indicate, in the database, the country fishing. Presently, there is no a regional fishery management agency for the Red Sea LME, and whatever management there is extends only to national schemes, pertaining to single EEZ. By country, Yemen has the highest percentages of the Red Sea catch (36%), followed by Egypt (28%), Saudi Arabia (23%), Eritrea (11%) and Sudan (2%), while Jordan and Israel contribute less than 0.2% each.

The artisanal fisheries accounted for 49% of the total catch from 1950 to 2010 (Figure 4, Table A2). Their contribution was dominant throughout the whole period, unlike the industrial sector (22%), which is important only in the later part of the period covered here. This has major economic and social implications, as artisanal fisheries employ a higher number of fishers per tonne of catch (Pauly 2006), which translates to higher employment and livelihood in the communities. The discards (near exclusively from industrial fishing), which are usually ignored in official reports, represented 16% of the total catch. The subsistence catch was 12%, while the recreational fishery (1%), which started

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (1

0 t)3

0

100

50

200

150

Yemen

EgyptSaudi Arabia

Eritrea

SudanIsrael

Jordan

FAO Red Sea total

Figure 3. Reconstructed catch of the countries bordering the Red Sea from 1950 to 2010 and its comparison to the data reported to FAO.

Introduction - Tesfamichael and Pauly 9

only recently, is still negligible. Egypt is the country with the most developed recreational fishery and even in that country, recreational catches are low.

Comparing the reconstructed catch with the FAO data at taxonomic level, only 42% of the reconstructed catch was accounted in the FAO data, i.e., the reported catch (Figure 5, Table A3). The remaining 58% was not accounted at all, which included 43% unreported, but landed catch and 15% discarded catch, which is not landed and thus unreported as well.

A total of 209 taxa or taxonomic group were identified as contributing to Red Sea catches, in addition to a group ‘others’ encompassing the minor taxa that were not represented separately. The taxa contributing most to the catch was Indian mackerel (Rastrelliger kanagurta; 8%), Spanish mackerel (Scomberomorus commerson; 7%), and jacks (Carangidae; 7%). Emperors (Lethrinidae) and ponyfishes (Leiognathidae) each accounted for 5% of the total catch, the former prized fishes, the latter the dominant taxon in the discarded catch of industrial trawlers. These percentages suggest that there is no a single taxon that is overly dominant in the Red Sea fisheries, a reflection of their multi-species nature, and one of the main challenges in managing the Red Sea fisheries. The major taxonomic groups of the total catch composition are presented in (Figure 6). Only few taxa are included here for better visual effect of the figure. Appendix Table (A4) has a large list of the taxonomic composition.

In the following, a brief per-country account is given, starting with Egypt and moving counter-clockwise along the Red Sea coast as the different chapters are introduced. For Egypt (Chapter 2), the reconstructed catch is higher than the fisheries catch statistics that Egypt submits to FAO from the beginning of 1960s until the beginning of 1990s, but the reverse occurs after the mid-1990s. This discrepancy is due to the fact that Egypt fishes outside its own waters (e.g., in Eritrean waters starting early 1990s (Tesfamichael and Mohamud 2012) and these catches are not included in the reconstruction (Tesfamichael and Mehanna 2012), as the focus of the reconstruction is to quantify the amount fished in the waters of various countries (also clearly identifying the fishing country) and not where they landed. The catch of Egyptian vessels from Eritrean waters is reported in the reconstruction of Eritrea.

The Sudanese data (Chapter 3) submitted to FAO does not include the catches of shells (trochus and mother-of-pearl) fishery, which was very important before 1980s. Generally, there is no large difference between the reconstructed data and data submitted to FAO for Sudan. The sudden spike of Sudanese catch reported to FAO in 1983, on the other hand, is likely due to a reporting error, as there was no major change in the fisheries likely to cause such a sudden jump for only one year. The higher catches reported to FAO after the 1990s are also suspicious, as they contradict locally available data (Tesfamichael and Elawad 2012).

For Eritrea (Chapter 4), Yemen (Chapter 5) and Saudi Arabia (Chapter 6), the reconstructed catches are higher than those reported to FAO, due to the latter not including various fisheries and omitting discards. The major discrepancies between the reconstructed data and data submitted to FAO for Eritrea are in the early decades (1950s and 1960s) and later, after 2000. Between those periods the fishery was largely inactive, hence catches were low (Tesfamichael and Mohamud 2012). For Yemen in the Red Sea, the reconstructed catch is higher than the reported catch, the difference being more consistent for Yemen than for any other country (Tesfamichael et al. 2012b). There

Figure 6. The major taxonomic composition of the total reconstructed catch of the Red Sea from 1950 to 2010.

Figure 5. Reconstructed catch of the Red Sea fisheries by components from 1950 to 2010.

Figure 4. Reconstructed catch of the Red Sea fisheries by sector from 1950 to 2010.

10

is clear difference between the reconstructed and reported catch for Saudi Arabia in the Red Sea until the mid-1980s. After the mid-1980s, trawlers were introduced into the Saudi fishery, and hence the differences between the two data sets consist mainly of discard (Tesfamichael and Rossing 2012). The reconstructed catches of Israel and Jordan (Chapter 7) are negligible compared to those of the other countries (Tesfamichael et al. 2012a), which is understandable given their minuscule footholds in the inner Gulf of Aqaba. They also exhibited less fluctuation than the FAO data.

In addition to the catch reconstruction for each country bordering the Red Sea, a list is provided of common commercial fishes caught by the fisheries in the Red Sea and their corresponding local names (Chapter 8). The names include valid scientific names, common English names, local (Arabic) names written in both Arabic script and Roman characters. We believe this will helps researchers, resource users and managers. A brief reconstruction of the effort of the Red Sea fisheries is provided as an appendix, by country and split between the artisanal and industrial sector. Jointly, the information presented here can help in better understanding the Red Sea and provide a basis for the management schemes that the future will require (Tesfamichael 2012).

aCknowledgements

Compiling a long time series catch data involves many people. We are very grateful for the support and cooperation we received from the fisheries administration of the Red Sea countries. Without their involvement and sharing their information and data, this work would not have been possible. We have been helped by many fishers and managers who shared their knowledge and expertise during the interviews. We thank their time and insight. There were few individuals in each country that should be acknowledged individually. However, as their contributions were country-specific, we have opted to thank them in each country’s chapter. Here, we would like to mention and express our gratitude to the following people for their help overall: UBC librarian Sally Taylor for helping us locate old records, Dirk Zeller and Kyrstn Zylich for reviewing the database and the reports, and their insights, Evelyn Liu for drafting all our figures, Christopher Hoornaert for the GIS maps and Melanie Ang for formatting the report. This research was supported by Sea Around Us, a scientific collaboration between the University of British Columbia and The Pew Charitable Trusts. Additional support was obtained from Eritrea’s Coastal, Marine & Island Biodiversity Conservation Project (ECMIB).

referenCes

Al-Khol AA and El-Hawary MM (1970) Some penaeids of the Red Sea. Bull. Inst. Oceanogr. Fish., Cairo 1: 339-377.Alder J, Cullis-Suzuki S, Karpouzi V, Kaschner K, Mondoux S, Swartz W, Trujillo P, Watson R and Pauly D (2010)

Aggregate performance in managing marine ecosystems of 53 maritime countries. Marine Policy 34(3): 468-476.

Alverson DL, Freeberg MH, Murawski SA and Pope JG (1994) A global assessment of fisheries bycatch and discards. FAO, Rome. 233 p.

Atkins WSaP (1965) Development of fishing industry in Ethiopia. W. S. Atkins and Partners, Surrey and Addis Ababa. 282 p.

Ben-Tuvia A (1968) Report on the fisheries investigation of the Israel South Red Sea expeditions, 1962. Sea Fish Res. Stn. Haifa, Bull. 52: 21–55.

Ben-Yami M (1964) Report on the Fisheries in Ethiopia. Min. of Foreign Affairs, Dep. for International Cooperation, Jerusalem. 106 p.

Beverton RJH and Holt SJ (1957) On the Dynamics of Exploited Fish Population. Chapman & Hall, London.Braithwaite CJR (1987) Geology and palaeogeography of the Red Sea region. pp. 22–44 In Edwards AJ and Head SM

(eds.), Red Sea. Pergamon press, Oxford.Caddy JF and Gulland JA (1983) Historical patterns of fish stocks. Marine Policy 7(4): 267-278.Chakraborty D (1983) Marine fisheries statistics in Sudan–an expanded plan of development. FAO, Rome. 39 p.Chakraborty D (1984) Fish landings on the Red Sea and Gulf of Aden coast of the member countries: A preliminary

estimate. Development of Fisheries in Areas of the Red Sea and Gulf of Aden, United Nations Development Programme (UNDP) and Food and Agriculture Organization (FAO) of the United Nations, Suez, Egypt. 29 p.

Christensen V, Guénette S, Heymans JJ, Walters CJ, Watson R, Zeller D and Pauly D (2003) Hundred-year decline of North Atlantic predatory fishes. Fish and Fisheries 4(1): 1-24.

Edgren G (1993) Expected economic and demographic developments in coastal zones world wide. In Beukenkamp P, Gunther R, Klein R, Misdorp D and Sadacharan LDV (eds.), World Coast ‘93, Noordwijk, The Netherlands. 367–370 p.

Edwards FJ (1987) Climate and oceanography. pp. 45–69 In Edwards AJ and Head SM (eds.), Red Sea. Pergamon press, Oxford.

El-Saby MK and Farina L (1954) Report to the government of Saudi Arabia on possibility for development of marine fisheries. FAO, Rome.

Evans PGH (1987) Sea birds of the Red Sea. pp. 315–338 In Edwards AJ and Head SM (eds.), Red Sea. Pergamon press, Oxford.

Forsskål P (1775) Descriptiones animalium, avium, amphibiorum, piscium, insectorum, vermium; quae in itinere orientali observavit. Hauniae, Copenhagen.

Introduction - Tesfamichael and Pauly 11

Frazier J, Bertram GC and Evans PGH (1987) Turtles and marine mammals. pp. 288–314 In Edwards AJ and Head SM (eds.), Red Sea. Pergamon press, Oxford.

Frihy OE, Fanos AM, Khafagy AA and Abu Aesha KA (1996) Human impacts on the coastal zone of Hurghada, northern Red Sea, Egypt. Geo-Marine Letters 16(4): 324-329.

Garibaldi L (2012) The FAO global capture production database: A six-decade effort to catch the trend. Marine Policy 36(3): 760-768.

Getahun A (1998) The Red Sea as an extension of the Indian Ocean. pp. 277-281 In Sherman K, Okemwa EN and Ntiba MJ (eds.), Large marine ecosystems of the Indian Ocean: Assessment, sustainability, and management. Blackwell Science, Cambridge, MA.

Girdler RW and Southren TC (1987) Structure and evolution of the northern Red Sea. Nature 330(6150): 716-721.Goren M (1986) A suggested model for the recolonization process of the Red Sea at the post glacial period. In Uyeno

T, Arai R, Taniuchi T and Matsuura K (eds.), Int. Conf. on Indo-Pacific Fishes, 29 Jul-Aug 3 1985, 29 Jul-Aug 3 1985, Tokyo (Japan).

Grofit E (1971) The Red-Sea fisheries of Ethiopia (1966–1969). Min. of Foreign Affairs, Dep. for International cooperation, Jerusalem. 82 p.

Gulland JA, editor (1971) The fish resources of the ocean. Fishing News Books, Surrey, U.K.Gulland JA (1975) Manual of methods for fisheries resource survey and appraisal. Part 5. Objectives and basic methods.Harley SJ, Myers RA and Dunn A (2001) Is catch-per-unit-effort proportional to abundance? Canadian Journal of

Fisheries and Aquatic Sciences 58: 1760-1772.Head SM (1987a) Introduction. pp. 1–21 In Edwards AJ and Head SM (eds.), Red Sea. Pergamon press, Oxford.Head SM (1987b) Red Sea fisheries. pp. 363-382 In Edwards AJ and Head SM (eds.), Red Sea: Key Environments.

Pergamon press, Oxford.Hilborn R and Walters CJ (1992) Quantitative fisheries stock assessment. Choice, dynamics and uncertainty. Chapman

and Hall, New York.Horton M (1987) The human settlement of the Red Sea. pp. 339–362 In Edwards AJ and Head SM (eds.), Red Sea.

Pergamon press, Oxford.Kelleher K (2004) Discards in the world’s marine fisheries: An update. FAO, Rome. 134 p.Kleiber P and Maunder MN (2008) Inherent bias in using aggregate CPUE to characterize abundance of fish species

assemblages. Fisheries Research 93(1–2): 140-145.Klunzinger CB (1870) Eine zoologische Excursion auf ein Korallenriff des rothen Meeres. Verhandlungen der

zoologisch-botanischen Gesellschaft Wien 20: 389-394.Klunzinger CB (1872) Zoologische Exkursionen auf ein Korallenriff des Rothen Meeres bei Kossér. Zeitschrift der

Gesellschaft für Erdkunde zu Berlin 7: 20-55.Klunzinger CB (1878) Upper Egypt: its people and its products. A descriptive account of the manners, customs,

superstitions, and occupations of the people of the Nile Valley, the desert, and the Red Sea coast, with sketches of the natural history and geology: ixv, 1-408, figs. Blackie and Son, London.

Kristjonsson H (1956) A brief survey of the Sudanese red sea fisheries–Report to the government. FAO, Rome.Larkin PA (1977) An Epitaph for the Concept of Maximum Sustained Yield. Transactions of the American Fisheries

Society 106(1): 1-11.Lisac H (1971) Report to travel to Yemen Arabic and the People’s Republic of Southern Yemen, (16 January–1 February

1972) FAO Fish. Travel Aide Mem., FAO, Rome.Losse G (1973) Marine resources of the Yemen Arabic Republic. A report prepared for the the UNEP/FAO Food and

Nutrition programme 1973.Luksch J (1898) Expedition S. M. Schiff “Pola” in das Rothe Meer, Nördliche Hälfte (Oct. 1895-May 1896).

Wissenschaftliche Ergebnisse. VI. Physikalische Untersuchungen. Denkschrifte der Akademie der Wissenschaften (Mathematische-Naturwissenschaftliche Klasse) 65: 351-422, Wien.

Luksch J (1900) Expedition S. M. Schiff “Pola” in das Rothe Meer, Südliche Hälfte (September 1897-April 1898). Wissenschaftliche Ergebnisse. XVIII. Physikalische Untersuchungen. Denkschrifte der Akademie der Wissenschaften (Mathematische-Naturwissenschaftliche Klasse), Wien.

Makris J and Rihm R (1991) Shear-controlled evolution of the Red Sea: pull apart model. Tectonophysics 198(2-4): 441-466.

Mohammed E (2003) Reconstructing fisheries catches and fishing effort for the southeastern Caribbean (1940-2001): General methodology. University of British Columbia, Vancouver, BC (Canada) Fish. Cent.

Morcos SA (1970) Physical and chemical oceanography of the Red Sea. Oceanogr. Mar. Biol 8: 73-202.Norman J (1939) Fishes. pp. 1–116 In History) BMN (ed.), The John Murray expedition 1933–1934: Scientific

reportsVII London.Ormond R and Edwards A (1987) Red Sea fishes. pp. 251–287 In Edwards AJ and Head SM (eds.), Red Sea. Pergamon

press, Oxford.Pauly D (1995) Anecdotes and the shifting baseline syndrome of fisheries. Trends in Ecology & Evolution 10(10): 430.Pauly D (1998) Rationale for reconstructing catch time series. Bulletin. EC Fisheries Cooperation/Bulletin. CE

Cooperation Peche. Brussels 11(2): 4-10.Pauly D (2006) Major trends in small-scale marine fisheries, with emphasis on developing countries, and some

implications for the social sciences. Maritime Studies 4(2): 7-22.Pauly D and Froese R (2012) Comments on FAO’s State of Fisheries and Aquaculture, or ‘SOFIA 2010’. Marine Policy

36(3): 746-752.

12

Pauly D and Watson R (2008) Adjusting for context in evaluating national fisheries statistics reporting systems. pp. 57-61 In Alder J and Pauly D (eds.), A comparative assessment of biodiversity, fisheries and aquaculture in 53 countries’ exclusive economic zones. Fisheries Centre Research Reports 16(7), Vancouver, Canada.

Pauly D and Zeller D (2003) The global fisheries crisis as a rationale for improving the FAO’s database of fisheries statistics. pp. 1–9 In Zeller D, Booth S, Mohammed E and Pauly D (eds.), Western Central Atlantic and Brazil: fisheries catches and ecosystem models in the second half of the 20th century. Fisheries Centre Research Reports, Vol. 11 (6), Vancouver, Canada.

Pilcher N and Alsuhaibany A (2000) Regional status of coral reefs in the Red Sea and the Gulf of Aden. pp. 35–64 In Wilknson C (ed.), Status of coral reefs of the world: 2000. Australian Institute of Marine Science, Dampier

Pitcher TJ (1995) The impact of pelagic fish behaviour on fisheries. Scientia Marina 59(3-4): 295-306.Pitcher TJ (2005) Back-to-future: a fresh policy initiative for fisheries and a restoration ecology for ocean ecosystems.

Philosophical transactions of the royal society 360(1453): 107-121.Pitcher TJ, Watson R, Forrest R, Valtysson HP and Guenette S (2002) Estimating illegal and unreported catches from

marine ecosystems: a basis for change. Fish and Fisheries 3(4): 317-339.Preen A (1989) Dugongs Vol. 1. The status and conservation of Dugongs in the Arabian Region. MEPA Coastal and

Marine Management Series, MEPA, Jeddah. 200 p.Punt AE and Smith ADM (2001) The gospel of maximum sustainable yield in fisheries management: birth, crucifixion

and reincarnation. pp. 41-66 In Reynolds JD, Mace GM, Redford KR and Robinson JR (eds.), Conservation of Exploited Species Cambridge University Press, UK.

Raitsos DE, Hoteit I, Prihartato PK, Chronis T, Triantafyllou G and Abualnaja Y (2011) Abrupt warming of the Red Sea. Geophysical Research Letters 38(14): L14601.

Sadovy Y and Domeier M (2005) Are aggregation-fisheries sustainable? Reef fish fisheries as a case study. Coral Reefs 24(2): 254-262.

Scott Baker C and Clapham PJ (2004) Modelling the past and future of whales and whaling. Trends in Ecology & Evolution 19(7): 365-371.

Sheppard C, Price A and Roberts C (1992) Marine ecology of the Arabian region: Patterns and Processes in Extreme Tropical Environments. Academic press, London.

Smeed DA (2004) Exchange through the Bab el Mandab. Deep Sea Research (Part II, Topical Studies in Oceanography) 51(4-5): 455-474.

Sparre PJ (2000) Manual on sample-based data collection for fisheries assessment: Examples from Viet Nam. FAO, Rome. 171 p.

Stagl V, Sattmann H and Dworschak PC (1996) The material of the “Pola” Red Sea Expeditions (1895-1898) in the collections of the Natural History Museum in Vienna. In Uiblein F, Ott J and Stachowitsch M (eds.), Deep-sea and extreme shallow-water habitats: affinities and adaptations. Biosystematics and Ecology Series 11:29-41.

Tesfamichael D (2005) Reconstructing the John Murray/Mabahiss expedition. The Sea Around Us Project Newletter (29): 4.

Tesfamichael D (2012) Assessment of the Red Sea ecosystem with emphasis on fisheries. PhD, University of British Columbia, Resource Management and Environmental Studies, Vancouver. 241 p.

Tesfamichael D and Elawad AN (2012) Reconstructing Red Sea fisheries of Sudan: Foreign aid and fisheries. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D, Govender R and Pauly D (2012a) Preliminary reconstruction of fisheries catches of Jordan and Israel in the inner Gulf of Aqaba, Red Sea, 1950-2010. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D and Mehanna SF (2012) Reconstructing Red Sea fisheries of Egypt: Heavy investment and fisheries. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D and Mohamud S (2012) Reconstructing Red Sea fisheries of Eritrea: A case study of the relationship between political stability and fisheries development. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D and Pauly D (2011) Learning from the Past for Future Policy: Approaches to Time-series Catch Data Reconstruction. Western Indian Ocean J. Mar. Sci. 10(2): 99-106.

Tesfamichael D and Pitcher TJ (2006) Multidisciplinary evaluation of the sustainability of Red Sea fisheries using Rapfish. Fisheries Research 78(2-3): 227-235.

Tesfamichael D and Pitcher TJ (2007) Estimating the unreported catch of Eritrean Red Sea fisheries. African Journal of Marine Science 29(1): 55-63.

Tesfamichael D, Pitcher TJ and Pauly D (in press) Assessing changes in fisheries using fishers’ knowledge to generate long time series of catch rates: a case study from the Red Sea. Ecology and society.

Tesfamichael D and Rossing P (2012) Reconstructing Red Sea fisheries catches of Saudi Arabia: National wealth and fisheries transformation. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D, Rossing P and Awadh H (2012b) The marine fisheries of Yemen with emphasis on the Red Sea and cooperatives. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Introduction - Tesfamichael and Pauly 13

Thunell RC, Locke SM and Williams DF (1988) Glacio-eustatic sea-level control on Red Sea salinity. 334(6183): 601-604.

Walker DI (1987) Benthic algae. pp. 152–168 In Edwards AJ and Head SM (eds.), Red Sea. Pergamon press, Oxford.Walter RC, Buffler RT, Bruggemann JH, Guillaume MMM, Berhe SM, Negassi B, Libsekal Y, Cheng H, Edwards RL,

von Cosel R, Neraudeau D and Gagnon M (2000) Early human occupation of the Red Sea coast of Eritrea during the last interglacial. Nature 405(6782): 65-69.

Walters C (1986) Adaptive Management of Renewable Resources. McMillan Publisher Co., New York. 374 p.Walters CJ and Bonfil R (1999) Multispecies spatial assessment models for the British Columbia groundfish trawl

fishery. Canadian Journal of Fisheries and Aquatic Sciences 56(4): 601-628.Watson R and Pauly D (2001) Systematic distortions in world fisheries catch trends. Nature 414(6863): 534-536.Zeller D, Booth S, Davis G and Pauly D (2007) Re-estimation of small-scale fisheries catches for U.S. flag island areas

in the Western Pacific: The last 50 years. US Fishery Bulletin 105(2): 266-277.Zeller D and Pauly D (2005) Good news, bad news: global fisheries discards are declining, so are total catches. Fish

and Fisheries 6(2): 156-159.

14Appendix Table A1: Reconstructed catch (in tonnes) of the countries bordering the Red Sea from 1950 to 2010 and its comparison to the data reported to FAO. Year FAO landings Reconstructed total catch Yemen Egypt Saudi Arabia Eritrea Sudan Israel Jordan1950 12,194 55,071 11,458 5,535 7,326 28,599 1,946 66 1421951 13,218 55,166 11,631 5,683 7,326 28,599 1,721 66 1421952 18,771 55,937 11,841 5,831 7,326 28,599 2,133 66 1421953 18,962 56,153 12,069 5,980 7,326 28,599 1,972 66 1421954 20,427 56,509 12,316 6,129 7,509 28,599 1,749 66 1421955 23,736 56,383 11,933 6,277 7,692 28,599 1,663 77 1421956 24,467 52,402 12,239 5,247 7,875 25,051 1,761 88 1421957 25,639 55,495 12,544 11,839 8,058 21,503 1,311 98 1421958 25,583 53,105 12,852 12,397 8,241 18,054 1,309 109 1421959 29,273 49,897 13,171 12,569 8,424 13,848 1,622 120 1421960 30,129 48,235 13,500 11,270 8,608 13,166 1,418 131 1421961 32,139 60,342 13,842 18,417 8,791 17,684 1,324 142 1421962 42,712 69,555 14,201 30,454 8,974 14,157 1,475 153 1421963 41,084 76,642 14,554 37,841 9,157 13,159 1,626 163 1421964 37,392 81,296 14,899 41,475 8,167 14,661 1,777 174 1421965 39,282 91,316 15,225 41,750 9,428 22,657 1,928 185 1421966 38,426 83,324 15,525 29,647 10,039 25,695 2,080 196 1421967 36,809 80,393 15,810 29,328 10,805 22,325 1,783 206 1351968 36,041 77,079 16,086 29,087 11,803 18,365 1,393 217 1291969 38,671 79,475 16,362 28,904 13,265 18,888 1,713 222 1221970 40,010 87,412 20,510 28,776 13,293 22,406 2,085 227 1161971 46,233 89,365 20,363 30,224 13,322 23,797 1,319 231 1091972 41,963 82,974 19,679 33,699 13,699 13,886 1,672 236 1021973 27,277 59,395 19,535 16,728 14,075 7,162 1,580 241 751974 31,644 74,843 21,380 30,235 14,450 7,027 1,367 279 1051975 31,051 82,196 22,776 38,618 14,824 4,637 955 286 991976 34,349 91,687 24,410 46,756 15,196 3,393 1,562 292 781977 32,613 84,947 27,085 39,751 15,222 1,481 1,041 299 691978 36,728 88,218 28,647 37,422 19,160 1,258 1,355 305 701979 49,050 89,831 28,016 40,629 16,905 1,314 2,576 311 791980 44,233 83,142 27,530 36,123 15,516 1,758 1,781 346 881981 47,139 88,513 31,511 35,589 17,056 1,366 2,579 317 961982 47,100 95,047 34,218 35,868 20,950 1,455 2,328 122 1051983 50,018 95,561 27,847 42,473 20,685 2,223 2,106 113 1141984 50,104 98,079 27,068 43,490 22,916 2,036 2,262 151 1561985 62,333 100,831 29,651 35,339 31,376 1,699 2,364 204 1981986 62,597 105,332 32,528 35,118 33,141 1,724 2,420 206 1961987 83,220 114,395 33,863 35,659 40,138 1,452 2,892 196 1941988 90,283 124,165 37,033 38,649 44,163 980 2,959 187 1931989 106,386 138,613 42,429 48,012 43,304 759 3,764 155 1911990 101,623 133,641 42,859 46,970 40,401 533 2,567 122 1891991 114,136 148,208 59,018 41,520 44,500 535 2,354 90 1921992 118,048 152,994 63,539 43,715 41,921 1,058 2,408 158 1941993 135,085 176,943 79,390 49,255 44,525 1,005 2,431 141 1961994 137,648 171,632 81,409 33,231 49,503 5,017 2,080 175 2181995 131,708 162,695 78,507 34,120 40,353 6,913 2,342 214 2461996 119,382 141,913 65,977 30,834 37,766 4,346 2,457 296 2381997 133,088 167,935 88,038 33,507 42,108 1,501 2,312 240 2291998 131,384 163,244 89,499 28,347 39,500 2,714 2,758 206 2201999 155,244 171,199 89,922 24,983 40,500 12,598 2,764 166 2662000 139,742 164,542 69,768 33,454 37,485 20,626 2,762 190 2572001 134,293 157,725 69,699 28,684 39,431 16,703 2,738 190 2802002 142,696 168,085 78,402 32,044 38,497 15,570 3,189 95 2882003 136,406 169,269 80,393 31,586 37,820 15,565 3,575 94 2372004 138,811 159,861 76,315 31,993 29,180 16,545 5,410 168 2502005 124,519 139,738 64,934 24,249 34,396 10,442 5,310 141 2662006 128,752 137,630 58,872 22,783 34,329 18,769 2,486 140 2512007 118,105 117,813 48,884 23,247 38,206 4,634 2,469 113 2602008 117,069 122,244 49,752 26,002 38,406 3,853 3,864 112 2552009 126,212 121,131 46,728 26,662 38,601 5,683 2,993 132 3322010 124,397 116,368 44,358 24,279 38,796 6,721 1,873 99 242

Introduction - Tesfamichael and Pauly 15

Appendix Table A2: Reconstructed catch (in tonnes) of the Red Sea fisheries by sector from 1950 to 2010. Year Artisanal Industrial Discards Subsistence Recreational1950 44,191 557 1,848 8,475 01951 44,132 580 1,895 8,559 01952 44,737 604 1,939 8,658 01953 44,781 627 1,980 8,765 01954 44,920 650 2,019 8,920 01955 44,758 674 2,055 8,896 01956 41,722 429 1,177 9,074 01957 38,137 1,940 6,165 9,253 01958 35,002 2,140 6,529 9,434 01959 31,533 2,195 6,551 9,619 01960 30,470 4,110 3,818 9,837 01961 34,061 7,909 8,343 10,028 01962 30,687 14,056 14,618 10,194 01963 30,029 15,718 20,507 10,388 01964 32,193 13,490 25,797 9,815 01965 41,715 13,282 26,175 10,144 01966 45,494 10,676 16,675 10,479 01967 42,821 11,786 15,077 10,709 01968 39,437 13,017 13,642 10,966 161969 41,503 14,325 12,330 11,287 321970 45,903 16,295 13,729 11,387 1001971 46,799 18,667 12,309 11,422 1681972 37,957 18,661 14,551 11,568 2371973 32,847 6,485 7,853 11,903 3061974 35,171 18,311 8,434 12,494 4331975 35,474 17,527 17,036 11,654 5051976 36,365 26,368 16,393 11,983 5781977 37,008 21,520 13,596 12,172 6511978 41,502 20,396 12,767 12,829 7241979 41,372 25,207 9,855 12,600 7971980 39,693 19,299 10,936 12,345 8681981 44,670 17,901 11,713 13,290 9401982 46,869 21,713 11,852 13,601 1,0121983 40,683 29,898 11,279 12,616 1,0841984 41,040 33,072 10,255 12,553 1,1591985 50,073 25,793 9,883 13,848 1,2341986 53,181 24,295 12,196 14,350 1,3101987 60,350 27,211 10,191 15,257 1,3861988 64,902 30,468 11,526 15,806 1,4621989 70,480 40,661 9,580 16,354 1,5381990 67,598 39,785 8,763 15,882 1,6131991 80,908 35,848 11,792 17,969 1,6911992 85,044 37,411 10,311 18,460 1,7691993 98,486 44,686 11,931 19,994 1,8461994 96,826 34,243 19,133 19,517 1,9131995 78,686 37,507 27,580 16,940 1,9821996 64,910 34,496 25,706 14,744 2,0561997 83,682 36,776 28,343 17,005 2,1291998 81,832 33,943 28,718 16,549 2,2021999 80,120 37,625 35,097 16,108 2,2472000 57,707 54,083 37,532 12,916 2,3022001 55,678 46,683 40,219 12,775 2,3702002 61,497 49,829 41,422 12,889 2,4482003 58,511 49,622 46,478 12,128 2,5302004 57,826 49,523 38,402 11,443 2,6672005 55,588 36,492 33,241 11,619 2,7982006 57,413 36,089 29,558 11,646 2,9232007 58,976 26,884 17,140 11,769 3,0432008 55,985 30,859 20,851 11,387 3,1612009 53,946 32,144 20,771 10,994 3,2762010 49,370 31,242 22,033 10,335 3,388

16Appendix Table A3: Reconstructed catch (in tonnes) of the Red Sea fisheries by components from 1950 to 2010.

Year Reported Unreported Discards1950 8,726 44,497 1,8481951 8,777 44,495 1,8951952 11,647 42,352 1,9391953 12,262 41,911 1,9801954 12,211 42,279 2,0191955 13,829 40,500 2,0551956 12,464 38,761 1,1771957 14,181 35,150 6,1651958 14,646 31,929 6,5291959 15,102 28,245 6,5511960 17,742 26,675 3,8181961 20,988 31,010 8,3431962 26,939 27,998 14,6181963 27,939 28,195 20,5071964 27,251 28,248 25,7971965 30,967 34,174 26,1751966 29,328 37,322 16,6751967 27,232 38,084 15,0771968 23,336 40,101 13,6421969 27,195 39,950 12,3301970 29,201 44,483 13,7291971 32,952 44,104 12,3091972 25,712 42,711 14,5511973 16,654 34,888 7,8531974 21,105 45,304 8,4341975 20,075 45,085 17,0361976 23,836 51,458 16,3931977 22,863 48,488 13,5961978 25,477 49,974 12,7671979 32,113 47,863 9,8551980 29,472 42,733 10,9361981 35,103 41,697 11,7131982 34,361 48,834 11,8521983 34,717 49,564 11,2791984 38,327 49,497 10,2551985 43,253 47,695 9,8831986 49,825 43,312 12,1961987 62,967 41,236 10,1911988 64,919 47,720 11,5261989 68,540 60,493 9,5801990 70,569 54,308 8,7631991 81,425 54,991 11,7921992 81,272 61,412 10,3111993 91,608 73,403 11,9311994 92,412 60,088 19,1331995 80,086 55,028 27,5801996 71,143 45,064 25,7061997 77,540 62,051 28,3431998 74,258 60,268 28,7181999 80,412 55,690 35,0972000 68,325 58,684 37,5322001 65,586 51,920 40,2192002 71,814 54,849 41,4222003 71,503 51,288 46,4782004 73,658 47,801 38,4022005 69,711 36,786 33,2412006 73,326 34,745 29,5582007 67,674 32,999 17,1402008 68,070 33,323 20,8512009 69,231 31,128 20,7712010 65,161 29,174 22,033

Introduction - Tesfamichael and Pauly 17

Appendix Table A4: The major taxonomic composition of the total reconstructed catch (in tonnes) of the Red Sea from 1950 to 2010. Year 1 2 3 4 5 6 7 8 9 10 11 12 13 141950 4,975 3,616 2,203 1,376 84 17,500 9,663 1,556 795 190 0 8 414 6281951 5,048 3,647 2,215 1,395 84 17,500 9,677 1,565 795 201 0 9 427 6371952 5,136 3,684 2,228 1,416 84 17,500 9,693 1,574 795 212 0 9 438 6491953 5,232 3,725 2,242 1,438 84 17,500 9,711 1,584 795 224 0 10 449 6611954 5,339 3,809 2,285 1,475 84 17,500 9,731 1,617 812 235 0 11 459 6751955 5,183 3,784 2,319 1,487 84 17,500 9,701 1,646 830 246 0 11 468 6541956 5,315 3,877 2,354 1,502 84 15,173 8,562 1,652 848 128 0 6 238 6711957 5,447 3,971 2,430 1,539 84 12,846 7,422 1,877 866 856 0 38 1,547 6881958 5,581 4,066 2,474 1,576 199 10,519 6,285 1,931 884 946 0 41 1,631 7041959 5,719 4,163 2,520 1,614 199 7,731 4,916 1,975 902 973 0 43 1,637 7221960 5,861 4,261 2,535 1,673 361 6,681 4,420 1,893 920 646 0 23 853 7401961 6,009 4,362 2,606 1,712 719 8,951 5,589 2,096 938 1,554 0 52 1,892 7591962 6,164 4,466 2,698 1,731 854 6,366 4,326 2,399 956 2,676 0 97 3,483 7781963 6,316 4,569 2,787 1,770 926 5,505 3,925 2,700 974 3,752 0 143 4,999 7981964 6,532 4,403 2,980 1,712 791 6,869 4,632 2,854 882 4,678 395 479 6,443 8171965 6,682 4,742 3,172 1,883 787 11,803 7,125 3,072 998 4,842 333 441 6,544 8341966 6,840 4,926 3,236 1,989 811 13,312 7,904 2,730 1,055 3,241 413 428 4,040 8511967 7,230 5,145 4,083 2,069 789 14,466 1,271 2,746 1,126 3,000 1,490 1,209 3,631 8661968 7,476 5,413 4,604 2,169 827 8,006 1,294 2,835 1,221 2,804 1,951 1,537 3,238 8821969 7,732 5,784 5,199 2,307 905 7,350 4,993 2,979 1,357 2,636 2,412 1,866 2,861 8971970 7,962 5,835 5,612 2,409 1,726 10,675 6,692 2,953 1,379 2,762 2,872 2,194 2,500 9131971 8,158 5,831 6,221 2,444 1,617 11,200 6,977 2,915 1,401 2,509 3,705 2,797 2,194 9131972 8,216 5,954 6,082 2,518 1,337 8,006 1,398 3,146 1,455 3,048 3,400 2,603 3,001 9291973 8,113 6,238 4,151 2,619 884 2,691 1,418 2,927 1,508 1,709 758 613 1,564 9961974 9,903 6,723 6,685 2,809 611 3,084 1,450 3,087 1,574 1,822 4,080 3,066 1,870 1,1261975 10,358 7,112 5,851 2,948 487 1,411 1,483 3,681 1,628 3,756 2,724 2,159 4,215 1,2261976 11,617 7,444 7,789 3,026 554 250 1,520 3,783 1,757 3,663 5,291 4,040 4,013 1,3101977 12,423 7,869 7,103 3,034 339 0 1,552 3,675 1,753 3,045 4,302 3,291 3,344 1,4461978 12,883 8,900 7,552 3,430 477 0 1,573 4,116 2,132 2,841 4,101 3,134 3,021 1,5011979 7,920 7,381 8,476 4,876 192 0 1,598 4,172 3,127 2,316 5,789 4,355 2,507 1,4581980 7,276 6,962 6,853 4,810 58 289 1,659 4,150 3,108 2,491 3,907 2,987 2,847 1,4181981 8,076 8,300 7,379 5,281 128 198 1,843 3,941 3,556 2,973 1,788 3,154 3,021 1,6271982 9,039 8,685 8,515 5,731 1,742 200 1,881 3,859 3,618 2,443 2,579 4,154 2,388 1,7731983 11,636 7,979 9,782 4,842 1,703 200 1,904 2,156 3,646 2,261 5,177 5,448 2,254 1,7621984 7,257 9,159 10,975 5,505 1,970 300 1,918 3,766 3,195 1,149 7,169 6,841 1,874 6171985 4,653 10,502 9,920 7,940 1,954 250 1,941 4,874 5,388 1,350 5,012 4,788 1,784 1,8131986 8,245 11,215 9,130 8,281 1,985 300 1,985 4,804 4,933 2,829 4,021 3,873 2,378 1,3241987 9,871 12,756 10,745 8,864 1,626 250 2,026 5,337 5,954 2,055 4,796 4,616 2,000 1,1751988 9,814 13,529 12,119 9,345 3,151 0 2,035 5,939 6,417 1,219 6,058 5,796 1,718 8831989 11,205 14,271 14,771 9,972 1,886 0 2,050 6,286 6,845 955 8,460 7,993 1,732 9001990 10,807 13,819 14,566 9,593 2,108 0 2,076 5,258 6,751 683 8,568 8,084 1,426 7981991 12,592 14,262 13,892 10,905 3,939 0 2,222 6,043 6,689 962 7,241 6,869 1,461 3,7891992 4,282 13,880 14,118 11,396 2,057 0 2,252 6,907 7,689 1,431 7,278 6,853 1,853 8,3891993 4,351 15,527 16,120 13,998 3,670 0 2,290 10,282 9,104 1,494 9,087 8,568 1,596 10,3311994 4,413 15,597 12,807 13,743 8,881 0 2,400 8,454 8,836 2,860 5,240 5,054 1,312 9,9531995 6,048 8,002 10,590 10,689 13,903 0 2,714 5,557 6,249 4,453 5,280 5,025 1,433 6,7441996 3,304 6,959 10,775 10,846 12,869 0 2,677 4,861 6,937 3,803 4,457 4,268 1,357 5,3951997 4,332 9,210 11,194 11,908 14,271 0 2,805 5,768 7,411 4,462 4,953 4,797 1,455 7,1271998 8,591 10,366 9,768 10,763 15,135 0 2,780 2,782 7,503 4,892 4,162 4,041 1,182 6,0361999 5,285 8,945 9,776 11,169 19,075 0 2,875 3,087 7,613 7,697 3,279 3,169 1,213 7,1522000 7,816 8,723 9,954 5,801 20,922 0 2,908 2,026 6,018 9,511 5,804 5,533 1,078 2,3412001 8,067 8,642 7,479 7,092 22,351 0 2,964 2,348 5,110 9,950 4,216 4,106 1,222 1,4942002 12,019 8,905 7,572 6,787 22,496 0 2,963 2,195 4,929 12,325 4,721 4,555 1,442 4652003 13,971 7,560 7,387 6,659 25,394 0 3,007 2,224 3,148 10,034 4,388 4,256 1,553 8532004 10,414 7,112 7,091 6,134 20,567 0 2,859 2,256 3,786 11,891 4,728 4,465 1,423 9702005 9,687 8,106 5,244 6,587 17,300 0 2,832 1,983 4,484 8,327 2,520 2,439 1,455 1,4592006 11,065 6,436 5,277 6,846 15,546 0 3,132 2,222 4,805 7,813 2,541 2,585 1,239 1,5942007 11,631 7,836 5,704 6,853 7,891 0 2,776 1,772 5,076 3,650 2,760 2,838 1,192 1,6062008 13,772 3,907 5,815 5,713 9,976 0 2,781 2,680 4,150 4,580 3,316 3,367 1,284 2,0742009 12,487 2,983 6,990 5,222 9,879 0 2,786 2,663 2,750 4,578 3,433 3,497 1,306 1,8532010 11,917 3,593 6,084 5,818 11,030 0 2,807 2,428 2,944 4,842 3,079 3,118 1,150 1,184

1: Rastrelliger kanagurta; 2: Scomberomorus commerson; 3: Carangidae; 4: Lethrinidae; 5: Leiognathidae; 6: Engraulidae; 7: Clupeidae; 8: Lutjanidae; 9: Serranidae; 10: Synodontidae; 11: Etrumeus sadina; 12: Decapterus spp.; 13: Leiognathus berbis; 14: Carcharhinidae

18

A4 continuedYear 15 16 17 18 19 20 21 22 23 24 25 26 27 281950 292 341 317 854 296 541 0 374 27 773 0 0 336 3181951 294 346 321 863 305 541 0 380 27 774 0 0 336 3241952 296 352 327 872 313 541 0 386 27 775 0 0 337 3301953 298 357 333 881 321 541 0 394 27 775 0 0 337 3381954 300 363 340 892 328 554 0 402 27 784 0 0 345 3451955 303 370 330 903 335 571 0 389 27 794 0 0 353 3361956 305 348 338 914 170 587 0 399 27 802 0 0 361 3431957 308 508 346 926 1,105 604 0 409 27 811 0 0 369 3521958 310 527 353 954 1,165 620 0 419 27 820 0 0 377 3611959 313 537 362 966 1,169 636 0 430 27 829 0 0 385 3711960 2,629 443 376 1,061 609 653 0 441 27 838 0 0 393 3811961 3,756 584 397 1,274 1,351 669 0 452 27 847 0 0 400 3911962 7,616 808 411 1,365 2,488 686 0 463 27 856 0 0 409 4011963 7,368 1,030 423 1,417 3,571 702 0 475 27 865 0 0 417 4121964 2,524 1,251 428 1,347 4,602 633 0 486 27 831 0 0 379 4221965 2,163 1,297 437 1,375 4,674 726 0 497 27 1,441 0 0 431 4351966 2,634 946 446 1,373 2,886 772 0 507 27 1,680 0 0 456 4411967 1,144 876 453 1,296 2,593 830 0 516 27 3,748 0 0 494 5291968 1,448 841 462 1,356 2,313 904 0 525 27 6,134 0 0 541 5381969 1,752 808 472 1,443 2,044 1,008 0 534 27 2,602 0 0 607 4661970 2,058 1,741 506 1,449 1,786 1,008 347 543 27 2,207 0 0 613 4791971 2,593 1,648 503 1,430 1,567 1,008 328 543 65 3,009 0 0 621 4801972 2,399 1,537 502 1,418 2,144 1,032 237 553 103 1,828 0 0 631 5691973 707 970 521 1,347 1,117 1,057 117 593 142 1,148 0 0 618 6011974 2,837 928 578 1,257 1,336 1,081 81 671 180 1,268 0 0 664 6651975 1,969 1,267 625 1,243 3,010 1,105 49 730 218 818 0 0 664 7141976 3,613 1,271 667 1,259 2,867 1,129 55 780 357 914 0 0 703 7501977 2,982 1,210 731 1,169 2,389 1,129 75 861 496 826 0 0 692 8211978 2,853 1,300 761 1,146 2,158 1,405 121 894 635 1,030 0 0 847 8481979 3,937 1,144 1,397 1,924 1,791 2,260 2 1,027 774 947 0 583 771 961980 2,731 1,279 1,359 1,877 2,033 2,141 0 999 913 865 0 567 694 711981 3,365 1,330 1,557 2,047 2,158 2,264 3 1,146 1,172 1,118 0 651 926 941982 3,560 1,514 1,697 2,093 1,706 2,310 7 1,248 1,298 1,128 0 709 963 761983 5,356 1,378 672 1,321 1,610 1,841 454 1,062 1,425 1,065 0 0 1,164 751984 1,452 2,080 1,615 2,447 1,339 1,611 7 656 1,551 773 3,171 0 1,260 651985 1,086 2,078 1,786 1,775 1,274 1,637 1,519 1,247 1,678 511 2,217 1,657 1,883 731986 917 2,064 1,352 3,321 1,699 977 1,579 998 1,746 528 1,779 1,717 1,985 691987 1,050 1,808 1,508 1,593 1,429 1,179 1,116 816 1,907 648 2,122 3,613 2,502 4731988 1,264 2,308 1,423 1,581 1,227 1,293 2,202 1,198 2,067 682 2,680 3,761 2,616 4191989 1,673 1,943 1,925 1,567 1,237 1,878 3,652 1,652 2,228 694 3,742 3,561 2,684 1,2631990 1,690 1,932 2,260 1,826 1,018 2,322 2,461 1,950 2,389 712 3,790 2,851 2,468 2,0721991 1,463 2,507 2,599 1,863 1,044 1,423 2,754 3,189 2,550 715 3,203 4,674 2,484 2,2851992 1,468 1,829 3,742 1,461 1,324 2,574 4,973 3,286 2,710 717 3,219 4,540 2,523 2,2951993 1,773 2,415 5,235 1,408 1,140 3,484 346 3,282 2,871 756 4,019 8,686 2,690 8611994 1,116 3,257 4,373 1,389 937 4,301 681 3,211 3,032 754 2,318 6,733 2,694 1,8551995 1,101 4,735 3,856 1,325 1,023 3,764 1,017 2,842 3,193 468 2,335 4,826 1,053 1,9741996 978 3,993 2,923 1,433 969 2,999 1,353 2,678 3,353 484 1,971 3,684 1,079 1,4941997 1,060 3,973 3,597 1,304 1,039 4,079 1,688 3,805 3,514 500 2,191 5,350 1,235 2,5891998 920 3,581 3,791 3,169 844 2,896 6,018 3,067 3,675 502 1,841 0 1,188 2,0441999 760 3,421 3,605 2,195 866 4,149 7,079 3,649 3,836 685 1,450 0 1,527 2,2392000 1,171 4,319 2,060 1,499 770 2,387 4,781 1,556 4,001 761 2,567 0 1,131 2,2182001 913 4,289 2,420 1,999 873 1,373 5,821 1,637 902 786 1,865 0 468 1,4942002 1,426 3,303 2,244 1,698 1,030 1,267 6,844 1,834 1,340 784 2,088 0 535 1,0472003 1,678 4,284 4,253 1,415 1,109 545 5,507 1,777 3,616 743 1,941 0 996 1,7522004 2,443 3,010 2,953 1,543 1,017 521 4,869 1,673 6,422 556 2,091 0 435 1,1072005 1,923 3,149 2,809 1,787 1,039 362 3,508 1,796 1,468 674 1,114 0 644 1,9112006 603 3,370 3,239 1,568 885 728 2,803 1,621 1,370 918 1,124 0 466 1,6002007 633 2,636 2,834 1,637 851 462 2,331 1,815 1,407 968 1,221 0 576 1,9742008 737 1,985 2,591 1,653 917 2,936 1,624 1,116 271 959 1,467 0 604 2,6602009 1,050 2,641 569 1,546 933 1,751 1,639 3,540 144 1,020 1,519 0 500 2,7282010 686 1,629 718 1,431 821 1,345 1,740 2,120 74 1,181 1,362 0 563 1,875

15: Sardinella spp.; 16: Penaeidae; 17: Sphyraenidae; 18: Mugilidae; 19: Champsodon capensis; 20: Scombridae; 21: Nemipterus spp.; 22: Trachurus spp.; 23: Holothuroidea; 24: Elasmobranchii; 25: Scomber japonicus; 26: Chrysoblephus spp.; 27: Sphyraena spp.; 28: Euthynnus affinis

Introduction - Tesfamichael and Pauly 19

A4 continuedYear 29 30 31 32 33 34 35 36 37 38 39 40 41 421950 305 178 89 369 594 1,365 65 118 374 150 0 105 446 791951 308 183 90 374 594 1,033 67 122 376 150 0 106 446 811952 312 188 92 379 594 1,530 68 125 378 150 0 108 446 831953 316 192 94 385 594 1,364 70 128 380 150 0 110 446 861954 320 197 97 391 609 1,159 72 131 391 150 0 112 446 871955 314 201 95 397 624 1,097 74 134 403 150 0 109 446 891956 319 102 90 401 639 1,129 54 68 410 150 0 112 446 451957 325 663 134 408 654 750 178 442 420 150 0 115 446 2951958 330 699 139 414 669 761 173 466 431 150 0 117 446 3111959 336 702 143 421 683 1,070 178 468 442 150 0 120 446 3121960 342 365 119 422 698 848 198 244 453 150 0 123 521 1621961 348 811 158 427 713 781 519 541 464 150 0 126 521 3601962 354 1,493 220 435 728 932 772 995 474 150 0 130 446 6631963 361 2,142 281 440 743 1,083 988 1,428 485 150 0 133 446 9521964 367 2,761 343 445 660 1,234 1,083 1,841 436 150 0 136 446 1,2271965 373 2,805 355 463 762 1,385 1,108 1,870 508 150 0 139 446 1,2471966 378 1,732 262 453 811 1,536 848 1,154 532 150 0 142 744 7701967 383 1,556 250 424 873 1,270 797 1,037 572 150 0 144 744 6921968 388 1,388 239 442 953 866 784 925 623 150 0 147 744 6171969 393 1,226 228 463 1,071 1,130 794 817 697 150 0 149 744 5451970 398 1,072 232 507 1,069 1,542 713 714 707 150 130 152 744 4761971 398 940 222 526 1,067 751 653 627 708 150 123 152 744 4181972 403 1,286 259 545 1,094 1,073 750 857 726 150 89 155 744 5721973 423 670 192 564 1,120 931 486 447 744 150 44 166 744 2981974 463 801 209 600 1,146 725 436 534 762 150 30 188 744 3561975 493 1,806 326 620 1,172 276 757 1,204 780 150 19 204 744 8031976 518 1,720 323 631 1,197 442 739 1,147 785 150 20 218 744 7641977 560 1,433 297 652 1,195 141 553 956 786 0 28 241 302 6371978 576 1,295 289 671 1,509 257 489 863 979 0 45 250 308 5751979 538 1,075 264 692 1,322 1,223 441 716 867 0 76 540 313 4781980 510 1,220 275 710 1,206 520 576 813 800 0 74 526 445 5421981 569 1,295 344 733 1,031 209 478 863 741 0 85 603 395 5751982 624 1,023 329 743 1,029 345 422 682 747 0 110 657 455 4551983 81 966 384 761 688 114 475 644 574 0 36 56 838 4291984 557 803 528 798 530 172 457 536 413 0 53 252 717 3571985 959 764 513 839 484 298 465 510 322 0 289 1,245 597 3401986 958 1,019 589 859 503 81 448 679 322 0 288 733 603 4531987 652 857 727 882 639 543 369 572 384 0 135 526 510 3811988 1,184 736 549 886 689 601 309 491 403 0 167 478 417 3271989 1,413 742 686 923 687 1,398 336 495 422 0 216 491 325 3301990 1,446 611 663 939 635 115 266 407 412 0 197 440 53 2721991 2,925 626 686 938 634 115 314 417 372 0 550 760 53 2781992 2,081 794 812 951 633 442 397 529 352 0 919 1,262 106 3531993 1,846 684 927 973 682 613 371 456 397 0 1,325 1,965 100 3041994 3,742 562 1,049 984 681 277 716 375 393 0 2,056 1,927 98 2501995 4,247 614 1,019 1,169 370 396 998 409 626 0 3,091 1,700 113 2731996 3,321 581 1,072 1,224 368 319 494 388 500 0 2,492 1,383 255 2581997 4,952 623 1,214 1,280 415 600 724 416 567 0 3,166 1,786 57 2771998 3,219 507 1,239 1,268 413 750 734 338 544 3 4,636 1,854 39 2251999 4,934 520 1,432 1,263 365 379 2,378 347 569 0 3,859 1,721 153 2312000 299 462 1,250 923 351 500 2,133 308 313 115 577 204 157 2052001 404 524 1,397 978 384 417 1,632 349 422 792 469 1,248 165 2332002 435 618 1,188 918 357 335 1,239 412 397 4,439 394 84 154 2752003 611 665 2,748 940 339 364 1,168 444 324 2,786 182 113 56 2962004 505 610 4,300 953 198 336 1,361 407 198 3,732 369 90 98 2712005 492 624 4,042 986 216 367 1,280 416 339 2,732 343 222 76 2772006 760 531 4,063 992 185 301 1,590 354 373 2,375 658 373 93 2362007 648 511 1,247 987 259 280 658 340 322 2,375 400 307 105 2272008 185 550 1,552 1,027 261 312 641 367 472 2,375 819 117 108 2452009 122 560 1,520 1,022 262 42 789 373 385 2,375 383 475 125 2492010 95 493 1,541 1,032 263 13 825 329 357 2,375 1,385 36 112 21929: Scomberoides spp.; 30: Equulites elongatus; 31: Sepiidae; 32: Sparidae; 33: Valamugil seheli; 34: Trochus spp.; 35: Nemipteridae; 36: Pseudorhombus arsius; 37: Scaridae; 38: Holothuriidae; 39: Haemulidae; 40: Rachycentron canadum; 41: Lutjanidae <Snappers>; 42: Charybdis hellerii

20A4 continuedYear 43 44 45 46 47 48 49 50 51 52 53 54 551950 9 21 17 5 0 67 170 314 209 0 39 39 01951 9 21 18 5 0 83 172 319 212 0 41 41 01952 9 21 19 5 0 98 174 325 216 0 42 42 01953 9 22 20 5 0 113 176 331 220 0 43 43 01954 9 22 21 5 0 128 178 338 225 0 44 44 01955 9 22 21 5 0 143 181 327 218 0 45 45 01956 9 140 12 5 0 127 183 336 224 0 23 23 01957 9 152 70 5 0 140 186 344 229 0 147 147 01958 22 164 77 0 0 152 188 353 235 0 155 155 01959 22 176 79 0 0 164 191 361 241 0 156 156 01960 41 229 47 0 0 176 191 370 247 0 81 81 01961 81 255 104 0 0 188 193 380 253 0 180 180 01962 96 259 187 0 0 201 196 390 259 0 332 332 01963 105 278 269 0 0 213 199 399 266 0 476 476 01964 89 305 348 0 0 225 211 409 272 0 614 614 01965 89 28 361 0 0 294 216 418 278 0 623 623 01966 92 360 233 0 0 249 214 426 284 0 385 385 11967 89 654 215 0 0 261 228 434 289 0 346 346 11968 93 559 198 0 0 274 249 441 294 0 308 308 11969 102 444 182 0 0 286 270 449 299 0 272 272 11970 195 30 177 58 58 369 293 457 304 0 238 238 11971 183 31 160 55 55 384 316 457 304 0 209 209 11972 151 31 208 39 39 400 309 465 310 0 286 286 11973 100 32 114 20 20 415 241 498 332 0 149 149 11974 69 33 131 13 13 430 329 564 375 0 178 178 11975 55 34 287 8 8 445 294 614 409 0 401 401 11976 54 399 281 9 14 371 361 656 437 0 382 382 11977 38 403 237 22 13 383 337 724 482 0 319 319 11978 43 423 222 29 26 395 332 752 500 0 288 288 11979 10 421 185 71 7 408 379 1 0 0 239 239 11980 7 477 173 73 0 406 329 1 0 0 271 271 11981 0 453 178 80 8 496 242 2 0 0 288 288 21982 0 581 321 88 112 399 255 3 0 0 227 227 1971983 0 581 174 126 110 364 319 6 0 0 215 215 1951984 0 544 145 21 127 358 232 7 0 0 179 179 2281985 0 233 161 91 126 526 233 10 0 0 170 170 2261986 0 267 226 722 128 448 233 11 1 0 226 226 2281987 0 293 263 663 105 388 233 14 1 0 191 191 1881988 0 288 416 546 203 367 233 12 2 0 164 164 3541989 0 313 373 444 122 482 233 15 2 0 165 165 2131990 0 291 345 273 136 609 232 13 2 1 136 136 2321991 0 378 408 747 254 319 230 14 2 1 139 139 4571992 0 358 638 1,923 133 165 229 16 2 3 176 176 2471993 171 367 547 2,267 237 311 227 16 2 3 152 152 2581994 467 468 524 1,720 502 284 224 17 3 3 125 125 5511995 692 1,091 687 2,719 795 210 203 21 115 3 136 136 8961996 736 785 608 9 800 266 219 18 65 1 129 129 7331997 859 905 602 2 918 314 216 28 76 10 139 139 7791998 1,069 749 534 1,388 951 175 212 22 82 8 113 113 6531999 1,622 736 637 504 1,016 81 202 26 106 7 116 116 5422000 1,975 990 676 1,230 1,059 90 183 26 89 1,203 103 103 3952001 2,141 718 743 753 1,176 119 196 27 115 1,264 116 116 3772002 2,102 644 849 472 1,338 115 171 26 116 1,066 137 137 4362003 2,395 990 977 412 1,412 111 167 25 211 1,118 148 148 4692004 1,986 601 854 745 1,134 96 164 20 219 715 136 136 2812005 1,495 655 809 215 996 122 175 101 147 1,020 139 139 4552006 1,373 560 703 472 747 86 171 114 96 1,122 118 118 3932007 488 468 503 235 492 65 163 135 205 1,202 113 113 3992008 668 488 582 504 644 59 173 43 929 1,107 122 122 4192009 688 620 562 149 610 61 164 46 1,036 1,287 124 124 4202010 848 566 509 150 666 54 161 40 618 1,150 110 110 421

43: Terapon spp.; 44: Brachyura; 45: Mullidae; 46: Ariidae; 47: Trichiuridae; 48: Epinephelus spp.; 49: Encrasicholina punctifer; 50: Dasyatidae; 51: Thunnus tonggol; 52: Lethrinus lentjan; 53: Clypeaster reticulatus; 54: Jacksonaster depressum; 55: Balistidae

Introduction - Tesfamichael and Pauly 21

A4 continuedYear 56 57 58 59 60 61 62 63 64 65 66 67 68 691950 0 7 140 3 3 0 0 132 0 1 209 28 6 1,9371951 0 7 141 3 3 0 0 132 0 1 212 28 6 2,0721952 0 7 143 3 3 0 0 132 0 1 216 29 6 2,0171953 0 7 145 3 3 0 0 132 0 1 220 30 6 2,0511954 0 7 146 3 3 0 0 132 0 1 225 31 6 2,0661955 0 7 148 3 3 0 0 132 0 1 218 31 6 2,0621956 0 7 150 3 3 0 0 132 0 1 224 16 6 1,8081957 0 7 152 3 3 0 0 132 0 1 229 103 7 3,0711958 0 8 155 6 6 0 0 132 0 1 235 109 7 3,0631959 0 8 157 6 6 0 0 132 0 1 241 109 7 3,0741960 0 8 157 12 12 0 0 154 0 1 247 57 7 2,7571961 0 8 158 23 23 0 0 154 0 1 253 126 7 4,4691962 0 8 161 28 28 0 0 132 0 1 259 232 7 6,1311963 0 8 163 30 30 0 0 132 0 1 266 333 7 7,4871964 0 7 164 26 26 0 0 132 0 1 272 430 7 8,6191965 0 9 169 25 25 0 0 132 0 1 278 436 8 8,9301966 0 9 166 26 26 0 0 220 0 1 284 269 8 6,2301967 0 10 155 25 25 0 0 220 0 1 289 242 9 6,0381968 0 11 162 27 27 0 0 220 0 1 294 216 10 5,7761969 0 12 169 29 29 0 0 220 0 1 299 191 11 6,4881970 58 12 177 56 56 0 29 220 0 1 304 167 11 6,0481971 55 12 178 52 52 0 27 220 0 1 304 146 11 5,7881972 39 12 179 43 43 0 20 220 0 1 310 200 11 6,6221973 20 13 179 29 29 0 10 220 0 1 332 104 11 4,2751974 13 13 180 20 20 0 7 220 0 1 375 125 12 4,9621975 8 13 180 16 16 0 4 220 0 1 409 281 12 7,2741976 14 14 179 18 18 0 7 220 0 1 437 268 12 7,3321977 13 14 180 11 11 0 6 86 0 1 482 223 12 6,2931978 26 17 181 15 15 0 13 88 0 1 500 201 15 6,0831979 7 15 183 6 6 0 3 90 0 1 0 167 13 8,0161980 0 14 183 2 2 0 0 127 0 1 0 190 12 8,0411981 8 34 185 4 4 0 4 113 0 3 0 201 30 8,8671982 2 160 185 56 56 0 56 130 0 5 0 159 51 9,2351983 2 190 182 55 55 0 55 239 0 9 0 150 88 8,0071984 2 222 188 64 64 0 64 205 0 11 0 125 108 9,1161985 4 253 192 63 63 0 63 171 0 15 0 119 147 7,5851986 6 272 193 64 64 0 64 172 0 17 0 159 171 7,8651987 7 285 195 52 52 0 52 146 0 22 0 133 214 9,6951988 9 361 196 102 102 0 102 119 0 18 0 115 182 10,1271989 11 311 197 61 61 0 61 92 0 23 0 115 228 9,4361990 13 301 197 68 68 0 68 43 0 20 0 95 200 9,4281991 3 438 196 127 127 0 127 43 0 22 0 97 213 11,4401992 3 336 194 66 66 0 66 86 0 25 0 124 240 13,0451993 101 347 192 118 118 0 118 81 0 25 0 106 243 14,7511994 199 518 192 307 286 0 251 79 0 25 0 87 249 15,1151995 296 788 177 465 448 0 397 90 0 797 0 96 311 15,8991996 394 639 190 415 415 3 400 195 0 695 0 90 262 13,1641997 492 820 187 461 460 3 459 98 0 1,012 0 97 418 16,7511998 593 659 182 488 488 2 476 84 0 598 0 79 326 15,8991999 724 642 176 636 615 0 508 213 0 636 0 81 311 17,0002000 851 256 159 679 674 282 530 345 721 614 0 72 311 25,4732001 979 197 170 729 716 670 588 103 636 669 0 81 327 24,7032002 1,107 363 146 724 722 817 669 228 896 623 1 96 310 25,7142003 1,161 295 133 816 816 339 706 226 801 593 1 104 299 23,3112004 978 163 137 665 663 575 567 115 596 272 0 95 211 21,9752005 769 228 147 558 558 958 498 47 855 263 0 97 218 21,0592006 529 218 141 502 501 1,108 373 87 801 306 0 83 250 22,3752007 267 234 135 254 254 1,052 246 59 847 299 0 79 545 19,3642008 418 236 142 322 322 1,006 322 11 824 293 1 86 449 19,9882009 383 239 143 319 319 1,160 305 16 860 295 1 87 451 21,9752010 439 239 136 356 356 1,104 333 6 718 296 1 77 452 21,841

56: Gerreidae; 57: Gerres spp.; 58: Siganidae; 59: Platycephalidae; 60: Soleidae; 61: Sphyraena barracuda; 62: Tetraodontidae; 63: Serranidae; 64: Penaeus semisulcatus; 65: Siganus spp.; 66: Rhinobatidae; 67: Callyspongia monilata; 68: Netuma thalassina; 69: Others

22

Egypt - Tesfamichael and Mehanna 23

reConstruCting red sea fisheries of egypt: heavy investment and fisheries1

Dawit Tesfamichaela,b and Sahar Fahmy Mehannac

a Sea Around Us, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada

b Department of Marine Sciences, University of Asmara, Asmara, Eritrea.c National Institute of Oceanography and Fisheries, Suez, Egyptd.tesfamichael @fisheries.ubc.ca; sahar_mehanna @yahoo.com

abstraCt

The catch of Egyptian fisheries in its Red Sea Exclusive Economic Zone (EEZ) was reconstructed from 1950 to 2010. Five fisheries sectors were identified and their catch reconstructed by taxonomic group. Published papers, gray literature, reports, databases and on-site observations were used as sources. Where data gaps were identified, they were accommodated with assumptions based on the best available knowledge, which are clearly stated and can be substituted by different ones given better information. The result showed that purse seine is the dominant fishery, followed by trawl, subsistence, artisanal and recreational fisheries. The total catch of Egypt in its Red Sea EEZ was around 6,000 t·year-1 in the early 1950s, which rapidly increased in 1960 and remained at a high level except for a sharp decline in 1973 due to the Israel-Arab war. The peak catch of about 50,000 t was obtained in 1993; catches then declined to about 25,000 t·year-1 by the end of 2000s. A total of 42 taxonomic groups were identified in the catches, in addition to many which could not be individually identified and categorized as ‘others’. Jacks (mainly horse mackerels), herring and scads were dominant and jointly accounted for 34% of the total catch. The reconstructed total catch was compared with data Egypt submitted to the Food and Agriculture Organization (FAO) and clear differences were observed. While, overall, the reconstructed total catch is 1.1 times what Egypt submitted to FAO, this relatively close match masks a much stronger dominance of the reconstructed over the official catches from 1950 to the mid-1990s, followed by a period of high official catches, which includes fish caught outside Egypt’s Red Sea EEZ.

introduCtion

Catch data are fundamental information to understand any fishery system (Watson and Pauly 2001). When coupled with information on effort, they can be used for basic and informative analysis to understand the fishery in question. However, these data are not usually readily available. Acquiring and analyzing a long time series of catch and effort data helps to understand the evolution of the fishery and predict the possible consequences of any plans. Historic reconstruction of catch data includes compiling data from different sources, cleaning, and standardizing them for presentation in usable form. Assumptions are usually made in the process. They should be presented openly for criticism and further refinement. The strongest criticism to such work has been that its results are unreliable, therefore should not be undertaken. In our opinion, this is not in any way helping to move forward in understanding fishery systems for proper assessment and conservation of livelihoods and ecosystems. Progress in the development of new approaches in fisheries is necessary to tackle pressing issues. Equally important are the basic data on catch and effort, which are absent or incomplete in many jurisdictions – both in developing and developed countries (Tesfamichael 2012). If the ultimate objective of fisheries science is to be effective in the management of fisheries, it has to look at historical time series catch, and the socio-economic and political mechanisms that drove changes in the system. Building a management system without such foundation is most likely to fail. Thus, comprehensive catch reconstructions (Zeller et al. 2007), i.e., not only tabulating numbers and drawing graphs, but also understanding the mechanisms behind them, are important and critical steps to understand fisheries systems.1 Cite as: Tesfamichael, D. and Ekawad, A.N. (2012) Reconstructing Red Sea fisheries of Egypt: heavy investment and fisheries. pp. 23-50. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosysytem by countries (1950-2010). Fisheries Centre Research Reports 20(1). Fisheries Centre, University of British Columbia [ISSN 1198-6727].

Figure 1. The Egyptian Exclusive Economic Zone (EEZ) and shelf area to 200 m depth in the Red Sea.

24

Egypt has access both to the Red Sea and Mediterranean Sea; besides expansive inland waters supplying fish; the main ones include the Nile and its canals, coastal and delta lakes and man-made Lake Nasser. Aquaculture is important in Egypt and accounts for more than 65% of the total fish products. During the 1980s, marine fisheries constituted about 22% of total fish catch, while the lakes formed about 50%; the Nile yielded 11% and aquaculture production was about 17%. In the 1990s, the percentages were 20% for marine fisheries, 32.7% for lakes, 13.3% for the Nile and 34% for aquaculture (Mehanna 2007). Based on annual fishery statistics data for Egypt, in 2009, the contributions of the Red sea and Mediterranean Sea were 4.4 and 7% of the total fish catch, respectively, while lakes contributed 15.7% and the Nile 8%; the lion’s share – 65%–was from aquaculture (GAFRD 2012).

Egypt’s coast along the Red Sea extends from the border with Israel in the Gulf of Aqaba to Sudan in the south. In terms of fisheries, the Gulf of Suez is the most important part of the Egyptian Red Sea, and most of Egypt’s Red Sea catch originates from that area. The continental shelf of the Gulf of Suez covers 8,400 km2, which is about the same as the rest of the Egyptian shelf in the Red Sea (Sanders and Morgan 1989). Egypt is divided into 27 governorates, out of which 3 border the Red Sea: Suez, Red Sea and South Sinai. Fishing is done mainly from Suez and Red Sea proper, while South Sinai is known for its coastal tourism.

Egypt has one of the most developed fisheries in the Red Sea (Tesfamichael and Pitcher 2006). Egypt’s industrial fishery, which predominantly consists of trawling and purse seining, was the earliest to develop in the Red Sea. The industrial fishery is extensive and its vessels operate all over the Red Sea and outside the Red Sea, including in international waters as far as the eastern Atlantic (Feidi 1976). Because the number of industrial boats was growing too rapidly, the Egyptian government put a moratorium on the entry of new boats to the fishery (Mehanna and El-Gammal 2007). The main landing site in the Red Sea is Ataka, in the Gulf of Suez, while Hurgada and El-Tor are major landing sites as well. The other less important landing sites include Salakhana, Berenis, Quseir and Shalateen (Figure 1). Ataka has a detailed data recording system; for every vessel, boxes are weighed and species recorded for all types of fisheries, even the traditional fisheries. In Egypt, the management of fisheries lies under the jurisdiction of the General Authority for Fish Resources Development (GAFRD), which is mandated to collect landings data. A relatively good data recording system was initiated in 1979 by the “Project for the development of fisheries in areas of the Red Sea and Gulf of Aden”, but the quality of data from remote areas remains debatable. Another institute involved in fisheries is the National Institute of Oceanography and Fisheries (NIOF), whose task is mainly research.

The Egyptian fisheries can be divided into 4 major sectors: industrial (i.e., large-scale commercial, mainly purse seine and trawl gears), artisanal (i.e., small-scale commercial, also called ‘semi-industrial’), subsistence (labelled ‘traditional’ in Egypt) and recreational. The GAFRD database divides the Egyptian fisheries in to the first 3 categories, i.e., the recreational fishery does not appear in the database. Sometimes, the fishery records are divided geographically for administrative purposes. In this report, only the division by gear type is used, because it is an important criterion, which can be used in designing management tools. Purse seine and trawl are categorized here as industrial fisheries. Semi-industrial fishing (here referred to as artisanal) is done by motorized boats of smaller size than industrial vessels. The ‘traditional’ fishery, categorized here as subsistence fishery uses the least technologically advanced boats. Some of its practitioners have no boats, and fish from land. Both semi-industrial and traditional fisheries are mainly reef-associated fisheries.

The main fishing gears deployed by Egyptian fishers in the Red Sea are bottom trawl and purse seine (the industrial fishery), handline, longlines and gillnets (artisanal) and a variety of gears used by the traditional subsistence fishery. The industrial fisheries operate mainly in the Gulf of Suez and its adjacent areas, and Foul Bay, which borders Sudan. Semi-industrial fisheries are active around Ataka, Salakhana, Sakkala and El-Tor. Boats in Foul Bay, unlike the other areas, do not operate only one gear; the same boat can be involved in trawling, purse seining and handlining (Sanders et al. 1984b). The entire catch from the Red Sea is consumed within Egypt and none is exported. Egypt imports additional sea food from neighbouring and other countries.

Due to the lack of good and extensive data recording systems, the extent of Egyptian fisheries in the Red Sea and its effects are not well known. The objective of this research is, therefore, to reconstruct the Egyptian catch in the Red Sea by gear and its taxonomic composition from 1950 to 2010. First, each major fishery is introduced, followed by the catch reconstruction methods; finally, the results are presented and discussed.

Industrial fishery

Purse seine fishery

The purse seine fishery has been active in Egypt for a long time. The earliest operation began using sailing boats. The main operation, using motorized purse seiners, started in the Gulf of Suez in 1960 with five 150 hp vessels and in Hurgada in 1964 with four vessels. The number of purse seiners increased gradually, with the aim of identifying the level of fishing effort to generate the optimum catch (Rafail 1970, 1972). The vessels use lamps (gas or kerosene) to attract the fish; once the fish aggregate, they are entrapped in the purse seine and hauled to the deck of the vessel. The purse-seiners are operated at night using lighted dinghies. The operation starts in October and finishes at the end of May, and it ceases for about 10 days every month during the full moon. About 65% of the catch comes in the first three months, October to December (Sanders et al. 1984a). At the beginning of each season, the fishing trip takes two to five days because most fishing is undertaken relatively close to the landing site of Ataka at Suez city. Later in the season, fishing trips take more days as they have to venture further afield (Mehanna and El-Gammal 2007). The three distinct areas for purse seining along the Egyptian Red Sea coast are the Gulf of Suez, Hurgada area and Foul Bay (Rafail 1970).

Egypt - Tesfamichael and Mehanna 25

Usually, about 82 purse seiners operate in the Gulf of Suez and 30 outside the gulf, mainly in Foul Bay. The vessels’ lengths range between 12.5 and 30 m. They are powered by engines of 150 to 700 hp, with the majority in the 400-700 hp range. The net’s length is between 200 and 300 m and its depth ranged from 50 to 80 m. The nets are hauled manually. The crew number ranged between 25 and 40 persons, and has not changed from the past (Barrania and El Shennawi 1979; El-Gammal and Mehanna 2002).

Purse seiners target small pelagic schooling fishes, which are also caught by artisanal trammel and gillnets in Salakhana and El-Tor (starting the 1970s). In the past, only 10% of the catch was consumed in Suez City, the rest was shipped to Cairo (Barrania and El Shennawi 1979); now, the majority of catch is sold in the Suez fish markets. The catch is consumed mainly fresh and some part salted. There are events where salted fish are consumed, e.g., Sham Al-Naseem Feast or Spring Festival. This feast is an Egyptian national holiday marking the beginning of spring; Egyptians eat salted fish, lettuce, and onions on this day.

Trawl fishery

Egypt has one of the earliest industrialized trawl fisheries in the Red Sea, which started in 1921, and increased after the Second World War. Egyptian investment in the industrial fisheries is unparalleled in the Red Sea. Egyptian trawlers first targeted shrimp using otter trawlers, which were allowed to operate only from September to June, because the rest of the year is the spawning period for many fishes. The best catches of shrimp were obtained from October to mid-January. A small proportion of shrimp was caught by seiners in shallow waters (Al-Khol and El-Hawary 1970). The fishing grounds are generally divided into the Gulf of Suez, areas adjacent to the Gulf of Suez and Foul Bay. At the beginning of the season, the vessels operate in the northern part of the gulf and their trips take about 5 days. Later in the season, they move further south and the trips take longer. Trips from Foul Bay can be up 20 days, out of which 6 days are to travel to and from the fishing ground. The main base for this trawl fishery is Ataka, although Sakkala is also used when vessels operate outside the gulf. Note that none of the trawlers operate exclusively outside the gulf. The vessels that operate in Foul Bay, which represents about 10% of the three trawling grounds, are used for purse seining as well (El-Gammal and Mehanna 1999).

In the mid-2000s, the number of vessels operating in the Gulf of Suez was 78 vessels, while about 100 vessels operated outside the gulf and outside Egyptian waters. The vessel length varied between 20 and 30 m, and each was powered by a main engine of 200 to 1200 hp (mostly 400-600 hp). All vessels had mechanized winches, and some of them echo-sounders. The trawl net they employed was of the Mediterranean type, and its length ranged between 20 and 30 m with an average mesh size of 1.5 cm in the cod-end, and a sweep length between 200 and 250 m. The fishing trip was about 5 to 10 days and the number of crew varied from 10 to 15. The trawl fishery is seasonal, generally from October to May. The number of fishing days during the first three months of the fishing season constitutes 42% of the total effort (Mehanna and El-Gammal 2007).

Artisanal fishery

‘Artisanal fishery’ is not a term commonly used by the Egyptian authorities. What we categorized as ‘artisanal fishery’, based on its mode of operation, is called ‘semi-industrial fishery’ in Egypt. The artisanal fishery uses motorized boats locally called launches, whose number varied between 93 and 178 in the Gulf of Suez and about 415 outside, with lengths ranging between 10 to 15 m, and inboard engines of 50 to 200 hp. The fishing trips take about 10 days, and the crew ranges from 2 to 10. The fishers on these boats use several fishing gears such as long-line, hand-line, gillnet, trammel net and beach-seine (Mehanna 1999).

The crew of the artisanal frequent on fishing grounds within and adjacent to Gulf of Suez, and land their catch in Ataka and Salakhana (in Suez City), Sakkala in Hurgada and El-Tor in South Sinai. Their main targets are reef-associated fishes and they use seines and cast nets to catch bait. Part of their catch is stored in ice boxes with ice and transported to Cairo. The reef-associated catch from Foul Bay used to be done by purse seines landed in Berenis, Shalateen and Abo Ramad and transferred directly to Hurgada and Cairo (Chakraborty 1984a, 1984b). Now, the purse seiners are prohibited from catching reef-associated species.

Subsistence fishery

As in the case of the artisanal fishery, Egyptian authorities generally do not use the term ‘subsistence fishery’. The fishery referred to here as subsistence fishery is known as ‘traditional fishery’, and refers to small-scale fisheries mainly for their own consumption but a small portion may be sold in the local markets, and which have existed for longer time than any of the other fisheries. These fisheries include foot-fishers, sailing boats and a few motor boats, equipped mainly with outboard or small inboard engines. These fisheries operate in the near-shore waters along the Egyptian coast, including in South Sinai, which is known for its touristic attractions, but not for fishing. All the fisheries in Sinai are categorized as ‘traditional’ except in El-Tor (Chakraborty et al. 1983). The subsistence fishery targets mainly fishes in shallow waters and coral reef areas using handline, gillnet, trammel, seine nets and cast nets. In some areas, e.g., Quseir, large sail boats locally called ‘Katira’ are used to catch sardines, mullets and goatfish. The traditional fishers may occasionally use trucks and camels to transport food and fishing equipment from place to place (Chakraborty 1984a, 1984b).

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Recreational fishery

Some form of recreational fishing has been practiced in Egypt for a very long time, starting from the time of the Pharaohs (Pitcher and Hollingworth 2002). The more contemporary recreational fishery started with the growth of tourism in the Egyptian Red Sea, i.e., after the 1967 Arab-Israeli war (Hawkins and Roberts 1994). Both tourists and the local population are involved in recreational fishing. They usually use line fishing (simple hook and line, longline and trolling) and more rarely nets (mainly to catch bait). The catch is usually consumed by the fishers, some given to friends and very rarely, in the case of a big catch, a small portion may be sold in the market. The number of boats involved in the recreational fishery has grown very fast in the last few years (FAO 2004, 2010).

methods

As this research deals with historic statistics on the fisheries of Egypt, the methodology required the compilation of data from different sources, cleaning, and standardizing them for presentation in usable form (Tesfamichael and Pauly 2011). Whenever there were data gaps, they were filled using assumptions, which are stated openly for criticism and further refinement. An extensive search was made for fishery catch data of Egypt in the Red Sea in journal articles, gray literature, reports and databases. In addition, the knowledge of people (fishers and administrators) familiar with the statistical system was sought to fill in gaps and interpret data and the results of our analysis. We found that there are many published reports, mainly in national journals, on the Egyptian fisheries. After a close scrutiny of the literature, the main sources of Egyptian fisheries catch data can be categorized into three sources. The earlier ones were published (mainly in the ‘Bulletin of the Institute of Oceanography and Fisheries’) from the 1950s until the 1970s by local researchers in order to identify the potential of the resource using traditional stock assessment tools such as surplus-production models. The next category consists of reports from an FAO project titled ‘Development of Fisheries in Areas of the Red Sea and Gulf of Aden’, which ran from the late 1970s to the mid-1980s. The reports were very detailed and gave very good insight into the fisheries of Egypt by gear type, taxon and place. They were written mainly by foreign experts, sometimes with local co-authors. This phase is data rich and several similar reports, sometimes with overlapping contents, were written by different authors, mostly technical consultants to the project. The third category of data source is the database of GAFRD (2012), which presents data from 1979 to the present. Generally, the GAFRD database is informative, but it has gaps. The catch reconstruction was done separately for each major sector of the Egyptian fisheries in the Red Sea.

Industrial fisheries

Purse seine fishery

The earliest report for the purse seine fishery in the Egyptian Red Sea available to us was from Rafail (1970). Landings were given for Gulf of Suez from 1960 to 1965 for sardinella, Sardinella gibbosa, reported as S. jussieu, but also as goldstripe sardine in some reports (Chakraborty 1984a). The geographic distribution for S. gibbosa in Fishbase (Froese and Pauly 2012) included the Red Sea, but this was not the case for S. jussieu. The report gave the proportion of the taxon from the total purse seine fishery landings of the Gulf of Suez, which were used to calculate the total catch. For Hurgada, landings of sardinella, which accounted for 25% of the total purse seine catch in Hurgada, were given for two seasons (September – May) 1964/1965 and 1965/1966. First, the catches of Hurgada were converted to calendar year assuming that 63% was caught from September to December and the rest from January to May; this ratio is an average calculated based on reports from Sanders et al. (1984a) and data from GAFRD (GAFRD 2012). Catches were given for the Gulf of Suez and Hurgada separately, but not for Foul Bay, because the boats that fished in Foul Bay were from the Gulf of Suez and Hurgada, and it is probable that their catch was included in the reports from those two areas (Rafail 1970). For 1966, it was possible to calculate total catch only for Hurgada, as there was not any data given for the Gulf of Suez. Thus the total was calculated using the ratio of Hurgada to the Red Sea from 1965 and the total of Hurgada for 1966.

Prior to the industrial purse seiners, non-motorized sailing boats had already been purse seining, although at a smaller scale. Their catch was not recorded (based on interviews with fishers and administrators), thus it was estimated to be about 5% of the total purse seine catch. Thus, 5% of the purse seine catch for 1960, which was 133 t∙year-1 annually, was assumed from 1950 to 1959. In addition, trawlers were also involved in purse seining starting 1960 (Sanders et al. 1984b) and their catch is assumed to be 1% of the total purse seine catch. Accordingly, 6% (5% from non-motorized boats and 1% from trawlers) was added to the catch from 1960 to 2010. There were no data from 1967 to 1969, and the catch was interpolated between 1966 and 1970.

From 1970 to 1978, the annual purse seine catches were available (Chakraborty 1984a) and from 1979 to 1982 (Sanders et al. 1984a). Unlike other reports, these catches were for the whole Red Sea, not only for the Gulf of Suez. Thus, these values were used as they were, but 6% was added to account for the unreported catch by sailing boats and others.

From 1980 to 2010, data were available from GAFRD (2012), but it was only for the Gulf of Suez. The data from 1979 to 1989 were presented by fishing season only, i.e., September to May. These data were first converted to calendar year using the same procedure as described above. From 1990 to 2004, there were two data sets: one presented by season, which was converted to calendar year, and another by calendar year. Comparison of the two data sets resulted in correlation coefficient of r = 0.91, which showed our conversion process to be reasonable. From 2005 to 2010, the only data available were presented by calendar year. The converted data were used from 1983 to 1989 and the other set from 1990 to 2010.

Egypt - Tesfamichael and Mehanna 27

Once the annual total catches were calculated for the Gulf of Suez, they were scaled up to the whole Red Sea based on Sanders et al. (1984a), who reported that for 1980 and 1981 the Gulf of Suez accounted for 75% of the total Egyptian Red Sea purse seine catch. The total annual catch calculated from 1979 to 2010 were used except from 1980 to 1982, where the more detailed data from Sanders et al. (1984a) were used instead those from GAFRD (2012). To all the totals, 6% unreported catch was added (Figure 2).

The earliest catch composition data available for Egyptian purse seine fishery was the percentages of only S. gibbosa, which accounted for up to 95% of the total of the Gulf of Suez purse seine catch starting in 1960 (Rafail 1970). The difference between 100 and the percentages for S. gibbosa were allocated to ‘others’. Since, from 1960 to 1964, purse seining occurred only in the Gulf of Suez, those percentages were used for the whole Red Sea. The ratios of 1960 were used from 1950 to 1959. From 1964 to 1966, catch composition ratios were given for both the Gulf of Suez and Hurgada landings (Rafail 1970). For 1965, the unidentified catch of ‘others’ was too high (72%) and for 1966 the data were incomplete; thus, for these two years, the ratios of 1964 were used. For 1964, the group ‘others’ had a value of 33% and it was reduced by dividing it to the taxa not represented for 1964, but were represented in a more detailed catch composition for 1980 (Sanders et al. 1984a). Because of the uncertainty in identifying the sardinellas into species level, we presented them here as Sardinella spp.

Better catch composition data were available from 1980 to 1982 (Sanders et al. 1984a) and 1983 (Chakraborty 1984a). In both sources, horse mackerels and scads were reported as one group. However, the two belong to two different genera and are reported separately in the FAO database. Hence the ratio given for the two together was divided equally between the two. In addition, there was a group called ‘miscellaneous’ and another one called ‘others’, which were combined. The ratios of 1980 were used from 1967 to 1979. From 1984 to 2010, GAFRD (2012) data presented the catch by taxonomic components. The data were first converted to calendar year. For most of the years, a large proportion was categorized in the group ‘others’; this was disaggregated using the average catch composition ratios from the years where the group ‘others’ was less than 10% (1992 – 1994, 2000 and 2001). Similar to 1980 – 1983, the group ‘horse mackerel and scads’ was divided into two equal separate groups (Table 1).

Trawl fishery

The earliest Egyptian trawl fishery record available was the catch of shrimp from 1921 (Al-Khol and El-Hawary 1970) from the Gulf of Suez. Although the catch was given only for shrimp, we believe that at least some of the fishes were also retained, as implied in other reports on trawling (Latif and Shenouda 1972), which, however, presented data only for 1963. In addition, there are reports of demersal fish caught by trawling in Egyptian Red Sea data submitted to FAO. Thus, the total trawl catch from 1950 to 1961 was calculated based on reported shrimp catch. First, a continuous series of shrimp catches was established because the data from Al-Khol and El-Hawary (1970) were intermittent. Then the gaps in the shrimp catch from 1945 to 1955 were filled by interpolation, and scaled up to total retained catch for the Gulf of Suez, based on the ratio of shrimp from total catch, which was reported to be 10% (Chakraborty 1984a). The Gulf of Suez was later scaled up to the whole Red Sea based on Sanders et al. (1984b), who reported that the Gulf of Suez accounted for 90% of the total Egyptian Red Sea trawl catch. We used this procedure to reconstruct the catch from 1950 to 1961.

The next data set available was from 1963 to 1966 (Latif and Shenouda 1972). The value for 1963, however, was not used as it did not correspond to the other figures given in the same report. First, the Gulf of Suez catch was scaled up to the whole Red Sea, based on Sanders et al. (1984b), who reported that it accounted for 90% of the Red Sea total. The totals for 1962 and 1963 were interpolated using data from 1961 and 1964.

Table 1. Sources used to calculate the catch composition (in tonnes) of Egyptian purse seine fishery in the Red Sea.Year Horse

mackerelScads Round

herringSardinella Slimy

mackerelIndian

mackerelBarracudas Anchovies Others Source

1950–60 0.0 0.0 0.0 92.0 0 0.0 0.0 0.0 8.0 Rafail (1970)1961 0.0 0.0 0.0 81.0 0 0.0 0.0 0.0 19.0 Rafail (1970)1962 0.0 0.0 0.0 91.0 0 0.0 0.0 0.0 9.0 Rafail (1970)1963 0.0 0.0 0.0 95.0 0 0.0 0.0 0.0 5.0 Rafail (1970)1964 8.4 8.4 11.4 67.1 0 2.7 0.1 0.3 1.5 Rafail (1970)1967- 80 20.9 20.9 28.4 18.2 0 6.7 0.3 0.7 3.8 Sanders et al. (1984a)1981 25.2 25.2 15.0 26.3 0 6.3 0.1 0.1 1.7 Sanders et al. (1984a)1982 25.9 25.9 16.4 21.2 0 5.9 0.1 0.2 4.4 Sanders et al. (1984a)1983 22.9 22.9 22.2 22.0 0 6.5 0.2 0.4 2.9 Chakraborty (1984a)1984–2010 25.2 25.2 27.1 4.6 12 1.7 0.0 0.0 4.1 GAFRD (2012)

Figure 2. Sources and values used to reconstruct the Egyptian purse seine fishery in the Red Sea from 1950 to 2010.

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Chakraborty (1984a) presented the total catch of trawl fishery for the whole Red Sea from 1970 to 1983 with some years missing. However, only the data from 1970 to 1978 were used, as the years after that were not complete. Besides, there was a continuous data set from 1979 to 2010 from GAFRD (2012). In addition to Chakraborty (1984a), there were more sources for the years from 1980 to 1983, thanks to the FAO funded project, which employed many experts, e.g., Sanders et al. (1984b), who even presented monthly catches. However, all those data sets were very similar and because of its completeness and continuity, the data from GAFRD was used. It consisted of two sets: one only for the Gulf of Suez from 1979/80 to 2007/08 (except 2005/2006), by fishing season (September to May). The catch data therein were converted to calendar year using similar procedures we employed for the purse seine fishery (the value for 2005/06 was calculated as an average of 2004/05 and 2006/07). The annual total of the Gulf of Suez was then scaled up to the whole Red Sea, based on data from Sanders et al. (1984b), who reported that the Gulf of Suez accounted for 90% of the total Egyptian trawl fishery catch in the Red Sea. The second data set were from 1990 to 2010, by calendar year. Comparison was carried out between the two datasets over the overlapping years, 1990 – 2008, and resulted in a correlation coefficient of r = 0.83, which indicated that our conversion process of the seasonal data to calendar year is reasonable. From 1979 to 1989, the converted data were used and from 1990 to 2010, data given by calendar year were used (Figure 3). The main unreported portion of the trawl fishery is discarded catch. Since this was a substantial amount, it is treated separately.

A good proportion of trawlers’ catch is thrown back as discard. The only Egyptian study we found on this topic was El-Ganainy et al. (2005), who found, based on trawl surveys in 2003, that discards amounted to 56.1% of the total catch. Given that the trawl fishery in 1950 was mainly for shrimp, which has a discard amount of up to 90% in the Red Sea (Sanders and Morgan 1989; Tesfamichael and Pitcher 2007), a conservative estimate of discard of 80% of total catch was assumed for 1950. Using these data points, the discard proportion was interpolated from 1950 to 2010, to mimic the behaviour of the fishers who tend to retain more and more of the less valued fishes as the premium species, usually high-trophic level ones, start to decrease or disappear altogether in their catch (Pauly et al. 1998). Once the discard proportions were established, the discard amount was calculated based on the reconstructed retained catch.

The composition of retained catch was calculated based on data from Sanders et al. (1984b) for 1980 – 1982, Chakraborty (1984a) for 1983, and GAFRD (2012) for 1984 – 2010. The categories ‘miscellaneous’ and ‘pony fish’ (i.e., Leiognathidae), which were less than 1% each, were added to the category ‘others’ from 1980 to 1983. From 1950 to 1979, the average proportions of 1980 – 1983 were used. All the sources put ‘horse mackerel and scads’ together. However, given that the two belong to different genera and are reported separately in the FAO database, the group was divided into two equal portions (Table 2).

The catch composition of the discarded catch was calculated using data from El-Ganainy et al. (2005), where the ratio of fish species and crustaceans were given separately. However, the proportion of each category to total discards was not given. It is assumed, by comparison with other Red Sea trawl fisheries, that fish discards contributed 75% and crustaceans 25% (Table 3). For a few taxa, the scientific names presented were not the valid names. For those taxa, valid scientific names were obtained from FishBase (www.fishbase.org) and SeaLifeBase (www.sealifebase.org).

Artisanal fishery

The earliest record available for the artisanal (semi-industrial reef) fishery was for the 1979/80 season, lasting from October 1979 to September 1980, and for the next three seasons, i.e., until September 1982, for the whole Red Sea (Chakraborty 1984a). GAFRD (2012) also had data from 1979/80 to 2004/05 pertaining, however, only to the Gulf of Suez. The data from Chakraborty (1984a) were used because they were based on extensive frame surveys, detailed and included catches from areas that are not included in the GAFRD data set. For the rest of the years, the GAFRD database was used. First, the GAFRD data, 1982/83 – 2004/05, were scaled up to the whole Red Sea by comparing the data for the overlapping years (1979/80 – 1981/82) between Chakraborty (1984a) and GAFRD (2012), which resulted in the Red Sea total being 2.29 times that of the Gulf of Suez catch. Then the data were adjusted to calendar year using data from Sanders et al. (1984c): October to December (22%) and January to September (78%). From 1990 to 2010, the GAFRD database, which presented the Gulf of Suez catch by calendar year, was used. Comparison of the overlapping years, 1990 – 2005, between the seasonal data converted to calendar year and the data already presented by calendar resulted in correlation coefficient of r = 0.98, which indicates that the conversion process performed well.

Based on our observation of the operation of this fishery, we believe that part of the catch of this fishery is not fully reported. Some of the catch is sold in informal markets where data recording does not happen. A conservative estimate of 10% was added to the totals to account for the unreported catch.

Figure 3. Sources and values used to reconstruct the retained part of the Egyptian trawl fishery in the Red Sea from 1950 to 2010.

Egypt - Tesfamichael and Mehanna 29

No records were available for this fishery from 1950 to 1979. Approximate catches were derived for this period by assuming the level of catch in 1950 to be the same as 2010, where the catch declined to its lowest level, and interpolating between 1950 and 1979 (Figure 4).

The catch composition from 1980 to 1983 was calculated using data from Sanders et al. (1984c) and for 1984 from (Chakraborty 1984a). The only change made to the ratios given in those reports was that 10% of the category ‘others’ from the Gulf of Suez catch from 1980 to 1983 was deducted and allocated to Spanish mackerel, which appeared in other reports. Data from GAFRD (2012) gives the catch composition from 1979 to 2005, in which Spanish mackerel was presented separately and the average for 1980 to 1983 was 10% of the ‘others’. For 1984, 10% of ‘others’ from the overall Red Sea catch composition was assigned to Spanish mackerel. The GAFRD database catch composition from 1984 to 2005 is highly aggregated under the category ‘others’. Thus the catch composition of GAFRD is ignored and the average of 1980 to 1983 is used for 1984 to 2010 and 1950 – 1979 (Table 4).

Table 2. Sources used to calculate the composition of Egyptian trawl retained catch (in tonnes) in the Red Sea.Year Lizard fish Striped snappers Threadfin bream Horse mackerel Scads Red mullets Shrimps Cuttlefish Others Source1950–79 46 12 8 2 2 4 10 3 14 a*1980 41 13 9 2 2 3 11 2 17 b1981 48 10 7 2 2 3 10 3 13 b1982 50 13 8 2 2 6 7 3 10 b1983 45 11 8 2 2 3 11 3 15 c1984 26 14 8 4 4 3 20 5 15 d1985 31 15 8 3 3 3 19 4 14 d1986 51 10 5 2 2 3 11 3 12 d1987 39 11 4 3 3 5 15 4 17 d1988 22 18 3 3 3 7 16 2 26 d1989 15 28 3 2 2 7 16 3 25 d1990 11 29 2 2 2 8 22 4 19 d1991 22 20 3 3 3 9 22 4 14 d1992 24 19 3 1 1 11 15 3 22 d1993 15 23 3 2 2 11 18 5 21 d1994 15 20 4 4 4 11 19 8 14 d1995 27 13 6 2 2 11 13 4 22 d1996 26 11 5 2 2 9 13 4 28 d1997 27 11 10 4 4 8 13 3 19 d1998 29 13 14 4 4 8 11 3 14 d1999 29 13 14 2 2 9 10 3 17 d2000 27 14 10 3 3 10 12 4 17 d2001 28 14 10 4 4 10 9 4 17 d2002 32 12 11 3 3 10 7 5 18 d2003 28 14 11 3 3 10 7 5 20 d2004 31 15 11 1 1 11 15 7 8 d2005 32 13 11 2 2 10 15 7 9 d2006 28 9 10 5 5 10 8 5 21 d2007 28 8 10 5 5 8 7 4 26 d2008 28 9 10 5 5 7 8 4 26 d2009 28 9 10 5 5 7 8 4 26 d2010 28 9 10 5 5 7 8 4 26 d*a = Average of 1980 – 1983; b = Sanders et al. (1984b); c = Chakraborty (1984a); d = GAFRD (2012)

Table 3. Percentages used to calculate the composition of Egyptian trawl discarded catch in the Red Sea.

Taxa Common name %Leiognathus berbis Berber ponyfish 26Champsodon capensis Gaper 19Leiognathus elongatusa Slender ponyfish 11Pseudorhombus arsius Large tooth flounder 8Charybdis helleri Spiny hands crab 5Laganum depressumb (Sand dollar) 3Clypeaster reticulatus (Sand dollar) 3Callyspongia monilata Finger sponged 2Cliona vastificac Red sponged 1Others — 23a,b,c Valid names for taxonomic names given in the paper: a Equulites elongatus, bJacksonaster depressum, c Pione vastifica.d Sponges are not considered by the Sea Around Us. Therefore, for the purposes of the database, these entries are not considered.

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Subsistence fishery

Although the presence of a subsistence (traditional) fishery is acknowledged by many authors, we found only one estimate of its catch, for 1983, from a frame survey (Chakraborty 1984a). In the absence of other data, population size, based on the United Nations, Population Division (esa.un.org/unpd/wpp/Excel-Data/population.htm) was used as a proxy to estimate the subsistence fishery catch. This is a reasonable assumption, because catch of traditional fisheries is usually consumed locally, hence related to population size. Because the catches of the traditional fishery are almost exclusively consumed by local communities, this fishery is categorized as subsistence fishery in our reconstruction. First, the catch for 1983 was divided by total population. This per capita ratio was multiplied by 1.5 for 1950, assuming per capita rate of subsistence catch was 50% higher in 1950 when the resource was more abundant and the population size small. For 2010, the 1983 ratio was halved (50% less), reflecting the overall decline in fish abundance and increase in population size. Once these three points were established, the ratios for the rest of the years were interpolated. Then the total catch was calculated by multiplying these ratios by the population size. This is a very conservative estimate; as most of the estimates are less than the only report available, for 1983 (Figure 5). Traditional fishers are known to use a large proportion of their catch to feed their families and give to relatives and friends. Based on interviews in the Red Sea, this can be up to 50% of their total catch. It was also observed during the interviews that fishers used to give bigger proportion of their catch in the past, when there was less marketing of their catch, but later the ratio they give freely decreased. In order to estimate the proportion of the unreported catch of the traditional fishery, we used a conservative 30% for 1950 and 10% for 2010. The ratios were interpolated between the two years.

The catch composition of the subsistence catch was calculated using the ratios given in Chakraborty (1984a) with minor modification (Table 5). In the report, sardines and anchovies were reported as one group. However, they are reported separately in the FAO database. Thus, we presented them separately, with each having a composition of 4.4%.

Recreational fishery

The presence of a recreational fishery in Egypt is mentioned in many reports, but catch data are very scarce. Indeed, the only quantitative information available for the recreational fishery of Egypt in the Red Sea was that there were 3,013 recreational fishers in 2003 (FAO 2004) and 5,079 in 2008 (FAO 2010). The term ‘recreational fishers’ in Egypt refers to full-time operators of boats taking tourists (local and foreign) on day trips of recreational fishing. The 2008 report also gives the number of boats involved in recreational fishing activity. In order to estimate the total catch of the recreational fishery, the numbers of operators from 2003 and 2008 were used. First, the proportion of the recreational fishers from total population (participation rate) was calculated for 2003 and 2008, which were 0.0043% and 0.0067%, respectively. The recreational fishery was assumed to start in 1968,

Table 4. Sources used to calculate the composition of Egyptian artisanal fishery catch (in tonnes) in the Red Sea.Year Groupers Spangled

emperorYellow tailed

emperorJacks Little

tunaLong spine

breamParrot

fishSharks Spanish

mackerelOthers Source

1950–79 28 23 7 4 2 2 4 1 2 27 a*1980 27 21 9 4 1 2 4 1 2 29 b1981 31 21 6 5 2 2 4 1 2 27 b1982 25 28 6 3 2 1 4 2 1 27 b1983 29 21 8 4 2 2 4 1 3 26 c1984–2010 28 23 7 4 2 2 4 1 2 27 a*a =average of 1980 – 1983; b = Sanders et al. (1984c); c = Chackraborty (1984a)

Figure 5. Estimated catch of the Egyptian subsistence fishery in the Red Sea from 1950 to 2010 (solid line), and the growth of the Egyptian population (dotted line), as used in the estimation of this catch (see text).

Figure 4. Sources and values used to reconstruct the Egyptian artisanal fishery in the Red Sea from 1950 to 2010.

Egypt - Tesfamichael and Mehanna 31

after Egypt’s war with Israel in 1967. The tourism industry in the Red Sea started after the war (Hawkins and Roberts 1994) and tourism has major impacts on the recreational fishery. The participation rate for 1967, therefore, was assumed to be zero. The rates were interpolated between 1967 and 2003 and again from 2003 to 2008. The slope of change from 2007 to 2008 was used to calculate the participation rate for 2009 and 2010.

Once the participation rates were estimated from 1967 to 2010, the total number of participants was calculated by multiplying the participation rates by the population of Egypt, obtained from the United Nations, Population Division (esa.un.org/unpd/wpp/Excel-Data/population.htm; see also Figure 5). In addition to the number of participants, data on number of days per year and the catch rate per day are needed for the estimation of total catch. The number of days per year we assumed a conservative 250 days·year-1 based on the report from FAO (2010), stating that the recreational boats sail on more than 280 days per year. For the catch rate per operator, we assumed 2 kg·day-1 for 1968 and 1 kg·day-1 for 2010. This is again a conservative catch rate assumption. The catch rate was interpolated between 1968 and 2010, to mimic the change in catch rate as the intensity of fishing increases and abundance decreases. The total catch was then calculated by multiplying the number of operators by the number of days per year they fish multiplied by the catch rate (Figure 6). Since the estimated number of recreational operators was for the whole of Egypt’s EEZ, i.e., both the Mediterranean and the Red Sea, the Red Sea part was calculated by assuming that 75% of the recreational fishery occurs in the Red Sea (Figure 6), based on the report that most of the recreational fishing takes place in the Red Sea (FAO 2010).

The catch composition of the Egyptian recreational fishery in the Red Sea is estimated based on the field observation by the second author. The dominant taxa in catch are groupers (Serranidae), pelagic jacks and mackerels (Carangidae) and snappers (Lutjanidae). Emperors (Lethrinidae) and large sized threadfin breams (Nemipteridae) are also common in the catch, although not as dominant as the three previously listed ones. We assumed a contribution of 20% each for the three dominant taxa, 15% each for emperors and threadfin breams and 10% was allocated to the ‘others’.

Comparing reconstructed catch with FAO data for Egypt in the Red Sea

The catch data we reconstructed from different sources was compared with the Egyptian Red Sea catch as reported in the FAO database (www.fao.org/fishery/statistics/software/fishstat/en). Although Egypt has access both to the Red Sea and Mediterranean Sea, they belong to two different FAO statistical areas; hence, the FAO data for Egypt is separate for the two seas. To compare our data with Egypt’s FAO Red Sea data, we first checked for taxa not included in the different sectors of the reconstructed catch, but reported to FAO, and vice versa. Some groups: ‘silversides (sand smelts) nei’, ‘largehead hairtail’ and ‘flatfishes nei’ were reported by Egypt to FAO for a few years, but not represented in the reconstructed catch. We assigned their low catch to the group ‘others’. Other taxa, found in the FAO data but not the reconstruction, were allocated to the appropriate sector in the reconstruction. Their amount in the reconstructed catch was taken to be the same proportion they had in the total FAO catch. The amounts were later deducted from the ‘others’ of the sector to which they were allocated. For each sector, for the years in which the group ‘others’ was higher than 10%, it was reduced to 10% and the rest distributed to the taxa already identified according to their proportion in each sector. These procedures changed the original taxonomic composition of the catches described in each sector in the above. Hence, the final catch composition is different from the taxonomic composition tables given for each sector in the methods. Those tables are procedural tables and not final ones. Each taxon in the reconstructed catch was compared with its corresponding value in the FAO data. The part of the reconstructed catch that is accounted in the FAO data is referred as ‘reported catch’ in our result. The difference was presented either as unreported or over-reported catch depending whether the reconstructed value was higher or lower than the FAO value.

Table 5. Catch composition of Egyptian subsistence fishery in the Red Sea.

Taxa %Mullets 20.0Carangids 17.0Breams 9.4Stripped snapper 8.0Shrimps 7.0Sardines 4.4Anchovy 4.4Rabbit fish 3.5Barracuda 1.0Cuttle fish 0.3Queenfishes 0.2Croakers 0.1Other 24.7

Figure 6. Reconstructed total catch of the Egyptian recreational fishery in the Red Sea from 1950 to 2010 and the number of recreational fishing operators used to estimate the catch.

32

Egyptian fishery outside its waters in the Red Sea

Egyptian fishery is the most developed in the Red Sea and the earliest to expand and use advanced technology. The concentration of fishing fleets is so high that the government banned new entry to the fishery (Mehanna and El-Gammal 2007). The Egyptian fishing fleet has been known to roam the whole Red Sea, i.e., outside Egypt’s exclusive economic zone (EEZ) with or without formal agreements with the other Red Sea bordering countries. There are even reports that Egyptian vessels fishing outside the Red Sea, besides Egyptian waters in the Mediterranean, as far as the eastern Atlantic (Feidi 1976). The Egyptian fleets that venture out of Egyptian waters are mainly large trawlers and purse seiners. Based on the catch reconstruction of Sudan (Tesfamichael and Elawad 2012), Eritrea (Tesfamichael and Mohamud 2012) and Yemen (Tesfamichael et al. 2012), we were able to estimate the total catch of Egyptian vessels in those countries (Figure 7). It is worth noting that the values in Figure (7) represent what Egyptian vessels catch under formal agreement with the respective countries. It does not include the illegal fishing activities carried out by Egyptian vessels, which are not uncommon occurrences. Several Egyptian vessels and their crew have been arrested in Eritrea and interviews with fishers in Sudan revealed their grievance of their resources being exploited illegally by Egyptian vessels and how that had affected their catch.

results and disCussion

The reconstructed total Egyptian Red Sea catch deemed taken within the Egyptian EEZ or EEZ-equivalent waters (i.e., prior to the formal declaration of the EEZ) is shown in Figure (8) and appendix Table (A1), together with the catch Egypt reported to FAO from statistical area 51 to which the Red Sea belong. The reconstructed and FAO catches were more or less the same at the beginning until around 1960. Then two distinct patterns appeared with clear demarcation in 1993. The earlier pattern, from the early 1960s to 1993, was one where the annual reconstructed catches for Egyptian waters were clearly higher than the FAO reported. From 1993 on, the opposite occurred, where the FAO reported catches were much higher than the reconstructed catch. Our explanation, given all the information we have, is that the catch was underreported from the early 1960s to the early 1990s, but the later part included catches made outside Egypt’s own waters, which were not included in the reconstructed catch for Egypt in its EEZ. Egyptian boats, mainly industrial ones, have been expanding their operations to the other Red Sea countries mainly since the early 1990s and Egypt’s catch from those waters were presented in their respective country (Tesfamichael and Elawad 2012; Tesfamichael and Mohamud 2012; Tesfamichael et al. 2012), see Figure (7) in the above for what Egypt caught in Sudanese, Eritrean and Yemeni waters.

Here, we are primarily interested in getting a better estimate of what is caught in the ecosystem, i.e., where the catch comes from, and secondly who (or which country) is catching it. Thus, what Egypt caught in Sudanese, Eritrean and Yemen is reported in the respective countries reconstruction reports with clear indication that it was caught by Egyptian vessels. Nevertheless, adding the values of Egyptian catch outside its EEZ (Figure 7) to the reconstruction will not fill the gap between the reconstructed catch and FAO data of Figure (8). Since the gap is big, it is imperative to explain the difference. In order to do that, we dug deeper into Egyptian catch by area, which we were able to obtain for few years from the Egyptian authority (GAFRD 2012). The overall total Egyptian catches in the Red Sea match what is reported in the FAO data. However, when the data were dissected by region a different picture appears. The areas reported include the ‘Gulf of Suez’ (or catch landed in the ports in Suez, the main landing sites), ‘Aqaba’, and what is vaguely labeled as ‘south’ or ‘southern Red Sea’, and ‘outside’. These terms sometimes refer to the catch caught ‘outside Gulf of Suez’ or fish caught in the southern Red Sea including areas outside Egypt’s EEZ. For comparison, those catches were taken out from what Egypt reports to FAO for area 51, and we obtained

Figure 8. Reconstructed catch of the Egyptian fishery in the Egyptian Red Sea EEZ by sector and the data Egypt submitted to FAO from 1950 to 2010 for FAO area 51. Open circles indicate Egyptian catch reported to FAO without what is possibly caught outside its EEZ put for comparison purpose.

Figure 7. Total catches of the Egyptian fisheries in the Red Sea waters of Sudan, Eritrea and Yemen from 1950 to 2010.

Egypt - Tesfamichael and Mehanna 33

estimates closer to our reconstructed catch, the open circles in Figure (8). On the other hand, FAO’s database shows what a country catches in FAO described statistical areas; hence what Egypt caught outside its waters in the Red Sea would be rightly reported under Egypt. As catch data can be used in managing ecosystems, we believe reporting the catch by EEZs gives a better resolution.

The sudden sharp dip in the reconstructed total catch in 1973 was the consequence of the 1973 Arab-Israel war, which destabilized the region and destroyed infrastructure. The effect of the previous 1967 Arab-Israel 6 day war is also shown by the smaller dip in the late 1960s. The first rapid increase in the early 1960s was mainly due to the trawl fishery, which was rapidly expanding at the time. The reconstructed total catch remained stable, albeit with minor fluctuations until it declined in 1993, which may be due to Egyptian vessels sailing outside their EEZ for a better return in their operation than staying in the heavily-fished Egyptian EEZ. Logically, it makes sense that they would put more effort (fuel and time) to go further south, decreasing the total catch from Egyptian EEZ, but then they will get much higher catch (or catch rate) putting the total catch, i.e., what is reported to FAO much higher. Otherwise, their venturing outside the Egyptian EEZ would not be economically rewarding. It is also important to note that Egypt has a very high concentration of fishing vessels, and the fishery authority banned new entry, thus even existing vessels were forced to explore new grounds as the catches from the traditional fishing grounds began to decline.

Overall, from 1950 to 2010, purse seining contributed the largest share to the total catch (42%), followed by trawling (27% discarded and 13% retained catches). The trawl fishery was dominant in the early years, i.e., the 1960s until the mid-1970s, after which it was more or less at par with purse seining, which took over in recent years. The subsistence fishery was the third most important fishery by total catch (14%). The artisanal fishery and recreational fisheries had low contributions (3% and 1%, respectively). The subsistence fishery kept more or less the same level throughout, which is the case in the other Red Sea countries as well (Tesfamichael and Elawad 2012; Tesfamichael and Mohamud 2012; Tesfamichael et al. 2012). The subsistence fishery is less affected by external factors, such as international market demand. They are conducted mainly for subsistence and they operate as long as there are people, mainly their families and communities, to consume their catches.

The reconstructed total catch in Egypt’s EEZ can be divided into the catch that can be found in the official report to FAO (reported catch), unreported landed catch and the discarded catch, which is also not reported to FAO. The unreported landed catch contributes 43% of total catch, while reported catch is 30% and discarded catch 27% (Figure 9, Table A2).

Looking at the fishery sectors separately, the industrial purse seine fishery had a continuous, although fluctuating, upward trend from its beginning until it peaked in 1993. After 1993, it declined, but again with fluctuations (Figure 10, Table A3). The trend of the purse seine fishery shaped the trend of the overall reconstructed catch for Egypt, especially in the later years because it was the fishery with the highest contribution. As far as the composition of the purse seine fishery is concerned, three taxa contributed more than 70% of the total catch. They were red-eye round herring (Etrumeus sadina, 26%), jacks (Carangidae, 23%) and scads (Decapterus spp., 23%).

The industrial trawl fishery expanded very quickly at the beginning of the 1960s after its exploratory phase throughout the 1950s; then there was a sudden decline during both the 1967 and 1973 Arab-Israel wars (Figure 11, Table A4). Since its recovery in 1974, the trawl fishery exhibited fluctuations with a slight declining trend. In the earlier period, the trawl fishery had the highest contribution to the total catch until it was taken over by purse seine. Although the main prized target of trawl fishery is shrimp, lizardfishes (Synodontidae) had the highest contribution by far (40%), followed by snappers (Lutjanidae; 14%), while shrimp was the third with 12% of the retained catch. The three taxa contributed more than 66% of the total landed catch from 1950 to 2010. The discarded trawl catch (Figure 12, Table A5) followed a similar pattern, except that the decline was stronger. This is because the percentage of discarded catch to the total catch was lower in the later years as more and more of the lower-grade fishes were retained in the catch when the most sought-after fishes started to decrease. Berber ponyfish (Leiognathus berbis) had the highest contribution to the discarded catch (26%).

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (1

0 t)3

0

25

50

Reported

Unreported

Discards

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (1

0 t)3

0

10

20

30

Etrumeus sadina

Carangidae

Decapterus spp.

Sardinella spp.

Scomber japonicus

Rastrelliger kanagurta Others

Figure 9. Reconstructed catch of the Egyptian fishery in the Egyptian Red Sea EEZ by component from 1950 to 2010. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.

Figure 10. Catch composition of the Egyptian purse seine fishery in the Red Sea from 1950 to 2010.

34

The artisanal fishery (sometimes described as ‘semi-industrial’ in Egyptian national reports), reached its peak in 1990 (Figure 13, Table A6). There was a continuous increase from 1950 to 1979, largely driven by our estimation process, and thus ignoring potential inter-annual variability. We did not have data for that period for the fishery and we assumed the lowest catch that was realized, which was the catch of 2010, for 1950 and linearly interpolated the rest of the period. For the period we had data, the fishery had a declining trend with fluctuations. In terms of the composition of the catch, groupers (Epinephelus spp.) had the highest share (31%) and second was emperors (Lethrinidae; 25%).

The subsistence (traditional) fishery had the most stable pattern (Figure 14, Table A7). Because of its diffuse and least regulated nature, this fishery sector was the most difficult in terms of getting estimates as to its size or catch. This is the catch taken by the smallest boats, some even without boats, who mostly fish for their own family consumption and is the least affected by markets and other external factors. Mullets (Mugilidae) had the biggest share of the total catch (23%), followed by jacks (Carangidae; 20%) and porgies and seabreams (Sparidae; 11%).

The recreational fishery was the fishery with the least contribution to the total catch and also the fishery that started last. Since then, however, it is the only fishery with a continuously increasing trend (Figure 15, Table A8). The number of boats involved in recreational fishing has increased considerably as sea-based tourism (both international and local) has increased in Egypt and became economically quite important. As compared to the other sectors, there was no dominant taxon in this fishery. The recreational fishery does not seem to get attention from the Egyptian fishery authority, possibly because of its limited size and/or that it does not fall into the commonly accepted fisheries in the country: fishing solely done for commercial purposes or to feed one’s family.

For all fisheries combined, the composition of the reconstructed total catch is dominated by jacks (Carangidae; 13%), red-eye round herring (Etrumeus sadina; 11%), scads (Decapterus spp.; 10%) and sardinella (Sardinella spp.; 6%) from the dominant purse seine fishery. The other dominant taxa are Berber ponyfish (Leiognathus berbis; 7%) and lizardfishes (Synodontidae; 5%) (Figure 16), both from the trawl fishery; the former is a discarded species, but the latter is retained. The total number of taxa identified in the Egyptian fishery was quite large (42), which accounted for 89% of the total catch. The remaining 11% was a mix of many taxa not identified separately, as their contribution was small. They were lumped in the ‘others’ group. In Figure (16), only the taxa that have major contributions to the total catch are presented. The actual catch composition data by taxonomic group identified in the catch reconstruction is given in Table (A9).

This reconstructed catch of Egypt in the Egyptian Red Sea EEZ is quite detailed in terms of its comprehensive coverage of the sectors and the composition of their catches, incorporating all the information available to us. To our knowledge, this is the only attempt made to clarify and standardize the Egyptian fisheries catch data for the Red Sea. When necessary assumptions were made, they are clearly stated. The methods and results are standardized and can be used for any further analysis of the fishery. We believe this work will help to better understand the Egyptian

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (1

0 t)3

0

0.4

0.8

1.2

1.6

Epinephelus spp.

Lethrinidae

Brachyura

Lethrinus mahsenaScaridae

Carangidae

Scomberomorus commerson

Holothuroidea

Others

Figure 11. Catch composition of the Egyptian trawl fishery (retained) in the Red Sea from 1950 to 2010.

Figure 12. Catch composition of the Egyptian trawl fishery discards in the Red Sea from 1950 to 2010.

Figure 13. Catch composition of the Egyptian artisanal fishery in the Red Sea from 1950 to 2010.

Egypt - Tesfamichael and Mehanna 35

fishery in the Red Sea in assessing, managing and conserving the livelihoods and the ecosystem (which cannot be separated from each other) and improve the practice of data collection and presentations of fishery data in the future. Most of the assumptions we had to make can be, in the future, replaced by some simple procedures in the data collections systems.

aCknowledgements

We would like to thank the fishery authorities and research institutes in Egypt for their collaboration during this research. Thanks also go to Ms. Eden and Ms. Emnet for hosting the first author during his field trip to Egypt. This research was supported by the Sea Around Us, a scientific collaboration between the University of British Columbia and The Pew Charitable Trusts.

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (1

0 t)3

0

1

2

3

4

Mugilidae

Carangidae

Sparidae

LutjanidaePenaeidae

Encrasicholina punctiferSardinella spp.

SiganidaeBrachyura

Others

Sphyraena spp. Argyrops spinifer

Holothuroidea

Figure 14. Catch composition of the Egyptian subsistence fishery in the Red Sea from 1950 to 2010.

Figure 15. Catch composition of the Egyptian recreational fishery in the Red Sea from 1950 to 2010.

Figure 16. Composition of the total Egyptian fishery catch in the Red Sea from 1950 to 2010 .

36

referenCes

Al-Khol AA and El-Hawary MM (1970) Some penaeids of the Red Sea. Bull. Inst. Oceanogr. Fish., Cairo 1: 339-377.Barrania AA and El Shennawi MA (1979) Report on the exploratory socio-economic survey of the Egyptian Red Sea

fisheries. FAO/UNDP Proj. for Development of Fisheries in Areas of the Red Sea and Gulf of Aden, Suez, Egypt.Chakraborty D (1984a) Fish landings on the Red Sea and Gulf of Aden coast of the member countries: A preliminary

estimate. Development of Fisheries in Areas of the Red Sea and Gulf of Aden, United Nations Development Programme (UNDP) and Food and Agriculture Organization (FAO) of the United Nations, Suez, Egypt. 29 p.

Chakraborty D (1984b) Fishery statistics in the Egyptian Red Sea coast an expanded plan. FAO/UNDP, Suez (Egypt).Chakraborty D, Moharram M and Waheed A (1983) An account of basic fisheries information of the South Sinai

Governorate in Egypt. Development of Fisheries in Areas of the Red Sea and Gulf of Aden, United Nations Development Programme (UNDP) and Food and Agriculture Organization (FAO) of the United Nations, Cairo (Egypt). 26 p.

El-Gammal FI and Mehanna SF (1999) Maximum sustainable yield of the demersal fish resources exploited by trawling in the Gulf of Suez with special reference to shrimp fishery. In The role of Science in the Development of Egyptian Society and Environment, 23-24 October, 1999. 198-210 p.

El-Gammal FI and Mehanna SF (2002) Purse-seine fishery in the Gulf of Suez with special reference to sardine fishery. Asian J. Fish 15(1): 81-88.

El-Ganainy AAH, Yassien MH and Ibrahim EA (2005) Bottom trawl discards in the Gulf of Suez, Egypt. Egyptian Journal of Aquatic Research Vol. 31, special issue: 240 – 255.

FAO (2004) The Arab Republic of Egypt: Fishery country profile. Food and Agriculture Organization of the United Nations (FAO), Rome. Available at: http://www.fao.org/fi/oldsite/FCP/en/EGY/profile.htm [Accessed: Feb. 10, 2010].

FAO (2010) Fishery and aquaculture country profile: The arabic Republic of Egypt. Food and Agriculture Organization of the United Nations (FAO), Rome. Available at: http://www.fao.org/fishery/facp/EGY/en [Accessed: March 10, 2011].

Feidi IH (1976) Egyptian high seas fisheries development project. Food and Agriculture Organization (FAO) of the United Nations, Cairo, Egypt. 58 p.

Froese R and Pauly D (2012) FishBase. Available at: www.fishbase.org [Accessed: May 24, 2012].GAFRD (2012) General Authority for Fisheries Resources Development database.Suez.Hawkins JP and Roberts CM (1994) The Growth of Coastal Tourism in the Red Sea: Present and Future Effects on

Coral Reefs. Ambio 23(8): 503-508.Latif AFA and Shenouda T (1972) Biological studies on Rhonciscus striatus (fam. Pomadasyidae) from the Gulf of

Zuez. Bull. Inst. Ocean. Fish., UAR 2: 105-134.Mehanna SF (1999) An assessment and management of the coral reef fish stocks in the Gulf of Suez. Egyp. J. Aquat.

Biol. & Fish. 3(2): 103-114.Mehanna SF (2007) Fisheries assessment of Lake Nasser, Egypt with special reference to tilapia fishery. J. Egyp. Acad.

Soc. Environ. Develop. 8(4): 27-35.Mehanna SF and El-Gammal FI (2007) Gulf of Suez fisheries: current status, assessment and management. J. King

Abdulaziz University, Mar. Sci. 18: 3-18.Pauly D, Christensen V, Dalsgaard J, Froese R and Torres F, Jr. (1998) Fishing down marine food webs. Science

(Washington) 279(5352): 860-863.Pitcher TJ and Hollingworth CE (2002) Fishing for fun: where’s the catch? pp. 1-16 In Pitcher TJ and Hollingworth CE

(eds.), Recreational fisheries: ecological, economic and social evaluation. Blackwall Science Ltd., Oxford, UK.Rafail SZ (1970) Studies of populations and exploitation status of Egyption Red Sea abundant sardines. Bull. Inst.

Oceanogr. Fish., UAR 1: 129-148.Rafail SZ (1972) Studies of Red Sea fisheries by light and purse-seine near Al-Ghardaqa. Bull. Inst. Oceanogr. Fish.,

UAR (2): 25-49.Sanders MJ, Kedidi SM and Hegazy MR (1984a) Catches, fishing efforts, catches per fishing effort, and fishing locations

for the Gulf of Suez and Egyptian Red Sea coast purse seine fishery during 1979 to 1982. FAO/UNDP, Suez (Egypt).

Sanders MJ, Kedidi SM and Hegazy MR (1984b) Catches, fishing efforts, catches per fishing effort, and fishing locations for the Gulf of Suez and Egyptian Red Sea coast trawl fishery during 1979 to 1982. FAO/UNDP, Suez (Egypt).

Sanders MJ, Kedidi SM and Hegazy MR (1984c) Catches, fishing efforts, catches per fishing effort, and fishing locations for the Gulf of Suez and Egyptian Red Sea fishery for reef associated fish during 1979 to 1982. FAO/UNDP, Suez (Egypt).

Sanders MJ and Morgan GR (1989) Review of the fisheries resources of the Red Sea and Gulf of Aden. FAO, Rome. 138 p.

Tesfamichael D (2012) Assessment of the Red Sea ecosystem with emphasis on fisheries. PhD, University of British Columbia, Resource Management and Environmental Studies, Vancouver. 241 p.

Tesfamichael D and Elawad AN (2012) Reconstructing Red Sea fisheries of Sudan: Foreign aid and fisheries. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Egypt - Tesfamichael and Mehanna 37

Tesfamichael D and Mohamud S (2012) Reconstructing Red Sea fisheries of Eritrea: A case study of the relationship between political stability and fisheries development. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D and Pauly D (2011) Learning from the Past for Future Policy: Approaches to Time-series Catch Data Reconstruction. Western Indian Ocean J. Mar. Sci. 10(2): 99-106.

Tesfamichael D and Pitcher TJ (2006) Multidisciplinary evaluation of the sustainability of Red Sea fisheries using Rapfish. Fisheries Research 78(2-3): 227-235.

Tesfamichael D and Pitcher TJ (2007) Estimating the unreported catch of Eritrean Red Sea fisheries. African Journal of Marine Science 29(1): 55-63.

Tesfamichael D, Rossing P and Awadh H (2012) The marine fisheries of Yemen with emphasis on the Red Sea and cooperatives. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Watson R and Pauly D (2001) Systematic distortions in world fisheries catch trends. Nature 414(6863): 534-536.Zeller D, Booth S, Davis G and Pauly D (2007) Re-estimation of small-scale fisheries catches for U.S. flag island areas

in the Western Pacific: The last 50 years. US Fishery Bulletin 105(2): 266-277.

38

Appendix Table A1: Reconstructed catch (in tonnes) of the Egyptian fishery in the Red Sea by sector and the data Egypt submitted to FAO from 1950 to 2010.Year FAO landings Reconstructed total catch Purse seine Discards Subsistence Trawl Artisanal Recreational1950 2,900 5,535 133 1,578 3,236 394 194 01951 3,900 5,683 133 1,625 3,270 418 237 01952 6,100 5,832 133 1,669 3,308 441 281 01953 6,400 5,980 133 1,710 3,349 464 324 01954 6,500 6,130 133 1,749 3,392 488 368 01955 7,800 6,278 133 1,785 3,438 511 411 01956 10,101 5,247 133 907 3,486 267 454 01957 9,401 11,839 133 5,895 3,535 1,778 498 01958 9,300 12,397 133 6,215 3,586 1,922 541 01959 11,000 12,570 133 6,237 3,637 1,978 585 01960 11,600 11,271 2,650 3,248 3,689 1,056 628 01961 12,000 18,417 4,398 7,207 3,740 2,400 672 01962 21,400 30,454 8,154 13,268 3,791 4,526 715 01963 20,300 37,840 7,547 19,043 3,841 6,651 758 01964 14,300 41,475 3,460 24,546 3,890 8,777 802 01965 10,800 41,749 2,913 24,930 3,937 9,124 845 01966 8,200 29,647 3,619 15,392 3,983 5,764 889 01967 6,500 29,328 5,240 13,831 4,027 5,298 932 01968 6,700 29,088 6,860 12,334 4,069 4,833 976 161969 6,900 28,905 8,481 10,900 4,106 4,367 1,019 321970 6,200 28,776 10,102 9,525 4,138 3,901 1,062 481971 9,400 30,225 13,031 8,358 4,166 3,499 1,106 651972 9,600 33,700 11,956 11,433 4,189 4,891 1,149 821973 4,400 16,729 2,666 5,958 4,209 2,604 1,193 991974 6,168 30,235 14,350 7,124 4,228 3,181 1,236 1161975 5,526 38,618 9,580 16,055 4,247 7,322 1,280 1341976 9,303 46,756 18,606 15,289 4,266 7,120 1,323 1521977 7,899 39,750 15,130 12,740 4,286 6,058 1,366 1701978 9,140 37,421 14,424 11,507 4,306 5,586 1,410 1881979 17,542 40,630 20,358 9,552 4,327 4,733 1,453 2071980 14,783 36,123 13,741 10,844 4,348 5,484 1,480 2261981 15,774 35,589 11,923 11,510 4,369 5,939 1,602 2461982 13,386 35,869 15,716 9,098 4,391 4,790 1,608 2661983 13,908 42,474 23,320 8,588 4,413 4,613 1,254 2861984 11,343 43,490 26,437 7,140 4,419 3,912 1,276 3061985 21,256 35,339 18,483 6,795 4,425 3,797 1,512 3271986 19,708 35,119 14,829 9,059 4,431 5,163 1,289 3481987 23,300 35,658 17,688 7,621 4,435 4,429 1,116 3691988 28,450 38,651 22,342 6,546 4,436 3,879 1,057 3911989 43,580 48,012 31,200 6,599 4,429 3,986 1,386 4121990 39,924 46,970 31,596 5,431 4,413 3,345 1,753 4321991 41,937 41,521 26,705 5,566 4,387 3,494 917 4521992 43,300 43,714 26,840 7,060 4,352 4,517 474 4711993 50,740 49,255 33,512 6,082 4,311 3,966 894 4901994 48,300 33,232 19,323 4,997 4,267 3,321 816 5081995 47,300 34,119 19,470 5,458 4,220 3,697 749 5251996 48,435 30,835 16,435 5,169 4,172 3,567 949 5431997 57,417 33,507 18,266 5,542 4,122 3,897 1,120 5601998 57,063 28,347 15,347 4,503 4,070 3,225 625 5771999 82,400 24,983 12,093 4,621 4,016 3,372 287 5942000 75,972 33,454 21,404 4,105 3,961 3,052 321 6112001 73,559 28,684 15,547 4,656 3,905 3,526 423 6272002 72,881 32,044 17,411 5,495 3,847 4,238 410 6432003 70,408 31,586 16,182 5,915 3,788 4,647 395 6592004 63,914 31,994 17,436 5,422 3,727 4,339 341 7292005 50,732 24,248 9,292 5,542 3,664 4,517 436 7972006 46,940 22,783 9,372 4,722 3,598 3,919 307 8652007 46,986 23,248 10,177 4,539 3,531 3,838 231 9322008 47,361 26,003 12,229 4,893 3,461 4,213 209 9982009 49,031 26,662 12,661 4,974 3,388 4,361 216 1,0622010 43,974 24,279 11,355 4,381 3,312 3,911 195 1,125

Egypt - Tesfamichael and Mehanna 39

Appendix Table A2: Reconstructed catch (in tonnes) of the Egyptian fishery in the Red Sea by component from 1950 to 2010.

Year Reported Unreported Discards1950 1,290 2,667 1,5781951 1,314 2,744 1,6251952 1,339 2,824 1,6691953 1,591 2,679 1,7101954 1,622 2,758 1,7491955 1,654 2,838 1,7851956 1,455 2,885 9071957 2,559 3,385 5,8951958 2,842 3,340 6,2151959 2,889 3,443 6,2371960 4,782 3,240 3,2481961 7,387 3,823 7,2071962 13,094 4,092 13,2681963 13,443 5,355 19,0431964 9,719 7,209 24,5461965 9,483 7,336 24,9301966 7,067 7,188 15,3921967 5,351 10,147 13,8311968 4,540 12,213 12,3341969 4,759 13,245 10,9001970 5,054 14,198 9,5251971 5,308 16,558 8,3581972 5,185 17,081 11,4331973 2,306 8,464 5,9581974 4,929 18,182 7,1241975 4,919 17,643 16,0551976 8,950 22,517 15,2891977 7,809 19,201 12,7401978 7,876 18,039 11,5071979 13,095 17,982 9,5521980 11,536 13,743 10,8441981 12,148 11,932 11,5101982 9,563 17,208 9,0981983 9,918 23,967 8,5881984 8,395 27,956 7,1401985 7,245 21,299 6,7951986 9,452 16,607 9,0591987 11,585 16,453 7,6211988 10,692 21,412 6,5461989 13,405 28,007 6,5991990 15,243 26,296 5,4311991 15,005 20,949 5,5661992 13,993 22,662 7,0601993 16,700 26,473 6,0821994 14,202 14,032 4,9971995 10,453 18,209 5,4581996 9,181 16,484 5,1691997 9,714 18,251 5,5421998 8,538 15,306 4,5031999 11,666 8,697 4,6212000 10,876 18,473 4,1052001 10,008 14,020 4,6562002 11,232 15,318 5,4952003 16,302 9,369 5,9152004 15,706 10,865 5,4222005 13,144 5,563 5,5422006 13,352 4,709 4,7222007 13,649 5,059 4,5392008 13,132 7,977 4,8932009 12,639 9,049 4,9742010 11,637 8,261 4,381

40Appendix Table A3: Catch composition (in tonnes) of the Egyptian purse seine fishery in the Red Sea from 1950 to 2010.Year Etrumeus

sadinaCarangidae Decapterus spp. Sardinella spp. Scomber

japonicusRastrelliger kanagurta

Encrasicholina punctifer

Sphyraena spp. Others

1950 0 0 0 122 0 0 0 0 111951 0 0 0 122 0 0 0 0 111952 0 0 0 122 0 0 0 0 111953 0 0 0 122 0 0 0 0 111954 0 0 0 122 0 0 0 0 111955 0 0 0 122 0 0 0 0 111956 0 0 0 122 0 0 0 0 111957 0 0 0 122 0 0 0 0 111958 0 0 0 122 0 0 0 0 111959 0 0 0 122 0 0 0 0 111960 0 0 0 2,438 0 0 0 0 2121961 0 0 0 3,563 0 0 0 0 8361962 0 0 0 7,420 0 0 0 0 7341963 0 0 0 7,170 0 0 0 0 3771964 395 290 290 2,324 0 93 10 4 531965 333 244 244 1,956 0 78 9 3 451966 413 304 304 2,430 0 97 11 4 561967 1,490 1,095 1,095 955 0 351 39 15 2011968 1,951 1,433 1,433 1,250 0 460 51 20 2631969 2,412 1,772 1,772 1,545 0 568 63 24 3251970 2,872 2,110 2,110 1,841 0 677 75 29 3871971 3,705 2,722 2,722 2,374 0 873 97 37 4991972 3,400 2,498 2,498 2,179 0 801 89 34 4581973 758 557 557 486 0 179 20 8 1021974 4,080 2,998 2,998 2,615 0 961 107 41 5501975 2,724 2,001 2,001 1,746 0 642 71 27 3671976 5,291 3,887 3,887 3,390 0 1,247 139 53 7131977 4,302 3,161 3,161 2,757 0 1,014 113 43 5801978 4,101 3,013 3,013 2,628 0 966 107 41 5531979 5,789 4,253 4,253 3,710 0 1,364 152 58 7801980 3,907 2,871 2,871 2,504 0 921 102 39 5271981 1,788 3,007 3,007 3,136 0 754 13 11 2071982 2,579 4,072 4,072 3,331 0 925 26 16 6931983 5,177 5,340 5,340 5,130 0 1,516 93 47 6761984 7,169 6,669 6,669 1,220 3,171 457 0 0 1,0821985 5,012 4,662 4,662 853 2,217 320 0 0 7571986 4,021 3,741 3,741 684 1,779 256 0 0 6071987 4,796 4,462 4,462 816 2,122 306 0 0 7241988 6,058 5,636 5,636 1,031 2,680 386 0 0 9151989 8,460 7,870 7,870 1,440 3,742 540 0 0 1,2771990 8,568 7,970 7,970 1,458 3,790 546 0 0 1,2941991 7,241 6,736 6,736 1,233 3,203 462 0 0 1,0931992 7,278 6,771 6,771 1,239 3,219 464 0 0 1,0991993 9,087 8,453 8,453 1,547 4,019 580 0 0 1,3721994 5,240 4,874 4,874 892 2,318 334 0 0 7911995 5,280 4,911 4,911 899 2,335 337 0 0 7971996 4,457 4,146 4,146 759 1,971 284 0 0 6731997 4,953 4,608 4,608 843 2,191 316 0 0 7481998 4,162 3,871 3,871 708 1,841 265 0 0 6281999 3,279 3,050 3,050 558 1,450 209 0 0 4952000 5,804 5,399 5,399 988 2,567 370 0 0 8762001 4,216 3,922 3,922 718 1,865 269 0 0 6362002 4,721 4,392 4,392 804 2,088 301 0 0 7132003 4,388 4,082 4,082 747 1,941 280 0 0 6622004 4,728 4,398 4,398 805 2,091 302 0 0 7142005 2,520 2,344 2,344 429 1,114 161 0 0 3802006 2,541 2,364 2,364 433 1,124 162 0 0 3842007 2,760 2,567 2,567 470 1,221 176 0 0 4172008 3,316 3,085 3,085 564 1,467 211 0 0 5012009 3,433 3,194 3,194 584 1,519 219 0 0 5182010 3,079 2,864 2,864 524 1,362 196 0 0 465

Egypt - Tesfamichael and Mehanna 41Appendix Table A4: Catch composition (in tonnes) of the Egyptian trawl fishery (retained) in the Red Sea from 1950 to 2010.Year Synodontidae Lutjanidae Penaeidae Nemipteridae Mullidae Sepiidae Carangidae Decapterus spp. Others1950 190 49 41 32 15 11 8 8 391951 201 52 43 34 16 12 9 9 421952 212 55 45 36 17 12 9 9 441953 224 58 48 38 18 13 10 10 461954 235 61 50 40 19 14 11 11 491955 246 64 53 42 19 14 11 11 511956 128 33 27 22 10 7 6 6 271957 856 222 183 145 68 50 38 38 1781958 926 240 198 157 73 54 41 41 1921959 953 247 203 162 75 55 43 43 1981960 508 132 109 86 40 29 23 23 1061961 1,156 299 247 196 92 67 52 52 2401962 2,180 564 465 370 173 126 97 97 4531963 3,204 829 684 543 254 186 143 143 6651964 4,227 1,094 903 717 335 245 189 189 8781965 4,394 1,138 938 746 348 255 196 196 9121966 2,776 719 593 471 220 161 124 124 5761967 2,552 661 545 433 202 148 114 114 5301968 2,328 603 497 395 184 135 104 104 4831969 2,103 544 449 357 167 122 94 94 4371970 1,879 486 401 319 149 109 84 84 3901971 1,685 436 360 286 133 98 75 75 3501972 2,356 610 503 400 187 137 105 105 4891973 1,254 325 268 213 99 73 56 56 2601974 1,532 397 327 260 121 89 68 68 3181975 3,527 913 753 598 279 204 158 158 7321976 3,429 888 732 582 271 199 153 153 7121977 2,918 755 623 495 231 169 130 130 6061978 2,690 696 575 456 213 156 120 120 5591979 2,279 590 487 387 180 132 102 102 4731980 2,465 758 651 521 171 136 117 117 5481981 2,964 641 641 441 174 190 147 147 5941982 2,399 630 354 360 288 125 82 82 4691983 2,195 561 522 385 142 132 107 107 4611984 1,065 600 836 342 108 226 172 172 3911985 1,224 592 760 322 122 156 121 121 3801986 2,661 547 598 277 183 132 124 124 5161987 1,843 549 724 168 223 198 141 141 4431988 1,023 830 738 146 348 118 144 144 3881989 695 1,338 779 120 322 130 102 102 3991990 424 1,076 818 70 288 156 89 89 3341991 799 741 817 101 338 132 108 108 3491992 1,242 998 781 151 598 178 59 59 4521993 697 1,032 814 125 482 236 92 92 3971994 538 710 655 129 374 277 153 153 3321995 1,134 559 550 275 456 190 82 82 3701996 1,172 485 573 236 395 165 92 92 3571997 1,184 494 582 413 365 147 161 161 3901998 992 424 356 463 277 105 143 143 3231999 1,073 479 349 526 311 123 87 87 3372000 902 459 382 332 320 147 102 102 3052001 1,064 529 361 377 366 172 152 152 3532002 1,481 573 314 498 469 215 132 132 4242003 1,445 705 368 567 546 258 146 146 4652004 1,352 648 665 496 458 303 41 41 3352005 1,448 586 674 494 469 304 74 74 3942006 1,256 412 362 434 446 212 202 202 3922007 1,280 386 319 442 362 172 246 246 3842008 1,426 437 382 491 349 182 262 262 4212009 1,476 452 396 509 362 189 271 271 4362010 1,324 405 355 456 324 169 243 243 391

42Appendix Table A5: Catch composition (in tonnes) of the Egyptian trawl fishery (discarded) in the Red Sea from 1950 to 2010.Year Leiognathus

berbisChampsodon

capensisEquulites elongatus

Pseudorhombus arsius

Charybdis hellerii

Clypeaster reticulatus

Jacksonaster depressum

Callyspongia monilata

Pione vastifica

Others

1950 414 296 178 118 79 39 39 28 20 3671951 427 305 183 122 81 41 41 28 20 3781952 438 313 188 125 83 42 42 29 21 3881953 449 321 192 128 86 43 43 30 21 3981954 459 328 197 131 87 44 44 31 22 4071955 468 335 201 134 89 45 45 31 22 4151956 238 170 102 68 45 23 23 16 11 2111957 1,547 1,105 663 442 295 147 147 103 74 1,3711958 1,631 1,165 699 466 311 155 155 109 78 1,4451959 1,637 1,169 702 468 312 156 156 109 78 1,4501960 853 609 365 244 162 81 81 57 41 7551961 1,892 1,351 811 541 360 180 180 126 90 1,6761962 3,483 2,488 1,493 995 663 332 332 232 166 3,0851963 4,999 3,571 2,142 1,428 952 476 476 333 238 4,4271964 6,443 4,602 2,761 1,841 1,227 614 614 430 307 5,7071965 6,544 4,674 2,805 1,870 1,247 623 623 436 312 5,7961966 4,040 2,886 1,732 1,154 770 385 385 269 192 3,5791967 3,631 2,593 1,556 1,037 692 346 346 242 173 3,2161968 3,238 2,313 1,388 925 617 308 308 216 154 2,8681969 2,861 2,044 1,226 817 545 272 272 191 136 2,5341970 2,500 1,786 1,072 714 476 238 238 167 119 2,2141971 2,194 1,567 940 627 418 209 209 146 104 1,9431972 3,001 2,144 1,286 857 572 286 286 200 143 2,6581973 1,564 1,117 670 447 298 149 149 104 74 1,3851974 1,870 1,336 801 534 356 178 178 125 89 1,6561975 4,215 3,010 1,806 1,204 803 401 401 281 201 3,7331976 4,013 2,867 1,720 1,147 764 382 382 268 191 3,5551977 3,344 2,389 1,433 956 637 319 319 223 159 2,9621978 3,021 2,158 1,295 863 575 288 288 201 144 2,6751979 2,507 1,791 1,075 716 478 239 239 167 119 2,2211980 2,847 2,033 1,220 813 542 271 271 190 136 2,5211981 3,021 2,158 1,295 863 575 288 288 201 144 2,6761982 2,388 1,706 1,023 682 455 227 227 159 114 2,1151983 2,254 1,610 966 644 429 215 215 150 107 1,9971984 1,874 1,339 803 536 357 179 179 125 89 1,6601985 1,784 1,274 764 510 340 170 170 119 85 1,5801986 2,378 1,699 1,019 679 453 226 226 159 113 2,1061987 2,000 1,429 857 572 381 191 191 133 95 1,7721988 1,718 1,227 736 491 327 164 164 115 82 1,5221989 1,732 1,237 742 495 330 165 165 115 82 1,5341990 1,426 1,018 611 407 272 136 136 95 68 1,2631991 1,461 1,044 626 417 278 139 139 97 70 1,2941992 1,853 1,324 794 529 353 176 176 124 88 1,6411993 1,596 1,140 684 456 304 152 152 106 76 1,4141994 1,312 937 562 375 250 125 125 87 62 1,1621995 1,433 1,023 614 409 273 136 136 96 68 1,2691996 1,357 969 581 388 258 129 129 90 65 1,2021997 1,455 1,039 623 416 277 139 139 97 69 1,2891998 1,182 844 507 338 225 113 113 79 56 1,0471999 1,213 866 520 347 231 116 116 81 58 1,0742000 1,078 770 462 308 205 103 103 72 51 9542001 1,222 873 524 349 233 116 116 81 58 1,0822002 1,442 1,030 618 412 275 137 137 96 69 1,2772003 1,553 1,109 665 444 296 148 148 104 74 1,3752004 1,423 1,017 610 407 271 136 136 95 68 1,2612005 1,455 1,039 624 416 277 139 139 97 69 1,2892006 1,239 885 531 354 236 118 118 83 59 1,0982007 1,192 851 511 340 227 113 113 79 57 1,0552008 1,284 917 550 367 245 122 122 86 61 1,1382009 1,306 933 560 373 249 124 124 87 62 1,1562010 1,150 821 493 329 219 110 110 77 55 1,019

Egypt - Tesfamichael and Mehanna 43Appendix Table A6: Catch composition (in tonnes) of the Egyptian artisanal fishery in the Red Sea from 1950 to 2010.Year Epinephelus spp. Lethrinidae Brachyura Lethrinus mahsena Scaridae Carangidae Scomberomorus commerson Sparidae1950 67 55 0 18 9 9 5 41951 83 67 0 22 12 11 6 51952 98 80 0 26 14 14 7 61953 113 92 0 30 16 16 8 71954 128 104 0 33 18 18 9 81955 143 117 0 37 20 20 10 91956 127 104 118 33 18 18 9 81957 140 114 130 37 19 19 10 91958 152 124 141 40 21 21 10 101959 164 134 152 43 23 23 11 111960 176 144 163 46 25 24 12 121961 188 154 175 49 26 26 13 121962 201 164 186 53 28 28 14 131963 213 173 197 56 30 29 15 141964 225 183 209 59 31 31 15 151965 294 240 0 77 41 41 20 191966 249 203 231 65 35 35 17 161967 261 213 242 68 37 36 18 171968 274 223 254 72 38 38 19 181969 286 233 265 75 40 40 20 191970 369 301 0 97 52 51 25 241971 384 313 0 101 54 53 26 251972 400 326 0 105 56 55 27 261973 415 338 0 109 58 57 29 271974 430 350 0 113 60 59 30 281975 445 363 0 116 62 62 31 291976 371 303 344 97 52 51 26 241977 383 313 355 100 54 53 26 251978 395 322 367 104 55 55 27 261979 408 332 378 107 57 56 28 271980 406 308 414 131 61 55 29 301981 496 343 407 100 57 72 24 321982 399 456 416 101 63 53 22 221983 364 263 311 100 50 50 36 251984 358 292 332 94 50 50 25 231985 526 429 0 138 73 73 36 341986 448 365 0 117 63 62 31 291987 388 316 0 102 54 54 27 251988 367 300 0 96 51 51 25 241989 482 393 0 126 67 67 33 321990 609 497 0 160 85 84 42 401991 319 260 0 83 44 44 22 211992 165 134 0 43 23 23 11 111993 311 254 0 81 43 43 21 201994 284 231 0 74 40 39 20 191995 210 171 195 55 29 29 14 141996 266 217 247 70 37 37 18 171997 314 256 291 82 44 43 22 211998 175 143 163 46 24 24 12 111999 81 66 75 21 11 11 6 52000 90 73 83 24 13 12 6 62001 119 97 93 31 17 16 8 82002 115 94 24 30 16 16 8 82003 111 90 79 29 15 15 8 72004 96 78 70 25 13 13 7 62005 122 100 80 32 17 17 8 82006 86 70 76 23 12 12 6 62007 65 53 2 17 9 9 4 42008 59 48 1 15 8 8 4 42009 61 49 1 16 8 8 4 42010 54 44 1 14 8 8 4 4

44

Table A6 continuedYear Euthynnus

affinisElasmobranchii Holothuroidea Serranidae Variola

loutiPanulirus Epinephelus

tauvinaLethrinus

borbonicusOthers

1950 4 3 0 0 0 0 0 0 191951 5 3 0 0 0 0 0 0 241952 6 4 0 0 0 0 0 0 281953 7 4 0 0 0 0 0 0 321954 8 5 0 0 0 0 0 0 371955 9 6 0 0 0 0 0 0 411956 8 5 0 0 0 0 0 0 61957 8 5 0 0 0 0 0 0 71958 9 6 0 0 0 0 0 0 71959 10 6 0 0 0 0 0 0 81960 11 7 0 0 0 0 0 0 91961 11 7 0 0 0 0 0 0 91962 12 8 0 0 0 0 0 0 101963 13 8 0 0 0 0 0 0 101964 14 9 0 0 0 0 0 0 111965 18 11 0 0 0 0 0 0 851966 15 10 0 0 0 0 0 0 121967 16 10 0 0 0 0 0 0 131968 17 11 0 0 0 0 0 0 131969 17 11 0 0 0 0 0 0 141970 22 14 0 0 0 0 0 0 1061971 23 15 0 0 0 0 0 0 1111972 24 16 0 0 0 0 0 0 1151973 25 16 0 0 0 0 0 0 1191974 26 17 0 0 0 0 0 0 1241975 27 17 0 0 0 0 0 0 1281976 22 14 0 0 0 0 0 0 181977 23 15 0 0 0 0 0 0 191978 24 15 0 0 0 0 0 0 191979 25 16 0 0 0 0 0 0 201980 11 13 0 0 0 0 0 0 221981 40 10 0 0 0 0 0 0 211982 26 30 0 0 0 0 0 0 221983 25 12 0 0 0 0 0 0 161984 22 14 0 0 0 0 0 0 171985 32 20 0 0 0 0 0 0 1511986 27 17 0 0 0 0 0 0 1291987 23 15 0 0 0 0 0 0 1121988 22 14 0 0 0 0 0 0 1061989 29 19 0 0 0 0 0 0 1391990 37 24 0 0 0 0 0 0 1751991 19 12 0 0 0 0 0 0 921992 10 6 0 0 0 0 0 0 471993 19 12 0 0 0 0 0 0 891994 17 11 0 0 0 0 0 0 821995 13 8 0 0 0 0 0 0 101996 16 10 0 0 0 0 0 0 131997 19 12 0 0 0 0 0 0 151998 11 7 0 0 0 0 0 0 91999 5 3 0 0 0 0 0 0 42000 5 3 1 0 0 0 0 0 42001 7 5 17 0 0 0 0 0 62002 7 4 82 0 0 0 0 0 62003 7 4 21 0 0 3 0 0 52004 6 4 1 0 0 17 0 0 52005 7 5 1 0 0 33 0 0 62006 5 3 1 0 0 3 0 0 42007 4 3 0 25 21 1 11 0 32008 4 2 0 25 26 0 2 0 32009 4 2 0 28 19 1 3 3 32010 3 2 0 28 14 1 2 6 3

Egypt - Tesfamichael and Mehanna 45

Appendix Table A7: Catch composition (in tonnes) of the Egyptian subsistence fishery in the Red Sea from 1950 to 2010.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 151950 774 664 364 310 270 170 170 136 0 39 0 11 0 4 3241951 782 672 368 313 273 172 172 137 0 39 0 12 0 4 3271952 791 679 372 317 276 174 174 139 0 39 0 12 0 4 3311953 801 688 377 321 280 176 176 140 0 40 0 12 0 4 3351954 811 697 382 325 283 178 178 142 0 40 0 12 0 4 3391955 822 706 387 329 287 181 181 144 0 41 0 12 0 4 3441956 834 716 392 334 291 183 183 146 0 42 0 12 0 4 3491957 846 726 398 338 295 186 186 148 0 42 0 13 0 5 3541958 858 736 403 343 299 188 188 150 0 43 0 13 0 5 3591959 870 747 409 348 304 191 191 152 0 43 0 13 0 5 3641960 871 748 410 349 304 191 191 153 41 43 0 13 0 5 3691961 880 755 414 352 307 193 193 154 55 44 0 13 0 5 3741962 894 768 421 358 312 196 196 157 47 45 0 13 0 5 3791963 904 776 425 362 316 199 199 158 54 45 0 13 0 5 3841964 912 783 429 365 318 200 200 160 69 45 0 14 0 5 3891965 942 808 443 377 329 207 207 165 0 47 0 14 0 5 3941966 926 795 435 371 323 203 203 162 101 46 0 14 0 5 3981967 862 740 405 345 301 189 189 151 382 43 0 13 0 5 4031968 900 772 423 360 314 198 198 158 276 45 0 13 0 5 4071969 942 809 443 377 329 207 207 165 149 47 0 14 0 5 4111970 990 850 466 396 346 217 217 173 0 49 0 15 0 5 4141971 996 855 469 399 348 219 219 175 0 50 0 15 0 5 4171972 1,002 860 471 401 350 220 220 176 0 50 0 15 0 5 4191973 1,007 864 473 403 351 221 221 176 0 50 0 15 0 5 4211974 1,011 868 476 405 353 222 222 177 0 50 0 15 0 5 4231975 1,016 872 478 407 355 223 223 178 0 51 0 15 0 5 4251976 1,015 871 477 406 354 223 223 178 20 51 0 15 0 5 4271977 1,022 877 481 409 357 224 224 179 12 51 0 15 0 6 4291978 1,025 880 482 410 358 225 225 180 20 51 0 15 0 6 4311979 1,033 887 486 414 361 227 227 181 5 52 0 15 0 6 4331980 1,034 888 486 414 361 227 227 181 23 52 0 15 0 6 4351981 1,045 897 491 418 365 229 229 183 2 52 0 15 0 6 4371982 1,041 894 490 417 363 229 229 182 35 52 0 15 0 6 4391983 1,027 882 483 411 358 226 226 180 107 51 0 15 0 6 4411984 1,054 905 496 422 368 232 232 185 11 53 0 16 0 6 4421985 1,058 909 498 424 369 233 233 185 0 53 0 16 0 6 4431986 1,060 910 498 424 370 233 233 186 0 53 0 16 0 6 4431987 1,061 911 499 425 370 233 233 186 0 53 0 16 0 6 4441988 1,061 911 499 425 370 233 233 186 0 53 0 16 0 6 4441989 1,059 909 498 424 370 233 233 186 0 53 0 16 0 6 4431990 1,055 906 496 422 368 232 232 185 0 53 0 16 0 6 4411991 1,049 901 494 420 366 230 230 184 0 52 0 16 0 6 4391992 1,041 894 490 417 363 229 229 182 0 52 0 15 0 6 4351993 1,031 885 485 413 360 227 227 181 0 51 0 15 0 6 4311994 1,021 876 480 408 356 224 224 179 0 51 0 15 0 6 4271995 923 792 434 369 322 203 203 162 327 46 0 14 0 5 4221996 998 857 469 399 348 219 219 175 0 50 0 15 0 5 4171997 986 846 464 394 344 216 216 173 1 49 0 15 0 5 4121998 964 827 453 386 336 212 212 169 36 48 0 14 0 5 4071999 918 788 432 367 320 202 202 161 161 46 0 14 0 5 4022000 833 715 392 334 291 183 183 146 426 42 0 12 4 4 3962001 891 765 419 357 311 196 196 156 135 44 0 13 25 5 3912002 778 668 366 311 271 171 171 136 122 39 0 12 415 4 3852003 758 651 357 303 265 167 167 133 355 38 164 11 94 4 3232004 746 640 351 299 260 164 164 131 168 37 628 11 3 4 1212005 798 685 375 319 278 175 175 140 71 40 224 12 1 4 3662006 777 667 365 311 271 171 171 136 65 39 249 12 1 4 3602007 741 637 349 297 259 163 163 130 62 37 326 11 0 4 3532008 787 676 370 315 275 173 173 138 49 39 101 12 2 4 3462009 745 639 350 298 260 164 164 130 69 37 178 11 0 4 3392010 735 631 346 294 256 161 161 129 63 37 153 11 0 4 331

1: Mugilidae; 2: Carangidae; 3: Sparidae; 4: Lutjanidae; 5: Penaeidae; 6: Encrasicholina punctifer; 7: Sardinella spp.; 8: Siganidae; 9: Brachyura; 10: Sphyraena spp.; 11: Argyrops spinifer; 12: Sepiidae; 13: Holothuroidea; 14: Sciaenidae; 15: Others

46Appendix Table A8: Catch composition (in tonnes) of the Egyptian recreational fishery in the Red Sea from 1950 to 2010.Year Carangidae Lutjanidae Serranidae Lethrinidae Nemipteridae Others1950 0 0 0 0 0 01951 0 0 0 0 0 01952 0 0 0 0 0 01953 0 0 0 0 0 01954 0 0 0 0 0 01955 0 0 0 0 0 01956 0 0 0 0 0 01957 0 0 0 0 0 01958 0 0 0 0 0 01959 0 0 0 0 0 01960 0 0 0 0 0 01961 0 0 0 0 0 01962 0 0 0 0 0 01963 0 0 0 0 0 01964 0 0 0 0 0 01965 0 0 0 0 0 01966 0 0 0 0 0 01967 0 0 0 0 0 01968 3 3 3 2 2 21969 6 6 6 5 5 31970 10 10 10 7 7 51971 13 13 13 10 10 61972 16 16 16 12 12 81973 20 20 20 15 15 101974 23 23 23 17 17 121975 27 27 27 20 20 131976 30 30 30 23 23 151977 34 34 34 25 25 171978 38 38 38 28 28 191979 41 41 41 31 31 211980 45 45 45 34 34 231981 49 49 49 37 37 251982 53 53 53 40 40 271983 57 57 57 43 43 291984 61 61 61 46 46 311985 65 65 65 49 49 331986 70 70 70 52 52 351987 74 74 74 55 55 371988 78 78 78 59 59 391989 82 82 82 62 62 411990 86 86 86 65 65 431991 90 90 90 68 68 451992 94 94 94 71 71 471993 98 98 98 73 73 491994 102 102 102 76 76 511995 105 105 105 79 79 531996 109 109 109 81 81 541997 112 112 112 84 84 561998 115 115 115 87 87 581999 119 119 119 89 89 592000 122 122 122 92 92 612001 125 125 125 94 94 632002 129 129 129 96 96 642003 132 132 132 99 99 662004 146 146 146 109 109 732005 159 159 159 120 120 802006 173 173 173 130 130 872007 186 186 186 140 140 932008 200 200 200 150 150 1002009 212 212 212 159 159 1062010 225 225 225 169 169 112

Egypt - Tesfamichael and Mehanna 47Appendix Table A9: Composition of the total Egyptian fishery catch (in tonnes) in the Red Sea from 1950 to 2010.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 141950 682 0 8 414 292 190 296 0 359 774 178 311 118 3681951 692 0 9 427 294 201 305 0 365 782 183 316 122 3731952 702 0 9 438 296 212 313 0 372 791 188 322 125 3791953 713 0 10 449 298 224 321 0 379 801 192 327 128 3841954 725 0 11 459 300 235 328 0 386 811 197 333 131 3901955 737 0 11 468 303 246 335 0 393 822 201 340 134 3961956 739 0 6 238 305 128 170 0 367 834 102 318 68 4011957 784 0 38 1,547 308 856 1,105 0 560 846 663 478 442 4071958 799 0 41 1,631 310 926 1,165 0 583 858 699 497 466 4131959 812 0 43 1,637 313 953 1,169 0 595 870 702 507 468 4201960 795 0 23 853 2,629 508 609 0 480 871 365 413 244 4211961 833 0 52 1,892 3,756 1,156 1,351 0 651 880 811 554 541 4261962 893 0 97 3,483 7,616 2,180 2,488 0 922 894 1,493 778 995 4341963 949 0 143 4,999 7,368 3,204 3,571 0 1,191 904 2,142 1,000 1,428 4391964 1,293 395 479 6,443 2,524 4,227 4,602 0 1,459 912 2,761 1,221 1,841 4441965 1,290 333 441 6,544 2,163 4,394 4,674 0 1,515 942 2,805 1,267 1,870 4621966 1,257 413 428 4,040 2,634 2,776 2,886 0 1,089 926 1,732 916 1,154 4521967 1,985 1,490 1,209 3,631 1,144 2,552 2,593 0 1,006 862 1,556 846 1,037 4221968 2,351 1,951 1,537 3,238 1,448 2,328 2,313 0 966 900 1,388 811 925 4411969 2,721 2,412 1,866 2,861 1,752 2,103 2,044 0 928 942 1,226 778 817 4621970 3,105 2,872 2,194 2,500 2,058 1,879 1,786 0 892 990 1,072 747 714 4901971 3,719 3,705 2,797 2,194 2,593 1,685 1,567 0 848 996 940 708 627 4941972 3,535 3,400 2,603 3,001 2,399 2,356 2,144 0 1,027 1,002 1,286 853 857 4971973 1,554 758 613 1,564 707 1,254 1,117 0 747 1,007 670 619 447 5011974 4,017 4,080 3,066 1,870 2,837 1,532 1,336 0 825 1,011 801 680 534 5041975 3,119 2,724 2,159 4,215 1,969 3,527 3,010 0 1,346 1,016 1,806 1,108 1,204 5071976 4,993 5,291 4,040 4,013 3,613 3,429 2,867 0 1,324 1,015 1,720 1,087 1,147 5021977 4,256 4,302 3,291 3,344 2,982 2,918 2,389 0 1,198 1,022 1,433 980 956 5061978 4,106 4,101 3,134 3,021 2,853 2,690 2,158 0 1,144 1,025 1,295 932 863 5081979 5,340 5,789 4,355 2,507 3,937 2,279 1,791 0 1,045 1,033 1,075 848 716 5131980 3,975 3,907 2,987 2,847 2,731 2,465 2,033 0 1,217 1,034 1,220 1,012 813 5161981 4,172 1,788 3,154 3,021 3,365 2,964 2,158 0 1,109 1,045 1,295 1,005 863 5231982 5,153 2,579 4,154 2,388 3,560 2,399 1,706 0 1,100 1,041 1,023 717 682 5111983 6,437 5,177 5,448 2,254 5,356 2,195 1,610 0 1,029 1,027 966 881 644 5081984 7,856 7,169 6,841 1,874 1,452 1,065 1,339 3,171 1,083 1,054 803 1,204 536 5191985 5,830 5,012 4,783 1,784 1,086 1,224 1,274 2,217 1,081 1,058 764 1,130 510 5321986 4,906 4,021 3,864 2,378 917 2,661 1,699 1,779 1,041 1,060 1,019 968 679 5281987 5,641 4,796 4,603 2,000 1,050 1,843 1,429 2,122 1,048 1,061 857 1,094 572 5241988 6,819 6,058 5,780 1,718 1,264 1,023 1,227 2,680 1,333 1,061 736 1,108 491 5231989 9,030 8,460 7,972 1,732 1,673 695 1,237 3,742 1,844 1,059 742 1,148 495 5301990 9,136 8,568 8,060 1,426 1,690 424 1,018 3,790 1,585 1,055 611 1,186 407 5361991 7,880 7,241 6,845 1,461 1,463 799 1,044 3,203 1,251 1,049 626 1,184 417 5141992 7,840 7,278 6,830 1,853 1,468 1,242 1,324 3,219 1,509 1,041 794 1,144 529 5001993 9,571 9,087 8,545 1,596 1,773 697 1,140 4,019 1,543 1,031 684 1,174 456 5051994 6,044 5,240 5,027 1,312 1,116 538 937 2,318 1,220 1,021 562 1,011 375 4991995 5,920 5,280 4,993 1,433 1,101 1,134 1,023 2,335 1,033 923 614 872 409 4481996 5,240 4,457 4,238 1,357 978 1,172 969 1,971 993 998 581 921 388 4871997 5,770 4,953 4,769 1,455 1,060 1,184 1,039 2,191 1,000 986 623 926 416 4841998 4,982 4,162 4,015 1,182 920 992 844 1,841 925 964 507 692 338 4651999 4,055 3,279 3,137 1,213 760 1,073 866 1,450 966 918 520 670 347 4372000 6,351 5,804 5,501 1,078 1,171 902 770 2,567 915 833 462 672 308 3982001 4,981 4,216 4,074 1,222 913 1,064 873 1,865 1,011 891 524 672 349 4272002 5,336 4,721 4,524 1,442 975 1,481 1,030 2,088 1,013 778 618 586 412 3732003 5,026 4,388 4,228 1,553 913 1,445 1,109 1,941 1,141 758 665 633 444 3642004 5,239 4,728 4,439 1,423 969 1,352 1,017 2,091 1,092 746 610 925 407 3572005 3,279 2,520 2,418 1,455 604 1,448 1,039 1,114 1,065 798 624 953 416 3832006 3,418 2,541 2,566 1,239 603 1,256 885 1,124 896 777 531 633 354 3712007 3,645 2,760 2,813 1,192 633 1,280 851 1,221 870 741 511 578 340 3532008 4,230 3,316 3,347 1,284 737 1,426 917 1,467 951 787 550 657 367 3742009 4,325 3,433 3,465 1,306 748 1,476 933 1,519 963 745 560 656 373 3542010 3,971 3,079 3,107 1,150 686 1,324 821 1,362 925 735 493 612 329 349

1: Carangidae; 2: Etrumeus sadina; 3: Decapterus spp.; 4: Leiognathus berbis; 5: Sardinella spp.; 6: Synodontidae; 7: Champsodon capensis; 8: Scomber japonicus; 9: Lutjanidae; 10: Mugilidae; 11: Equulites elongatus; 12: Penaeidae; 13: Pseudorhombus arsius; 14: Sparidae

48Table A9 continuedYear 15 16 17 18 19 20 21 22 23 24 25 26 27 281950 79 0 32 67 55 15 170 39 39 0 136 22 28 201951 81 0 34 83 67 16 172 41 41 0 137 23 28 201952 83 0 36 98 80 17 174 42 42 0 139 24 29 211953 86 0 38 113 92 18 176 43 43 0 140 25 30 211954 87 0 40 128 104 19 178 44 44 0 142 26 31 221955 89 0 42 143 117 19 181 45 45 0 144 26 31 221956 45 0 22 127 104 10 183 23 23 118 146 20 16 111957 295 0 145 140 114 68 186 147 147 130 148 62 103 741958 311 0 157 152 124 73 188 155 155 141 150 66 109 781959 312 0 162 164 134 75 191 156 156 152 152 68 109 781960 162 0 86 176 144 40 191 81 81 204 153 42 57 411961 360 0 196 188 154 92 193 180 180 230 154 80 126 901962 663 0 370 201 164 173 196 332 332 233 157 140 232 1661963 952 0 543 213 173 254 199 476 476 252 158 199 333 2381964 1,227 93 717 225 183 335 211 614 614 278 160 259 430 3071965 1,247 78 746 294 240 348 216 623 623 0 165 269 436 3121966 770 97 471 249 203 220 214 385 385 332 162 175 269 1921967 692 351 433 261 213 202 228 346 346 625 151 161 242 1731968 617 460 397 274 225 184 249 308 308 530 158 148 216 1541969 545 568 362 286 238 167 270 272 272 414 165 136 191 1361970 476 677 326 369 308 149 293 238 238 0 173 124 167 1191971 418 873 296 384 323 133 316 209 209 0 175 112 146 1041972 572 801 412 400 338 187 309 286 286 0 176 151 200 1431973 298 179 228 415 353 99 241 149 149 0 176 88 104 741974 356 961 277 430 368 121 329 178 178 0 177 104 125 891975 803 642 618 445 383 279 294 401 401 0 178 219 281 2011976 764 1,247 605 371 325 271 361 382 382 364 178 214 268 1911977 637 1,014 520 383 338 231 337 319 319 368 179 184 223 1591978 575 966 485 395 351 213 332 288 288 387 180 171 201 1441979 478 1,364 418 408 363 180 379 239 239 383 181 147 167 1191980 542 921 555 406 342 171 329 271 271 437 181 152 190 1361981 575 754 478 496 380 174 242 288 288 409 183 206 201 1441982 455 925 400 399 496 288 255 227 227 451 182 141 159 1141983 429 1,516 428 364 306 142 319 215 215 418 180 147 150 1071984 357 457 388 358 338 108 232 179 179 343 185 242 125 891985 340 320 371 526 478 122 233 170 170 0 185 172 119 851986 453 256 329 448 418 183 233 226 226 0 186 148 159 1131987 381 306 223 388 372 223 233 191 191 0 186 214 133 951988 327 386 204 367 358 348 233 164 164 0 186 134 115 821989 330 540 182 482 455 322 233 165 165 0 186 146 115 821990 272 546 135 609 562 288 232 136 136 0 185 172 95 681991 278 462 168 319 328 338 230 139 139 0 184 147 97 701992 353 464 222 165 205 598 229 176 176 0 182 193 124 881993 304 580 199 311 327 482 227 152 152 0 181 251 106 761994 250 334 206 284 308 374 224 125 125 0 179 292 87 621995 273 337 353 210 250 456 203 136 136 521 162 204 96 681996 258 284 317 266 298 395 219 129 129 247 175 180 90 651997 277 316 497 314 340 365 216 139 139 292 173 162 97 691998 225 265 549 175 230 277 212 113 113 198 169 119 79 561999 231 209 615 81 155 311 202 116 116 236 161 136 81 582000 205 370 424 90 165 320 183 103 103 508 146 160 72 512001 233 269 471 119 191 366 196 116 116 228 156 186 81 582002 275 301 595 115 190 469 171 137 137 146 136 226 96 692003 296 280 666 111 189 546 167 148 148 434 133 269 104 742004 271 302 605 96 187 458 164 136 136 239 131 314 95 682005 277 161 614 122 219 469 175 139 139 151 140 316 97 692006 236 162 564 86 200 446 171 118 118 141 136 224 83 592007 227 176 582 65 193 362 163 113 113 63 130 183 79 572008 245 211 641 59 197 349 173 122 122 49 138 194 86 612009 249 219 668 61 209 362 164 124 124 70 130 200 87 622010 219 196 625 54 213 324 161 110 110 64 129 180 77 55

15: Charybdis hellerii; 16: Rastrelliger kanagurta; 17: Nemipteridae; 18: Epinephelus spp.; 19: Lethrinidae; 20: Mullidae; 21: Encrasicholina punctifer; 22: Clypeaster reticulatus; 23: Jacksonaster depressum; 24: Brachyura; 25: Siganidae; 26: Sepiidae; 27: Callyspongia monilata; 28: Pione vastifica

Egypt - Tesfamichael and Mehanna 49Table A9 continuedYear 29 30 31 32 33 34 35 36 37 38 39 40 41 42 431950 18 0 39 9 0 5 4 0 3 4 0 0 0 0 7601951 22 0 39 12 0 6 5 0 3 4 0 0 0 0 7811952 26 0 39 14 0 7 6 0 4 4 0 0 0 0 8021953 30 0 40 16 0 8 7 0 4 4 0 0 0 0 8221954 33 0 40 18 0 9 8 0 5 4 0 0 0 0 8421955 37 0 41 20 0 10 9 0 6 4 0 0 0 0 8621956 33 0 42 18 0 9 8 0 5 4 0 0 0 0 6031957 37 0 42 19 0 10 8 0 5 5 0 0 0 0 1,9191958 40 0 43 21 0 10 9 0 6 5 0 0 0 0 2,0141959 43 0 43 23 0 11 10 0 6 5 0 0 0 0 2,0301960 46 0 43 25 0 12 11 0 7 5 0 0 0 0 1,4501961 49 0 44 26 0 13 11 0 7 5 0 0 0 0 3,1351962 53 0 45 28 0 14 12 0 8 5 0 0 0 0 4,6601963 56 0 45 30 0 15 13 0 8 5 0 0 0 0 5,8641964 59 0 49 31 0 15 14 0 9 5 0 0 0 0 7,0381965 77 0 50 41 0 20 18 0 11 5 0 0 0 0 7,2321966 65 0 50 35 0 17 15 0 10 5 0 0 0 0 4,6211967 68 0 58 37 0 18 16 0 10 5 0 0 0 0 4,3621968 72 3 65 38 0 19 17 0 11 5 0 0 0 0 4,0361969 75 6 71 40 0 20 17 0 11 5 0 0 0 0 3,7241970 97 10 78 52 0 25 22 0 14 5 0 0 0 0 3,5171971 101 13 87 54 0 26 23 0 15 5 0 0 0 0 3,3261972 105 16 84 56 0 27 24 0 16 5 0 0 0 0 4,1471973 109 20 58 58 0 29 25 0 16 5 0 0 0 0 2,2981974 113 23 91 60 0 30 26 0 17 5 0 0 0 0 3,0831975 116 27 78 62 0 31 27 0 17 5 0 0 0 0 5,3981976 97 30 104 52 0 26 22 0 14 5 0 0 0 0 5,4401977 100 34 94 54 0 26 23 0 15 6 0 0 0 0 4,6121978 104 38 92 55 0 27 24 0 15 6 0 0 0 0 4,2561979 107 41 110 57 0 28 25 0 16 6 0 0 0 0 3,9481980 131 45 91 61 0 29 11 0 13 6 0 0 0 0 4,0761981 100 49 63 57 0 24 40 0 10 6 0 0 0 0 3,9601982 101 53 68 63 0 22 26 0 30 6 0 0 0 0 3,7651983 100 57 98 50 0 36 25 0 12 6 0 0 0 0 3,6201984 94 61 53 50 0 25 22 0 14 6 0 0 0 0 3,6241985 138 65 53 73 0 36 32 0 20 6 0 0 0 0 3,3431986 117 70 53 63 0 31 27 0 17 6 0 0 0 0 3,8361987 102 74 53 54 0 27 23 0 15 6 0 0 0 0 3,5311988 96 78 53 51 0 25 22 0 14 6 0 0 0 0 3,4131989 126 82 53 67 0 33 29 0 19 6 0 0 0 0 3,8331990 160 86 53 85 0 42 37 0 24 6 0 0 0 0 3,5501991 83 90 52 44 0 22 19 0 12 6 0 0 0 0 3,3121992 43 94 52 23 0 11 10 0 6 6 0 0 0 0 3,7221993 81 98 51 43 0 21 19 0 12 6 0 0 0 0 3,7521994 74 102 51 40 0 20 17 0 11 6 0 0 0 0 2,8441995 55 105 46 29 0 14 13 0 8 5 0 0 0 0 2,9211996 70 109 50 37 0 18 16 0 10 5 0 0 0 0 2,7161997 82 112 49 44 0 22 19 0 12 5 0 0 0 0 2,9101998 46 115 48 24 0 12 11 0 7 5 0 0 0 0 2,4711999 21 119 46 11 0 6 5 0 3 5 0 0 0 0 2,3722000 24 122 42 13 0 6 5 5 3 4 0 0 0 0 2,5982001 31 125 44 17 0 8 7 43 5 5 0 0 0 0 2,5312002 30 129 39 16 0 8 7 497 4 4 0 0 0 0 2,8692003 29 132 38 15 164 8 7 114 4 4 0 3 0 0 2,8972004 25 146 37 13 628 7 6 4 4 4 0 17 0 0 2,5082005 32 159 40 17 224 8 7 2 5 4 0 33 0 0 2,5152006 23 173 39 12 249 6 5 3 3 4 0 3 0 0 2,3242007 17 212 37 9 326 4 4 0 3 4 21 1 11 0 2,3052008 15 224 39 8 101 4 4 2 2 4 26 0 2 0 2,5082009 16 241 37 8 178 4 4 0 2 4 19 1 3 3 2,5592010 14 253 37 8 153 4 3 0 2 4 14 1 2 6 2,321

29: Lethrinus mahsena; 30: Serranidae; 31: Sphyraena spp.; 32: Scaridae; 33: Argyrops spinifer; 34: Scomberomorus commerson; 35: Euthynnus affinis; 36: Holothuroidea; 37: Elasmobranchii; 38: Sciaenidae; 39: Variola louti; 40: Panulirus; 41: Epinephelus tauvina; 42: Lethrinus borbonicus; 43: Others

50

Sudan - Tesfamichael and Elawad 51

reConstruCting red sea fisheries of sudan: foreign aid and fisheries1

Dawit Tesfamichaela,b, Abdalla Nassir Elawadc

a Sea Around Us, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada

b Department of Marine Sciences, University of Asmara, Asmara, Eritrea.c Fisheries Research Center, Port Sudan, Sudan

d.tesfamichael @fisheries.ubc.ca; al_awad2002 @hotmail.com

abstraCt

The fisheries catch in the Red Sea Exclusive Economic Zone (EEZ) of Sudan was reconstructed from 1950 to 2010, by major fisheries and taxa. Published papers, reports and interviews were used as a base for the reconstruction. For the years where data were missing, interpolations or extrapolations were made using assumptions based on current knowledge of the fisheries. The results showed that Sudanese fisheries went through major shifts. The catches were about 2,000 t·year-1 in the 1950s, remained low, and took off at the end of 1970s, mainly due to development projects aided by foreign organizations, which led to a massive increase in artisanal fishing effort, and ultimately, to catches of more than 5,000 t·year-1 in the 2000s. The fisheries also shifted from being dominated by a shellfish fishery in the early years to being dominated by an artisanal finfish fishery in the later years. The number of species or species groups with major contribution to the total catch is higher in the latter years. The contribution of the industrial fishery is generally low. The reconstructed catch is higher than the catch reported by the Food and Agriculture Organization of the United Nations (FAO) on behalf of Sudan in the early years. However, in later years, the opposite seems to occur, i.e., the catch by FAO is higher than the reconstructed catch. This was deemed to be due to over reporting by Sudan.

introduCtion

Sudan borders the Red Sea (Figure 1) and its shore is characterized by a relatively narrow shelf (as compared to other Red Sea countries) of about 4,000 km2. Overall, Sudanese waters are deep; indeed, the deepest part of the Red Sea, about 3,040 m, is off Port Sudan. Inlets, or ‘marsas’ in Arabic, are common on the coast, and have deep narrow entrances with shallow fringing coral reefs, which drop rapidly to greater depth. These inlets are used as shelters by the artisanal fishers. They sail from their bases, usually in bigger ports and human settlements, to the inlets which they use as fishing camps, from which they venture out to the open water to fish. Sometimes, they stay in the inlets for months and their catches are collected by trucks on dirt roads. About half a mile from the shore, there are what are commonly referred to as ‘boat channels’. They are relatively shallow, up to 6 m deep, and are the navigation routes of local fishing boats. The boat channels are bordered by fringing reefs, which are an important area for fishing mainly by the small boats. Fringing reefs separate the shallow boat channels from the deep channels, which are from 80 to 400 m deep. They are the migratory routes of some fishes and some fishing takes place in those areas as well. Offshore from the deep channel is the barrier reef, about 3 – 6 nautical miles from shore, with most of the artisanal fishery catch originating from this area. Most of the commercially important coral reef species, which are the target of the hand line fishery, are found in the barrier reef area. Handlining is the main fishing technique of the artisanal fishery for finfish in Sudan (Barrania 1979; Vine and Vine 1980).1 Cite as: Tesfamichael, D. and Ekawad, A.N. (2012) Reconstructing Red Sea fisheries of Sudan: foreign aid and fisheries. pp. 51-70. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosysytem by countries (1950-2010). Fisheries Centre Research Reports 20(1). Fisheries Centre, University of British Columbia [ISSN 1198-6727].

Figure 1. The Red Sea coast of Sudan, its Exclusive Economic Zone (EEZ) and shelf waters to 200 m depth.

52

A prominent feature of the Sudanese coast is the extensive reef development, one of the most developed reef structures in the Red Sea. The fringing reefs, which are cut off by inlet channels are common, and the barrier reef is virtually continuous along the coast. The Sudanese coast also boasts the famous Sengenab Atoll, the only atoll in the Red Sea. It has very high biodiversity and has been nominated as a UNESCO world heritage sites. In addition, Rumi reef (‘She’ab Rumi’ in Arabic), was the site Jacques-Yves Cousteau chose for his Oscar award-winning documentary ‘World without Sun’, where an underwater house was built and the life in and around the underwater habitat of several ‘oceanauts’ was documented for one month.

Despite the high biodiversity in the Sudanese waters, the fish catch is not high and more than 95% of the fish supply of Sudan originates from inland waters, i.e., the Nile river, lakes and dams (Chakraborty 1983; Tesfamichael and Pitcher 2006). Most marine fishing in Sudan is handlining using different kinds of boats. Common are dugout canoes of 2 – 3 m that take 1 – 2 fishers using paddles (or sometimes sail) to fish in the inlets and behind the fringing reef. They are also very important for shell collection (see below). Other common boat types are huries of 3 – 5 m, and used mainly for handlining along the fringing reefs and in deeper waters just off the reefs. They can take 2 – 3 fishers and usually have sail and paddles. Bigger than huries are the rare felukas of 5 – 7 m length, which unlike the huries, are fitted with transom stern and usually have sail. Both huries and felukas are sometimes equipped with outboard engine of 3 – 8 hp (huries) and 10 – 12 hp (felukas). The biggest boat types used by Sudanese fishers are launches, which range from 7 to 11 m and are usually fitted with an inboard engine of 30 – 100 hp. They are used for handlining further offshore. They are also used, albeit to a lesser extent, in gillnet fishing. The length of a single trip is proportional to the size of the boats. Canoes and huries usually spend a single day per trip, while launches can spend up to 6 days (MEPI 1993).

There are many fish landing sites along the Sudanese coast; the most important ones are Abu Hashish, Salobona and Khor Kilab (the last not used much anymore) around Port Sudan; Mohammed Qol in the north and Suakin in the south. The main fish market is in Port Sudan. Suakin has better facilities to deliver fish to Port Sudan, and is also closer (Figure 1). Fish from the Red Sea is usually consumed on the coast, i.e., do not supply the inland markets, where the population concentration is higher. This is mainly due to poor transportation facilities, and the fact that fresh water catches tend to cover the demand of the inland population. Sometimes, a small portion of fish caught by artisanal fishers is exported to neighboring countries such as Saudi Arabia and Egypt. In addition to the artisanal fishers, trawlers (and to a lesser extent purse seiners) from foreign countries operate in Sudanese waters.

Prior to the prominence of finfish in catches; shells were, for centuries, the main target in Sudan (MEPI 1993), which was a major exporter of shell (Eltayeb 2004). The shells collected were mainly trochus and mother-of-pearl. Though the catch of the former was much larger, the latter had greater economic importance as its unit price was quite high. Sudan was important for shell fisheries of the whole Red Sea in the 1950s and 1960s, and fishers would come from all countries in the region, including from as far as Somalia and Yemen to land their catch. More than half, and sometimes up to 90%, of the shells landed in Sudan used to come from other neighboring countries (Kristjonsson 1956; Reed 1962). The fishers were sea nomads, who used to land their catches in either Port Sudan or Suakin, though they also used Massawa, Eritrea or Jeddah, Saudi Arabia, when they received better prices and marketing conditions. They would sail for days for a small difference in price. Because they were using sails, it did not cost them much to sail from one port to another (Reed 1962). However, in the 1970s, marketing in Sudan became difficult for foreigners, and the importance of that country as a destination for shell collectors declined (Eltayeb 2004).

The fishery for finfish started to gain momentum after mass mortality of shells in 1969; and many of the shell fishers converted to finfish through various development projects (Barrania 1979). Two major projects had important influences on Sudanese fisheries. One was run by the British Overseas Development Agency (ODA) from 1975 to 1990, targeting the southern part of Sudan (around Suakin). The main aim was to motorize the sailing boats of the artisanal fishers and to enhance the infrastructure at the landing site by providing storage and workshops (ODA 1983). The second important project was an FAO/UNDP project (1979 – 1985), which emphasized the northern part of Sudan, around Mohammed Qol and Dungunab, where the shell industry faced a major crisis. The objective was to organize the fishers into cooperatives so that they could access technical and financial facilities (Barrania 1985). The Canadian International Development Agency (CIDA) was also involved in shell fish culture research. These projects changed the landscape of Sudanese fisheries, especially the artisanal sector.

In this report, the catch of the major Sudanese fisheries are reconstructed from 1950 to 2010. The major fishery sectors were treated separately and a few minor fisheries were also examined. The catch compositions of the different fisheries were then calculated. First, we introduce the fisheries with respect to their operation, the fish they target and their marketing. Then, we explain the methodology of the reconstruction, followed by results and a discussion.

Artisanal finfish fishery

The two major sectors of the artisanal fisheries are shell collection, which is treated separately in this report, and the finfish fishery, which is the main artisanal fishery and sometimes referred as ‘the artisanal fishery’. Until recently, the artisanal fishery mainly operated dugout canoes in the shallow waters near the shore, using handlining, which accounts for up to 80% of the fish caught (Kristjonsson 1956; MEPI 1993). The fishers target carnivorous fishes in rocky grounds or near coral reefs up to 200 m deep using stones as sinkers, which are tied in such a way that they are released by jerking the line when it gets to a suitable depth. Knowing the right depth for releasing the sinker is gained through experience. In the past, fishing trips would be single day-trips using sail-power and no ice was used, because it was expensive and the fish did not need to be held more than a few hours as the fishers could get a reasonably good catch in a single day. The fish commonly caught were groupers (Serranidae), snappers (Lutjanidae), emperors (Lethrinidae), jacks (Carangidae), and sharks (Elasmobranchii). Most of the catch was consumed within

Sudan - Tesfamichael and Elawad 53

Sudan and a large fraction of the catch was delivered to Port Sudan by trucks owned by merchants, only a small portion is consumed locally. Mullet (Mugilidae) catch used to be salted in barrels, locally called ‘fissik’ and exported to Egypt, lately some is consumed locally. Until the end of the 1960s, the traditional artisanal fishery was shell collection. However, in 1969 there was a mass mortality of shells in Sudan and most of the fishers that were active in shell fishery switched to finfish fishing or other activities such as farming and trading.

Artisanal invertebrate fishery

The artisanal invertebrate fishery in Sudan includes collection of shells in shallow waters and diving in deeper waters, for example for sea cucumber. Shell collection has a very long tradition in Sudan, where shell middens can be found all over the coast and on the islands. One oyster midden, estimated to consist of 3,000 t of shells, was found by radioactive dating to be 1,500 years old (MEPI 1993). In the contemporary history of Sudanese artisanal fishery, shell collection was dominant and the tradition continued until the end of the 1960s. However, most fishers previously active in the shell fishery switched to finfish fishing or other activities after the mass mortality of shells in the late 1960s. The major shells collected in Sudan are mother-of-pearl (Pinctada spp.) and trochus (Trochus spp.). Dungunab Bay, in the northern part of Sudanese Red Sea coast, is famous for its mother-of-pearl oysters.

Shells are collected by skin diving in shallow waters (down to 10 m). In the past, trips were usually done by bigger sambuks with 6 – 8 crew. When they reached a protected bay (marsa), they would anchor the sambuk; the divers then would take the huries they carried onboard to the diving sites and brought back their catch. Shell collection consisted of drifting with the huries over the shell beds, while monitoring the sea floor with a glass-bottomed bucket. The fisher then dove when they spotted oysters (Kristjonsson 1956). Huries with sail and motorized launches were also used to sail to the fishing ground. Some shells were collected by walking in the shallow waters near settlements. In the past, the fishers hardly used any snorkeling equipment for shell collection, but later, they started using masks, snorkels and flippers. The fishing season is the warm summer months. The season usually started around April but the main activity occurs between July and November, when the water is warm, clam and thus provides better visibility. There was no shell collection from January to March and the fishers switched to finfish fishing or other activities such as farming or trading (MEPI 1993).

The most important species in the shell fishery are black lip mother-of-pearl oyster Pinctada margaritifera var. erythreaensis and Trochus dentatus, in Arabic ‘sedaf’ and ‘kokian’, respectively (Reed 1962). Centuries ago, oysters were collected mainly for their pearl. Later, oyster shells started to be exported to Europe for the manufacturing of fancy buttons, inlay work, jewelry and artifacts. A small proportion is used locally for poultry feed as a source of calcium. Trochus is also exported for production of small buttons. Oysters and trochus were also used for making plaster, used for whitening walls. However, because it was very expensive, it is now abandoned; instead fossilized corals and other shells are used. Other mollusks are collected either for their meat and/or their opercula. The sun dried meat of mainly conchs (Family Strombidae, specifically Stombus spp. and Lambis spp.), locally called ’surumbak’, is consumed locally and some of it used to be exported to Saudi Arabia. The nail (opercula) of conchs and other gastropods such as Fasciolaria spp. locally called ‘tsifri’ were also collected to be used as fixatives in the local production of perfumes (MEPI 1993).

Sea cucumber has been collected for export to Asian markets. Fishers started collecting sea cucumbers in shallow waters, and later moved to deeper water using skin diving. As those resources started to get scarce, SCUBA diving was introduced, and finally, fishers used boat hookah diving with compressors onboard so that they can stay longer in the water to collect more sea cucumbers. Some of these practices did not have enough safety measures and training and many serious accidents occurred. Once the sea cucumbers are collected, they are usually boiled and dried for export to Asian markets. The local fishers sometimes fish for shrimp in the shallow lagoons using cast net (Elnaiem 2002).

Subsistence fishery

The definition of subsistence fisheries may vary. FAO defines it as “a fishery where the fish caught are consumed directly by the families of the fishers rather than being bought by middle-(wo)men and sold at the next larger market”.2 For the purpose of this research, in line with the FAO definition, we considered catch that is consumed by the crew, given to family, friends and part of the community who need the support (e.g., widows) as part of the subsistence fishery. In Sudan, like other Red Sea countries, it is a common practice for fishers to share part of their catch with the community before they land their catch. This portion of the catch is significant, sometimes half of the total catch, and never gets reported. It is a social obligation for everyone to do their duty and not contributing has social consequences. The part of the catch that is given freely to the community is the fish that is not directed for export, such as shark fins.

Industrial fishery

Only a small fraction, about 700 km2, of the narrow continental shelf along the Sudanese coast, which is dominated by coral reefs, is suitable for bottom trawling (Sanders and Kedidi 1981). Most of this is in the southern part of the coast, including the Toker Delta. The Gulf of Agig, on the border with Eritrea, is also frequently visited by trawlers. The earliest trawling survey to explore trawl suitable grounds started intermittently in the late 1950s and the early 2 http://www.fao.org/docrep/003/X2465E/x2465e0h.htm

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1960s (Reed 1962). On the other hand, the more concerted surveys performed from 1976 to 1981 by ODA and private companies ushered the beginning of commercial trawling operation in the early 1980s. Since the beginning, trawling has been undertaken by foreign companies from Egypt, China and others, targeting shrimp and some fish. Although trawling is done during the day and at night, the catch is found to be higher at night between 8 pm and 4 am (Elnaiem 2002). The shrimp catch usually accounts for only 3 – 10% of the total catch, and most of the bycatch ends up discarded at sea (Elawad 2002; Elnaiem 2002).

Purse seining is another industrial fishery that operates in Sudan, but less common than trawling. The main fishing areas are in the northern part of the Sudanese coast in and around the area disputed with Egypt (Figure 1), where Egyptian purse seiners have been fishing for decades without any permit from Sudan, which hardly has any fishing activities of its own in the area (MEPI 1993). Starting in 2002, purse seiners from Egypt started fishing in the southern part of the Sudanese coast with permits. All their catch was landed in Egypt.

materials and methods

Published papers, technical reports, government reports, archives, theses and research reports were searched for data and information on Sudanese marine fisheries. Early reports, from the mid-1950s to the late 1980s were authored mainly by FAO personnel who visited the country as expert advisors. The ODA project reports also provided some valuable information for the 1970s and 1980s. Information referring to later periods (after 1990) was available mainly from local reports and files of the Fisheries Administration in Port Sudan (FA 2007, 2012). On-site interviews were also carried out by the first author in 2007 to fill in information gaps (Tesfamichael et al. in press). Where information was not available at all, interpolation was used to estimate the catch given the best knowledge available at the time of the research. Since different procedures were used for the different fishery sectors, the method for each fishery is given separately.

Artisanal finfish fishery

According to reports and the Fisheries Administration of Sudan, the small-scale finfish fisheries are divided into artisanal and semi-industrial. The main difference is that the former uses smaller boats and usually no motors, while the latter uses engines and larger boats. For the purpose of this research, they are all considered part of the artisanal fishery (the shell fishery is treated separately).

Kristjonsson (1956) was the first to publish an estimate of Sudanese finfish catch, i.e., 300 t∙year-1. At the time, this fishery was mainly for local consumption and to supply a small market in Port Sudan. This estimate was later adopted by Oswald (1958) and Reed (1962). In the 1950s and 1960s, Sudanese fishers were more interested in shell collection than finfish fishing, as there was a lucrative market for shells. However, this changed in 1969 when a massive mortality of shell fish occurred. Thus, the estimate of 300 t∙year-1 is used here as the total catch of artisanal fishery from 1950 to 1969. The next catch estimates were from Barrania (1979), who quantified the annual amount of fish sold in the fish market of Port Sudan from 1975 to 1978. A later survey showed that about half of the fish consumed in Port Sudan did not go through the formal market channel; in addition, 300 t of fish were consumed every year outside Port Sudan (Chakraborty 1983). So, to estimate the total annual catch of the artisanal fishery from 1975 to 1978, the amount of fish sold in Port Sudan market is multiplied by two and 300 t added to it. An independent detailed fishing effort and catch survey for 1976 along the Sudanese coast was published by ODA (1983). The ODA estimate, 671 t for 1976, was higher than the one calculated using the data of Barrania (1979) and the method described above, i.e., 609 t. Thus the total catches for all years calculated using Barrania (1979) data from 1975 to 1978 were corrected using the ODA survey (Table 1). Catch estimates from 1970 to 1974 were interpolated so as to reflect the slight increase in total catch as fishers moved from shell collection to finfish fishery.

The Fisheries Hydrobiological Administration of Sudan (FHAS 1984) reported Sudanese catch for 1979 and 1980 using Port Sudan reported catch and the procedure described above, while Chakraborty (1983) also estimated catch for 1979, which was similar to FHAS estimate. The FHAS (1984) data were used here because they provided more details on the data collection procedure, including the taxonomic composition of the catch.

For the years 1981 – 1983, a number of catch estimates were published by the experts and consultants hired by the ODA and FAO/UNDP projects. The estimates of Chakraborty (1983) were obtained using the reported catch of Port Sudan. Kedidi (1984) based his estimate on effort data (number of fishers for 1981 and number of boats for 1982 and 1983), multiplied by the catch per unit of effort taken from a sample of boats, and ODA (1983) based their estimate on a survey of fishing villages for 1981 and the number of full time and part time fishers for 1982 (Table 2). The ODA estimates were used for 1981 and 1982, while Kedidi’s estimate was used for 1983. These data points were chosen because they provided details that were missing from the other reports.

Table 1. Sources and adjustment to estimate the Sudanese artisanal finfish fishery catch (tonnes) from 1975 to 1978.

Year Port Sudan(Barrania 1979)

Total catch(Port Sudan *2 + 300 t)

ODA (1983)survey data

Total, adjustedto ODA survey

1975 56.2 412.4 - 454.21976 154.6 609.2 671 671.01977 135.3 570.6 - 628.51978 148.3 596.6 - 657.1

Table 2. Estimates of total catches (tonnes) of Sudanese artisanal finfish fishery by different authors from 1981 to 1983; the bold values are the ones used here.

Year Chakraborty (1983) ODA (1983) Kedidi (1984)1981 1050 1628 11021982 1109 1441 11911983 1167 - 1443

Sudan - Tesfamichael and Elawad 55

Data for 1984 and 1989 were available from MEPI (1993). Again, the total catch was calculated using Port Sudan reported catch multiplied by two and adding 300 to it. However, the estimate of 300 t∙year-1 for fish consumed outside Port Sudan used in the 1970s calculation, which was still being used in the 1980s and 1990s, was here assumed to change with increase in population size. Thus, we assumed it to be 300 t∙year-1 in 1980; for the other years, this figure was increased based on the ratio of population of the respective year to the population of 1980. Data from 1985 to 1988 were interpolated (Figure 2). From 1990 to 2010, catch data of fish sold in the Port Sudan market were compiled by the authors from the files of the Fisheries Administration (FA 2007, 2012) in Port Sudan. Those values were multiplied by two and the catch consumed outside Port Sudan was added based on the population size adjustment outlined above (Figure 2).

There was a mullet fishery using veranda nets by Egyptian fishers along the Sudanese coast all the way south to the Eritrean waters, which caught an estimated 1,000 t·year-1 (Sanders and Morgan 1989). The fish were salted in barrels, producing what is locally called ‘fissik’. According to records and experts from the Fisheries Administration in Port Sudan, this fishery existed only from 1986 to 1991 and was experimental. There were about 4 – 6 boats operating only 4 months per year. It is believed the 1,000 t·year-1 is an over estimate for the Sudanese coast, partly because the fishers were fishing all over the Red Sea. Thus the annual 1,000 t was not used for Sudan, instead the annual average catch was calculated taking the average of 5 boats operating 4 months and a catch per day of half a tonne, resulting in 300 t·year-1, which was added to the totals of 1986 – 1991. Figure (3) shows the summary of the sources and procedures of the reconstructed catch of the Sudanese Red Sea artisanal fishery compiled for the whole period studied, 1950 – 2010.

The catch of the artisanal fishery consists of many species; however, only a few are dominant. Different authors estimated the catch composition and their percentages were used to calculate the catch composition of the reconstructed total catch (Table 3). In some cases, data from a single year was used to calculate the catch compositions for a longer period. For example, Barrania (1979) estimated the catch composition for 1978, which was used for the period 1950 – 1978. Data files from the Fisheries Administration, Port Sudan office (FA 2007) provided the composition of the fish landed in Port Sudan for 2006 and were used for 1990 – 2010. For 1981 – 1982, the weighted average of 1979 – 1980 was used. For the calculated total catch composition 300 t·year-1 of mullet was added from 1986 to 1991. The blue-spotted sea bass reported in Chakraborty (1984) for 1983 was lumped together with the grouper category.

Table 3. Sudanese artisanal finfish fishery catch composition percentages, 1950–2010. Period Groupers Snappers Emperors Jacks Sharks Mullets Unicorns Others Source1950-78 30.11 23.26 13.54 7.65 5.10 7.81 2.55 10.00 Barrania (1979)1979 19.86 27.91 14.25 6.06 8.59 10.31 3.02 10.00 FHAS (1984)1980 27.71 22.57 19.17 6.12 6.20 7.09 1.13 10.00 FHAS (1984)1981-82 24.13 25.03 16.93 6.10 7.26 8.57 1.99 10.00 Calculated*1983 47.07 17.76 25.17 0.00 0.00 0.00 0.00 10.00 Chakraborty (1984)1984-89 20.58 32.28 17.22 11.03 2.70 5.11 1.08 10.00 MEPI (1993)1990-10 19.95 15.09 14.65 7.33 7.88 25.10 0.00 10.00 FA (2007)* Weighted mean of 1979 and 1980

Figure 3. Catch reconstruction of the artisanal finfish fishery of Sudan. The values until 1969 (the star) are assumed values, after 1969 it is interpolated between 1969 and 1975. The stars in 1985 and 1986 represent the addition of mullet to total catch (see Figure (2) and text).

Figure 2. Sources and procedure for reconstructing artisanal finfish fishery catch of Sudan from 1984 to 2010. The stars in 1985 and 1986 indicate the addition of 300 t of mullet to the total catch starting 1986 (see text).

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Figure (4) shows the reconstructed catch composition of the Sudanese artisanal finfish fishery (see Appendix Table A1). All the catch composition figures presented here are after the adjustment and comparison procedure described above were carried out. The taxa represented in the figures are only the dominant ones for better representation; therefore, the list of taxa in the catch composition may be bigger than the taxa in the figure. Expanded tables of catch composition data are given in the appendix.

Artisanal invertebrate fishery

The trochus shells landed in Sudan were almost exclusively destined for export; as a result, reliable records were available starting in the early 20th century. Export data were available for 1950 – 1961 (Reed 1962), 1966 – 1989 (MEPI 1993), 1992 – 2002 (Eltayeb 2004), 2003 – 2006 (FA 2010) and 2007 – 2010 (FA 2012). Not all shells that were landed were exported; some of them were discarded simply because the shells lost their nacreous layer making them unsuited for export (Eltayeb 1999). Data of landed and export amounts were available from 1997 to 1999 (Eltayeb 1999) and the average discarded amount was 42.5% of the exported shell weight. This ratio was used to scale up the export amount to total landing. There was no export of trochus in 1990 and 1991 (Eltayeb 1999). However, MEIP (1993) reported a total catch of 114.8 t annually for the early 1990s, and this value was used for 1990 and 1991. Data were not available from 1962 to 1965 and an interpolation was used to fill in the gap (Figure 5).

The oyster fishery in Sudan was also almost exclusively for export, thus records existed starting in the early 20th century. Data were available from 1950 to 1961 (Reed 1962), while MEPI (1993) had export data for 1966 – 1979, 1984, 1987, 1989 and 1992. Records from the Fisheries Administration indicated a catch of 1 t for 2003, and none thereafter (FA 2010, 2012). Reed (1962) reported that the fishers could not tell if the oyster they picked was large enough for the export market. Thus, about 20% of the oysters collected were undersize and they had to be discarded at sea, with many eventually dying. Later, a method was introduced for planting the small oysters in wired trays to grow them until they were large enough for the market. We assumed that about half of the 20% undersized oysters died. So, 10% was added to the export value to calculate the total catch of oysters. For the years data were not available, interpolation was applied to estimate the catch (Figure 6).

There were few data points for the export of dried sea cucumber: MEPI (1993) reported 15 t in 1981, and FA (2007) 10 t and 3 t for 1985 and 1986, respectively. A continuous dataset was also available from 2001 to 2010 from the files of the Fisheries Administration of Sudan in Port Sudan (FA 2012). These values were converted to wet weight based on dry weight corresponding to 10% of wet weight (Tesfamichael and Mohamud 2012). The estimates from 1982 to 1984, and from 1987 to 2000 were interpolated. From 1950 to 1980, we assumed a catch of 27 t·year-1, the lowest of available data points (Figure 7). There was only one data point for the sun dried meat of conchs (Strombus spp. and Lambis spp. of family Strombidae), locally called ‘surumbak’ for 1992 from MEPI (1993), which estimated the annual total catch to be 44 t. In the absence of other data points and in the knowledge that this activity has been going on for a long time, this estimate is assumed to be the annual value from 1950 to 2010. Similarly, only one data point was available for the opercula of gastropods for 1992, i.e., 0.55 t (MEPI 1993). This was rounded to 1 t and assumed as the annual value from 1950 to 2010.

Figure 6. Catch reconstruction of the oyster shell fishery of Sudan, 1950–2010.

Figure 5. Catch reconstruction of the trochus shell fishery of Sudan, 1950-2010.

Figure 4. Catch composition of the artisanal finfish fishery of Sudan, 1950 - 2010.

Sudan - Tesfamichael and Elawad 57

Subsistence fishery

The total catch and composition of the subsistence fishery was calculated based on the information and knowledge obtained through the reconstruction of the finfish artisanal fishery. Data on the artisanal shell and shark fisheries were not included, because they are exclusively for export, hence it does not satisfy our definition of a subsistence fishery, which is catch given freely to family and friends and does not get recorded. To estimate the extent of the subsistence fishery, the time line of the artisanal fishery was divided into two periods, 1950-1979 and 1980-2010, based on the motorization of boats, which even if started earlier (Barrania 1979), accelerated in 1980 (Chakraborty 1983). We assumed the subsistence fishery to be 30% of the artisanal fishery from 1950 to 1979. This is a reasonably conservative estimate, because interviews with fishers indicated that before motorization and strong commercialization of fishery, they used to give up to half of their catch to family and friends. Once motorization accelerated, we assumed 20% of the artisanal fishery to be subsistence, and by 2010 we assumed this had declined to 10%. The ratio of subsistence was interpolated from 1980 to 2010. The catch composition of artisanal fishery was used to calculate the composition of subsistence fishery, except sharks and rays were excluded because they are mainly for export markets (Figure 8, Table A2).

Industrial fishery

The earliest report of industrial fishery was documented by Reed (1962) for exploratory trawling for shrimp during his assignment in Sudan from 1958 to 1961. The trials were sporadic and aimed to identify trawling grounds. He reported best catches of up to 100 individual shrimp per hour at night, with lower values during daytime. The next trawling surveys were conducted by ODA in 1976 and 1981 (ODA 1983), which we used as data anchor points. The 1976 shrimp catch was 14.7 t, with 114.5 t of discards, while in 1981, the shrimp catch was 26 t and retained fish catch was 13 t. Although the main target of trawling at the time was shrimp, some fish were kept for the local market. The fish catch for 1976 was not available and was estimated using the shrimp-fish ratio for 1981, while the discard for 1981 was calculated using the shrimp discard ratio of 1976. From 1977 to 1980, data were not available for trawling. However, Sanders and Morgan (1989) reported that a company called Ross Sea Food International was doing exploratory trawling in 1978 and 1979, and estimated the potential catch of shrimp from the Sudanese coast to be 30 t·year-1; however, their actual catch during the operation was not reported. Thus, the catches for 1978 and 1979 were interpolated using the data for 1976 and 1981 as anchors. Ross Sea Food International abandoned their operation when they concluded that the 30 t·year-1 shrimp potential was not worthwhile for a commercial venture. The catches in 1977 and 1980 were set to zero as there were no trawling activities reported for those years (ODA 1983; Sanders and Morgan 1989). Starting in the early 1980s, Sudan started issuing trawling permits to foreign vessels, mainly from Egypt (MEPI 1993). The annual catch from 1982 to 1984 was estimated based on Elawad (2002), who reported the minimum trawling total catch, including discards, from 1979 to 2000 was 90 t∙year-1. This value was assumed until 1984. The next reference available was for 1990, the last year the Egyptian trawlers operated before they were stopped for a few years. There were, however, a few other trawlers operating in Sudan. The total catch for 1990 was 544.2 t (MEPI 1993; Elawad 2002). The total catches from 1985 to 1989 were interpolated to depict the increase in the trawling activity during those years. The catch declined to 137 t·year-1 in 1991 (MEPI 1993). The next data reference was for 1998, being 290 t (Elawad 2002), when a special permit was given for trawling for Egyptian vessels. The catch from 1992 to 1997 was kept constant at the level of catch in 1991. Catches for 1999, 2002 – 2010 were available from the files of Fisheries Administration and Fisheries Research Centre (FA 2007, 2012). Catches for 2000 and 2001 were interpolated (Figure 9).

Figure 8. Catch composition of the subsistence fishery of Sudan, 1950-2010.

Figure 7. Catch reconstruction of Sudanese sea cucumber fishery in the Red Sea; the star at 1980 indicates the end of the assumed values from 1950 to 1980 (see text).

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The catch composition of the trawl catch in 2004 was taken from files of the Fisheries Administration (FA 2007), i.e., 5% shrimp (Penaeidae), 27% lizard fish (Saurida spp.), 7% threadfin bream (Nemipterus spp.), 4% goatfish (Mullidae) and 57% discards. These ratios were used from 1982 to 2006. From 1976 to 1981, the catches of shrimp, all fish and discard were calculated as mentioned in the previous paragraph. The shrimp catch and discard were used directly in the catch composition, while the fish total was divided according to the fish ratios from 2004 (Figure 10, Table A3). The main shrimp species were deep-water species, i.e., Penaeus semisulcatus, Metapenaeus monoceros and Melicertus latisulcatus, which contributed more than 90% of the catch. For coastal lagoon, which contributed less to the total catch, P. monodon and P. indicus were the only species reported (Elnaiem 2002). The composition of the discarded catch was calculated according to data from Yemen (Tesfamichael et al. 2012b), since trawl operations are similar between the two countries (Figure 11; Table A4).

The purse seine fishery in Sudan started in 2002 by vessels from Egypt. Data were available for the total catch and catch composition from 2002 to 2005 (FA 2007) and from 2006 to 2010 (FA 2012) from the Fishery Administration in Port Sudan. This fishery is assumed to not generate any discards. In addition, as a relatively limited and controlled fishery, there is good data recording system; hence the values were used as they were (Figure 12, Table A5).

Comparing reconstructed catches with FAO data

The reconstructed catches were compared to the composition of Sudanese catch in the FAO data (www .fao.org/fishery/statistics/software/fishstat/en). Annual catches are reported for Sudan in the FAO database. From 1950 to 1997, all the catch data are given as ‘Marine fishes nei’ without compositional breakdown. From 1998 to 2010, the two taxa ‘narrow-barred Spanish mackerel’ and ‘sharks, rays, skates etc. nei’ are represented separately and the rest lumped as ‘Marine fishes nei’. The FAO data for Sudan were not refined enough to provide information about any of the fisheries.

The taxonomic group ‘others’ in the reconstructed catch, which includes the miscellaneous taxa not reported separately, was very high for some years. It was first reduced to 10% of the total catch, and the difference was distributed to the previously identified taxa in proportion to their reported percentage except ‘sharks’. The procedure was needed because when the unidentified group ‘others’ assumes high proportion of the total catch, the resolution of the catch is not very informative. The group ‘sharks’ was excluded because it was reported separately in the FAO data. Then the FAO category ‘marine fishes nei’ was disaggregated further using the ratios in the reconstructed catch, again after excluding ‘narrow-barred Spanish mackerel’ and ‘sharks’. Finally, each taxon in the reconstructed catch was compared to the FAO data to calculate misreporting. The part of the reconstructed catch that is accounted in the FAO data is referred to as ‘reported catch’ in our result. If the value of a taxon in the reconstructed catch was higher than its value in the FAO data, then the difference was labeled as ‘unreported catch’, and if the FAO value for a taxon was higher than the reconstructed catch, the difference is over-reported catch.

Figure 10. Composition of the retained catch of trawl fishery in the EEZ of Sudan, 1950 - 2010.

Figure 11. Composition of the discarded catch of trawl fishery in the EEZ of Sudan, 1950-2010.

Figure 9. Catch reconstruction of the trawl fishery in the EEZ of Sudan, 1950 - 2010. The stars (1978 and 1979) represent interpolations line between 1976 and 1981. The star in 1997 represents the end of the assumed value from 1991 to 1997.

Sudan - Tesfamichael and Elawad 59

results

The reconstructed total catch of all the fisheries in the Sudanese EEZ in the Red Sea was generally low, below 2,000 t, until the end of the 1970s (Figure 13, Appendix Table A6). The total catch includes the amount caught by foreign vessels, trawling and purse seining as explained in the above, in the Sudanese EEZ. Between the 1980s and end of 2000, it was somewhat higher until it showed a rapid increase following the turn of the century. The FAO database provides the total catch reported by Sudan (www .fao.org/fishery/statistics/software/fishstat/en). Until 1992, the reconstructed data were higher than the FAO data except in 1962 and 1983. After 1992, the FAO data were significantly higher except in 2005 where they were more or less the same. As with many countries, this is not a case of either Sudan fishing in other countries’ EEZs, for example Egypt fishing in Sudanese, Eritrea and Yemeni waters (Tesfamichael and Mehanna 2012), or vessels from other countries fishing with Sudanese flag of convenience. Sudan is not listed as a country of flag of convenience, see www.itfglobal.org/flags-convenience/flags-convenien-183.cfm. The most reasonable explanation is that Sudan has misreported its catch to FAO as is the case with many countries (Watson and Pauly 2001; Pauly and Froese 2012).

The shell fishery was the main contributor to the total catch until the mid-1970s, where it started to decline and the catch of artisanal finfish fishery started to increase. The artisanal fishery then became dominant, and remained more or less stable until the present. The rapid increase in the total catch after 2001 was mainly due to the large catch from industrial fisheries, trawling and purse seining (Figure 13; Table A6).

Looking at the components of the reconstructed catch, the unreported landed catch was relatively higher until the end of the 1980s (Figure 14, Table A7). Overall the unreported landed catch accounted for 30% of the total catch from 1950 to 2010. The decline in the proportion of the unreported landed catch, starting in the 1990s, corresponds to the decline of the shell fishery, which had the worst data recording system and accounted for the highest ratio of the unreported landed catch when it was active. The reported catch (part of the reconstructed catch accounted in the FAO data) has the highest contribution to the total catch with 64%. The discarded catch, almost exclusively by trawling, was generally low, 5% from 1950 to 2010, and appears only later, starting the mid-1970s.

Trochus was the main species in the total catch until the beginning of the 1970s. As soon as the artisanal finfish fishery started growing, in the mid-1970s, the number of species in the catch increased. The catch of uncategorized species (i.e., ‘others’) also became very large. This pattern continued until the catch of industrial fisheries also became very important, i.e., after 2001. However, what became most prominent from the industrial fisheries was the high proportion of discards (Figure 15; Table A8).

Figure 12. Catch composition of the purse seine fishery in the EEZ of Sudan, 1950 - 2010.

Figure 13. Reconstructed catch in the EEZ of Sudan by gear type and what is reported to FAO, 1950 - 2010.

Figure 14. Reconstructed catch in the EEZ of Sudan by components, 1950 – 2010. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.

60

disCussion

The total catch in the EEZ of Sudan is the lowest in the Red Sea after Israel and Jordan (Tesfamichael and Pitcher 2006; Tesfamichael et al. 2012a). To a large extent, this can be attributed to the very narrow continental shelf along the Sudanese coast. Nevertheless, the Sudanese fishery has not developed well to fish in its shelf; for example, there has not been a continuous trawl fishery in the trawl suitable grounds and all the trawling has been done by foreign vessels (MEPI 1993). The major catch of the other countries bordering the Red Sea comes from bottom trawling and pelagic species, which are not well developed in Sudan due to the shelf characteristics. Also, the nutrient rich waters that flow into the Red Sea from the Gulf of Aden through the narrow straight ‘Bab al Mendab’ does not reach the Sudanese coast. Thus, the marine fishery sector in Sudan is very small, although still important to the livelihood of the coastal communities. The contribution of Red Sea fisheries to the total fish supply of the country is only around 5%. The major supply comes from inland waters: the Nile River, lakes and reservoirs (Chakraborty 1983).

The catches reported by the FAO on behalf of Sudan are thought to be highly exaggerated, and Sudan appears to submit not accurate estimates of its annual catch data on a regular basis. This has been a common problem for FAO to compile an accurate data of global fisheries catch (Garibaldi 2012). This is why the FAO data were higher than the reconstructed catches in Figure (13). The big spike of total catch according to data submitted to FAO in 1983 is probably an error due to Kedidi (1984), who wrote the potential annual catch to be 4,550 t, which is the value reported in the FAO database. However, the catch for 1983, also in Kedidi (1984), was 1,443 t and this value is used as a basis for the reconstructed catch.

The exploitation levels of Sudanese fisheries may not be very high (Tesfamichael and Pitcher 2006), as the artisanal sector has not expanded in recent years (Tesfamichael and Pauly 2011). Thus, it is not uncommon to still see large sized fishes in the catch and in markets. However, there is no reliable catch survey and data recording system in place to provide reliable estimations as to the status of the fisheries. We believe the present reconstruction to be a good starting point to assess the fishery, as it provides a more comprehensive and accurate estimate of catches, which is key for assessment and management (Pauly and Zeller 2003; Tesfamichael 2012). The general trends are clear, and the major shifts in the fisheries are the decline in the shell fishery, replaced by an artisanal finfish fishery, with a foreign industrial fishery added in recent years. The artisanal fishery, whose main market is the local population, has remained stable. However, the fast growth of the industrial fishery calls for serious assessment of the states of the stocks.

This is the first comprehensive catch reconstruction and fishery review for Sudan. Because there were some clear gaps in data, we had to make many assumptions, based on our knowledge of the fishery. These assumptions are open to criticism and can be replaced whenever better information is available.

aCknowledgement

We would like to thank the personnel of the Fisheries Administration and Fisheries Research Centre in Port Sudan. We would like also to extend our thanks to the personnel of the Ministry of Animal Resources and Fisheries Research Centre in Khartoum. Our special thanks goes to Kalid and Mohammed from the Fisheries Administration, Port Sudan for their help in compiling the catch data from scattered records and their assistance during interviews with fishers; their friendliness to the first author during his field work in Sudan was remarkable. This research was supported by the Sea Around Us, a scientific collaboration between the University of British Columbia and the Pew Charitable Trusts.

referenCes

Barrania A (1985) The socio-economic impact of project’s activities in Mohamed Qol, Sudan. FAO/UNDP Proj. for Development of Fisheries in Areas of the Red Sea and Gulf of Aden, Rome.

Barrania AA (1979) The exploratory socio-economic survey of the Sudanese Red Sea fisheries. FAO/UNDP Proj. for Development of Fisheries in Areas of the Red Sea and Gulf of Aden, Rome.

Chakraborty D (1983) Marine fisheries statistics in Sudan–an expanded plan of development. FAO, Rome. 39 p.Chakraborty D (1984) Fish landings on the Red Sea and Gulf of Aden coast of the member countries: A preliminary

estimate. Development of Fisheries in Areas of the Red Sea and Gulf of Aden, United Nations Development Programme (UNDP) and Food and Agriculture Organization (FAO) of the United Nations, Suez, Egypt. 29 p.

Figure 15. Composition of the reconstructed total catch in the EEZ of Sudan, 1950 - 2010.

Sudan - Tesfamichael and Elawad 61

Elawad AN (2002) Some biological aspects of fish by-catch from Sudanese Red Sea Shrimp Trawling. MSc, University of Khartoum, Department of Zoology, Khartoum. 133 p.

Elnaiem AG (2002) Aspects of shrimp fisheries on Sudanese Red Sea coast. PhD, University of Khartoum, Department of Zoology, Khartoum. 70 p.

Eltayeb MM (1999) Studies on the biology, ecology and fisheries of Tectus dentatus (Kokian) in the Sudanese Red Sea. MSc, University of London, Department of Geography. 92 p.

Eltayeb MM (2004) Review of the trochus fishery in Sudan. SPC Trochus Information Bulletin 11: 5-7.FA (2007) Fishery statistics of Sudan: based on the files of Fisheries Administration office in Port Sudan. Fisheries

Administration, Khartoum.FA (2010) Fishery statistics of Sudan: based on the files of Fisheries Administration office in Port Sudan. Fisheries

Administration, Khartoum.FA (2012) Fishery statistics of Sudan: based on the files of Fisheries Administration office in Port Sudan. Fisheries

Administration, Khartoum.FHAS (1984) Fish production in Sudan — a study on the methodology and the data collected during 1979 and 1980.

FAO/UNDP, SUEZ (EGYPT).Garibaldi L (2012) The FAO global capture production database: A six-decade effort to catch the trend. Marine Policy

36(3): 760-768.Kedidi SM (1984) The Red Sea reef associated fishery of the Sudan catches, efforts and catches per fishing effort survey

conducted during 1982-1984. Project for the development of fishries in the areas of the Red Sea and Gulf of Aden, FAO/UNDP, Cairo.

Kristjonsson H (1956) Sudan–A brief survey of the Sudanese red sea fisheries–Report to the government.MEPI (1993) Identification study for Sudan Red Sea fisheries. Ministry of Economic Planning and Investment,

Khartoum. 213 p.ODA (1983) Report on project activities in Sudan. Overseas Development Agency, U.K.Oswald E (1958) Sudan–Red sea fisheries–Report to the government. FAO, Rome.Pauly D and Froese R (2012) Comments on FAO’s State of Fisheries and Aquaculture, or ‘SOFIA 2010’. Marine Policy

36(3): 746-752.Pauly D and Zeller D (2003) The global fisheries crisis as a rationale for improving the FAO’s database of fisheries

statistics. pp. 1–9 In Zeller D, Booth S, Mohammed E and Pauly D (eds.), From Mexico to Brazil: Central Atlantic fisheries catch trends and ecosystem models. Fisheries Centre Research Reports, Vol. 11 (6), Vancouver, Canada.

Reed W (1962) Sudan–the sudanese shell industry and red sea fisheries–Report to the government.Sanders MJ and Kedidi SM (1981) Summary Review of Red Sea Commercial Fisheries Catches and Stock Assessments

Including Maps of Actual and Potential Fishing Grounds.Sanders MJ and Morgan GR (1989) Review of the fisheries resources of the Red Sea and Gulf of Aden. FAO, Rome.

138 p.Tesfamichael D (2012) Assessment of the Red Sea ecosystem with emphasis on fisheries. PhD, University of British

Columbia, Resource Management and Environmental Studies, Vancouver. 241 p.Tesfamichael D, Govender R and Pauly D (2012a) Preliminary reconstruction of fisheries catches of Jordan and Israel

in the inner Gulf of Aqaba, Red Sea, 1950-2010. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D and Mehanna SF (2012) Reconstructing Red Sea fisheries of Egypt: Heavy investment and fisheries. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D and Mohamud S (2012) Reconstructing Red Sea fisheries of Eritrea: A case study of the relationship between political stability and fisheries development. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D and Pauly D (2011) Learning from the Past for Future Policy: Approaches to Time-series Catch Data Reconstruction. Western Indian Ocean J. Mar. Sci. 10(2): 99-106.

Tesfamichael D and Pitcher TJ (2006) Multidisciplinary evaluation of the sustainability of Red Sea fisheries using Rapfish. Fisheries Research 78(2-3): 227-235.

Tesfamichael D, Pitcher TJ and Pauly D (in press) Assessing changes in fisheries using fishers’ knowledge to generate long time series of catch rates: a case study from the Red Sea. Ecology and society.

Tesfamichael D, Rossing P and Awadh H (2012b) The marine fisheries of Yemen with emphasis on the Red Sea and cooperatives. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Vine PJ and Vine MP (1980) Ecology of Sudanese coral reefs with particular reference to reef morphology and distribution of fishes.

Watson R and Pauly D (2001) Systematic distortions in world fisheries catch trends. Nature 414(6863): 534-536.

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Appendix Table A1. Catch composition (in tonnes) of the artisanal finfish fishery of Sudan, 1950 - 2010Year Serranidae Mugilidae Lutjanidae Lethrinidae Caranx spp. Elasmobranchii Acanthuridae Others1950 90 23 70 41 23 15 8 301951 90 23 70 41 23 15 8 301952 90 23 70 41 23 15 8 301953 90 23 70 41 23 15 8 301954 90 23 70 41 23 15 8 301955 90 23 70 41 23 15 8 301956 90 23 70 41 23 15 8 301957 90 23 70 41 23 15 8 301958 90 23 70 41 23 15 8 301959 90 23 70 41 23 15 8 301960 90 23 70 41 23 15 8 301961 90 23 70 41 23 15 8 301962 90 23 70 41 23 15 8 301963 90 23 70 41 23 15 8 301964 90 23 70 41 23 15 8 301965 90 23 70 41 23 15 8 301966 90 23 70 41 23 15 8 301967 90 23 70 41 23 15 8 301968 90 23 70 41 23 15 8 301969 90 23 70 41 23 15 8 301970 98 25 76 44 25 17 8 331971 106 27 82 48 27 18 9 351972 114 29 88 51 29 19 10 381973 121 31 94 55 31 21 10 401974 129 33 100 58 33 22 11 431975 137 35 106 62 35 23 12 451976 202 52 156 91 51 34 17 671977 189 49 146 85 48 32 16 631978 198 51 153 89 50 34 17 661979 157 82 221 113 48 68 24 791980 276 71 225 191 61 62 11 1001981 393 139 407 276 99 118 32 1631982 348 123 361 244 88 105 29 1441983 679 0 256 363 0 0 0 1441984 317 79 498 266 170 42 17 1541985 304 75 476 254 163 40 16 1481986 266 437 417 223 143 38 14 1711987 253 432 396 211 135 36 13 1641988 239 427 375 200 128 34 12 1571989 226 423 354 189 121 33 12 1511990 211 652 159 155 77 94 0 1501991 238 691 180 175 88 106 0 1641992 276 347 209 203 101 109 0 1381993 248 312 187 182 91 98 0 1241994 243 305 183 178 89 96 0 1221995 265 333 200 195 97 105 0 1331996 296 373 224 218 109 117 0 1481997 219 275 165 161 80 86 0 1101998 241 304 183 177 89 95 0 1211999 278 349 210 204 102 110 0 1392000 251 316 190 185 92 99 0 1262001 257 324 195 189 95 102 0 1292002 247 311 187 181 91 97 0 1242003 263 331 199 193 97 104 0 1322004 297 374 225 218 109 117 0 1492005 321 404 243 236 118 127 0 1612006 369 464 279 271 135 146 0 1852007 322 405 244 236 118 127 0 1612008 321 404 243 236 118 127 0 1612009 325 409 246 239 119 128 0 1632010 326 410 247 240 120 129 0 163

Sudan - Tesfamichael and Elawad 63

Appendix Table A2. Catch composition (in tonnes) of the subsistence fishery of Sudan, 1950 - 2010. Year Serranidae Lutjanidae Mugilidae Lethrinidae Caranx spp. Acanthuridae Others1950 27 21 7 12 7 2 91951 27 21 7 12 7 2 91952 27 21 7 12 7 2 91953 27 21 7 12 7 2 91954 27 21 7 12 7 2 91955 27 21 7 12 7 2 91956 27 21 7 12 7 2 91957 27 21 7 12 7 2 91958 27 21 7 12 7 2 91959 27 21 7 12 7 2 91960 27 21 7 12 7 2 91961 27 21 7 12 7 2 91962 27 21 7 12 7 2 91963 27 21 7 12 7 2 91964 27 21 7 12 7 2 91965 27 21 7 12 7 2 91966 27 21 7 12 7 2 91967 27 21 7 12 7 2 91968 27 21 7 12 7 2 91969 27 21 7 12 7 2 91970 30 23 8 13 8 3 91971 32 25 8 14 8 3 101972 34 26 9 15 9 3 111973 37 28 9 16 9 3 111974 39 30 10 18 10 3 121975 41 32 11 19 10 3 131976 61 47 16 27 15 5 191977 57 44 15 26 15 5 181978 60 46 15 27 15 5 191979 48 67 25 34 15 7 221980 56 45 14 38 12 2 191981 78 81 28 55 20 6 301982 68 70 24 48 17 6 261983 129 49 0 69 0 0 271984 59 93 15 50 32 3 281985 56 88 14 47 30 3 261986 48 75 79 40 26 3 301987 45 70 77 37 24 2 281988 42 65 74 35 22 2 271989 38 60 72 32 21 2 251990 35 27 110 26 13 0 231991 39 30 114 29 14 0 251992 45 34 56 33 16 0 201993 39 30 49 29 14 0 181994 38 28 47 28 14 0 171995 40 30 50 29 15 0 181996 44 33 55 32 16 0 201997 32 24 40 23 12 0 141998 34 26 43 25 13 0 161999 38 29 48 28 14 0 182000 34 26 43 25 12 0 152001 34 26 43 25 12 0 152002 32 24 40 23 12 0 142003 33 25 41 24 12 0 152004 36 27 45 26 13 0 162005 38 29 48 28 14 0 172006 42 32 53 31 15 0 192007 36 27 45 26 13 0 162008 35 26 43 25 13 0 162009 34 26 43 25 12 0 162010 33 25 41 24 12 0 15

64

Appendix Table A3. Composition of the retained catch (in tonnes) of trawl fishery in the EEZ of Sudan, 1950 - 2010.Year Synodontidae Nemipterus spp. Penaeidae Mullidae1950 0 0 0 01951 0 0 0 01952 0 0 0 01953 0 0 0 01954 0 0 0 01955 0 0 0 01956 0 0 0 01957 0 0 0 01958 0 0 0 01959 0 0 0 01960 0 0 0 01961 0 0 0 01962 0 0 0 01963 0 0 0 01964 0 0 0 01965 0 0 0 01966 0 0 0 01967 0 0 0 01968 0 0 0 01969 0 0 0 01970 0 0 0 01971 0 0 0 01972 0 0 0 01973 0 0 0 01974 0 0 0 01975 0 0 0 01976 5 1 15 11977 0 0 0 01978 7 2 19 11979 7 2 21 11980 0 0 0 01981 9 3 26 11982 24 7 4 41983 24 7 4 41984 24 7 4 41985 44 12 8 71986 64 18 12 101987 84 24 15 131988 104 29 19 161989 125 35 23 191990 145 40 26 221991 36 10 7 61992 36 10 7 61993 36 10 7 61994 36 10 7 61995 36 10 7 61996 36 10 7 61997 36 10 7 61998 77 22 14 121999 119 33 22 182000 122 34 22 192001 125 35 23 192002 127 35 23 202003 147 41 27 232004 412 115 75 632005 387 108 71 602006 0 0 0 02007 61 17 11 92008 418 117 76 642009 209 58 38 322010 0 0 0 0

Sudan - Tesfamichael and Elawad 65

Appendix Table A4. Composition of the discarded catch (in tonnes) of trawl fishery in the EEZ of Sudan, 1950 - 2010.Year 1 2 3 4 5 6 7 8 9 10 11 121950 0 0 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 0 0 01967 0 0 0 0 0 0 0 0 0 0 0 01968 0 0 0 0 0 0 0 0 0 0 0 01969 0 0 0 0 0 0 0 0 0 0 0 01970 0 0 0 0 0 0 0 0 0 0 0 01971 0 0 0 0 0 0 0 0 0 0 0 01972 0 0 0 0 0 0 0 0 0 0 0 01973 0 0 0 0 0 0 0 0 0 0 0 01974 0 0 0 0 0 0 0 0 0 0 0 01975 0 0 0 0 0 0 0 0 0 0 0 01976 72 5 5 2 2 2 2 2 1 1 1 181977 0 0 0 0 0 0 0 0 0 0 0 01978 95 6 6 3 3 3 3 3 2 2 2 231979 106 7 7 3 3 3 3 3 2 2 2 261980 0 0 0 0 0 0 0 0 0 0 0 01981 128 8 8 4 4 4 4 4 2 2 2 311982 32 2 2 1 1 1 1 1 1 1 1 81983 32 2 2 1 1 1 1 1 1 1 1 81984 32 2 2 1 1 1 1 1 1 1 1 81985 60 4 4 2 2 2 2 2 1 1 1 141986 87 6 6 3 3 3 3 3 1 1 1 211987 114 7 7 4 4 4 4 4 2 2 2 281988 142 9 9 5 5 5 5 5 2 2 2 341989 169 11 11 5 5 5 5 5 3 3 3 411990 196 13 13 6 6 6 6 6 3 3 3 481991 49 3 3 2 2 2 2 2 1 1 1 121992 49 3 3 2 2 2 2 2 1 1 1 121993 49 3 3 2 2 2 2 2 1 1 1 121994 49 3 3 2 2 2 2 2 1 1 1 121995 49 3 3 2 2 2 2 2 1 1 1 121996 49 3 3 2 2 2 2 2 1 1 1 121997 49 3 3 2 2 2 2 2 1 1 1 121998 105 7 7 3 3 3 3 3 2 2 2 251999 162 10 10 5 5 5 5 5 3 3 3 392000 165 11 11 5 5 5 5 5 3 3 3 402001 169 11 11 5 5 5 5 5 3 3 3 412002 173 11 11 6 6 6 6 6 3 3 3 422003 199 13 13 6 6 6 6 6 3 3 3 482004 559 36 36 18 18 18 18 18 9 9 9 1352005 525 34 34 17 17 17 17 17 8 8 8 1272006 0 0 0 0 0 0 0 0 0 0 0 02007 82 5 5 3 3 3 3 3 1 1 1 202008 567 37 37 18 18 18 18 18 9 9 9 1372009 283 18 18 9 9 9 9 9 5 5 5 692010 0 0 0 0 0 0 0 0 0 0 0 01: Leiognathidae; 2: Gerreidae; 3: Trichiuridae; 4: Parastromateus niger; 5: Platycephalidae; 6: Portunus pelagicus; 7: Soleidae; 8: Tetraodontidae; 9: Clupeidae; 10: Mullidae; 11: Stomatopoda; 12: Others

66

Appendix Table A5. Catch composition (in tonnes) of the purse seine fishery in the EEZ of Sudan, 1950 - 2010.Year Sardinella spp. Scomberomorus commerson Sphyraena spp. Carangidae1950 0 0 0 01951 0 0 0 01952 0 0 0 01953 0 0 0 01954 0 0 0 01955 0 0 0 01956 0 0 0 01957 0 0 0 01958 0 0 0 01959 0 0 0 01960 0 0 0 01961 0 0 0 01962 0 0 0 01963 0 0 0 01964 0 0 0 01965 0 0 0 01966 0 0 0 01967 0 0 0 01968 0 0 0 01969 0 0 0 01970 0 0 0 01971 0 0 0 01972 0 0 0 01973 0 0 0 01974 0 0 0 01975 0 0 0 01976 0 0 0 01977 0 0 0 01978 0 0 0 01979 0 0 0 01980 0 0 0 01981 0 0 0 01982 0 0 0 01983 0 0 0 01984 0 0 0 01985 0 0 0 01986 0 0 0 01987 0 0 0 01988 0 0 0 01989 0 0 0 01990 0 0 0 01991 0 0 0 01992 0 0 0 01993 0 0 0 01994 0 0 0 01995 0 0 0 01996 0 0 0 01997 0 0 0 01998 0 0 0 01999 0 0 0 02000 0 0 0 02001 0 0 0 02002 452 25 15 102003 764 42 25 172004 1,474 82 49 332005 1,319 73 44 292006 0 0 0 02007 0 0 0 02008 0 0 0 02009 302 17 10 72010 0 0 0 0

Sudan - Tesfamichael and Elawad 67

Appendix Table A6. Reconstructed catch (in tonnes) in the EEZ of Sudan by gear type and what is reported to FAO, 1950 - 2010.Year FAO landings Reconstructed total catch Artisanal finfish Artisanal invertebrates Subsistence Discards Trawl Purse seining1950 500 1,946 300 1,561 85 0 0 01951 500 1,721 300 1,335 85 0 0 01952 1,000 2,133 300 1,748 85 0 0 01953 1,300 1,972 300 1,587 85 0 0 01954 1,100 1,749 300 1,364 85 0 0 01955 1,100 1,663 300 1,277 85 0 0 01956 1,200 1,761 300 1,376 85 0 0 01957 800 1,311 300 925 85 0 0 01958 900 1,309 300 923 85 0 0 01959 1,100 1,622 300 1,237 85 0 0 01960 1,100 1,418 300 1,032 85 0 0 01961 1,200 1,324 300 938 85 0 0 01962 1,600 1,475 300 1,089 85 0 0 01963 1,000 1,626 300 1,241 85 0 0 01964 700 1,777 300 1,392 85 0 0 01965 700 1,928 300 1,543 85 0 0 01966 1,000 2,080 300 1,694 85 0 0 01967 800 1,783 300 1,398 85 0 0 01968 800 1,393 300 1,008 85 0 0 01969 800 1,713 300 1,328 85 0 0 01970 800 2,085 326 1,667 93 0 0 01971 800 1,319 351 867 100 0 0 01972 800 1,672 377 1,187 107 0 0 01973 800 1,580 403 1,062 115 0 0 01974 800 1,367 429 816 122 0 0 01975 800 955 454 372 129 0 0 01976 800 1,562 671 563 191 115 22 01977 600 1,041 628 233 179 0 0 01978 750 1,355 657 332 187 150 29 01979 700 2,576 792 1,367 217 168 32 01980 950 1,781 996 598 187 0 0 01981 870 2,579 1,628 412 297 203 39 01982 1,050 2,328 1,441 539 258 51 39 01983 4,450 2,106 1,443 300 274 51 39 01984 1,328 2,262 1,542 350 280 51 39 01985 409 2,364 1,475 460 263 94 71 01986 1,190 2,420 1,708 170 301 138 104 01987 1,200 2,892 1,641 651 283 181 136 01988 1,200 2,959 1,574 726 267 224 169 01989 1,200 3,764 1,507 1,539 251 267 201 01990 1,500 2,567 1,500 289 234 310 234 01991 1,500 2,354 1,643 323 251 78 59 01992 2,000 2,408 1,383 684 204 78 59 01993 2,500 2,431 1,242 873 179 78 59 01994 4,000 2,080 1,215 556 172 78 59 01995 4,000 2,342 1,328 693 184 78 59 01996 4,500 2,457 1,485 634 201 78 59 01997 5,000 2,312 1,096 934 145 78 59 01998 5,500 2,758 1,210 1,102 156 165 125 01999 5,500 2,764 1,391 749 175 255 192 02000 5,000 2,762 1,260 889 155 261 197 02001 5,000 2,738 1,291 824 155 267 201 02002 5,000 3,189 1,237 827 144 273 206 5022003 5,000 3,575 1,318 705 150 315 237 8492004 5,500 5,410 1,489 568 165 884 666 1,6382005 5,200 5,310 1,608 609 173 829 625 1,4662006 5,000 2,486 1,848 444 193 0 0 02007 5,699 2,469 1,614 463 164 130 98 02008 5,695 3,864 1,609 524 158 897 676 02009 5,690 2,993 1,631 87 155 448 337 3352010 5,700 1,873 1,635 88 151 0 0 0

68Appendix Table A7. Reconstructed catch (in tonnes) in the EEZ of Sudan by components, 1950 – 2010. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.

Year Reported Unreported Discards1950 500 1,446 01951 500 1,221 01952 1,000 1,133 01953 1,300 672 01954 1,100 649 01955 1,100 563 01956 1,200 561 01957 800 511 01958 900 409 01959 1,100 522 01960 1,100 318 01961 1,200 124 01962 1,374 101 01963 1,000 626 01964 700 1,077 01965 700 1,228 01966 1,000 1,080 01967 800 983 01968 800 593 01969 800 913 01970 800 1,285 01971 800 519 01972 800 872 01973 800 780 01974 800 567 01975 794 161 01976 800 648 1151977 600 441 01978 750 455 1501979 700 1,709 1681980 950 831 01981 870 1,506 2031982 1,050 1,227 511983 1,781 274 511984 1,328 883 511985 409 1,861 941986 1,190 1,092 1381987 1,200 1,512 1811988 1,200 1,535 2241989 1,200 2,297 2671990 1,500 757 3101991 1,500 776 781992 2,000 330 781993 2,076 277 781994 1,734 267 781995 1,975 288 781996 2,061 318 781997 2,003 231 781998 2,386 206 1651999 2,279 229 2552000 2,290 210 2612001 2,294 177 2672002 2,753 163 2732003 3,077 183 3152004 4,275 251 8842005 4,221 260 8292006 2,226 260 02007 2,127 212 1302008 2,761 206 8972009 2,318 227 4482010 1,659 214 0

Sudan - Tesfamichael and Elawad 69Appendix Table A8. Composition of the reconstructed total catch (in tonnes) in the EEZ of Sudan, 1950 - 2010.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 151950 1,365 118 30 91 53 27 30 0 0 15 0 123 44 0 01951 1,033 118 30 91 53 27 30 0 0 15 0 230 44 0 01952 1,530 118 30 91 53 27 30 0 0 15 0 145 44 0 01953 1,364 118 30 91 53 27 30 0 0 15 0 151 44 0 01954 1,159 118 30 91 53 27 30 0 0 15 0 133 44 0 01955 1,097 118 30 91 53 27 30 0 0 15 0 108 44 0 01956 1,129 118 30 91 53 27 30 0 0 15 0 175 44 0 01957 750 118 30 91 53 27 30 0 0 15 0 103 44 0 01958 761 118 30 91 53 27 30 0 0 15 0 90 44 0 01959 1,070 118 30 91 53 27 30 0 0 15 0 95 44 0 01960 848 118 30 91 53 27 30 0 0 15 0 112 44 0 01961 781 118 30 91 53 27 30 0 0 15 0 85 44 0 01962 932 118 30 91 53 27 30 0 0 15 0 85 44 0 01963 1,083 118 30 91 53 27 30 0 0 15 0 85 44 0 01964 1,234 118 30 91 53 27 30 0 0 15 0 86 44 0 01965 1,385 118 30 91 53 27 30 0 0 15 0 86 44 0 01966 1,536 118 30 91 53 27 30 0 0 15 0 86 44 0 01967 1,270 118 30 91 53 27 30 0 0 15 0 56 44 0 01968 866 118 30 91 53 27 30 0 0 15 0 69 44 0 01969 1,130 118 30 91 53 27 30 0 0 15 0 125 44 0 01970 1,542 128 33 99 57 27 32 0 0 17 0 53 44 0 01971 751 138 36 106 62 27 35 0 0 18 0 44 44 0 01972 1,073 148 38 114 66 27 38 0 0 19 0 42 44 0 01973 931 158 41 122 71 27 40 0 0 21 0 59 44 0 01974 725 168 44 130 76 27 43 0 0 22 0 19 44 0 01975 276 178 46 138 80 27 45 0 0 23 0 23 44 0 01976 442 263 68 203 118 27 67 72 0 34 5 50 44 1 151977 141 246 64 190 111 27 63 0 0 32 0 20 44 0 01978 257 258 67 199 116 27 65 95 0 34 7 3 44 2 191979 1,223 205 106 288 147 27 63 106 0 68 7 73 44 2 211980 520 332 85 270 229 27 73 0 0 62 0 6 44 0 01981 209 471 167 488 330 147 119 128 0 118 9 10 44 3 261982 345 415 148 431 291 135 105 32 0 105 24 14 44 7 41983 114 808 0 305 432 123 0 32 0 0 24 18 44 7 41984 172 377 94 591 315 110 202 32 0 42 24 22 44 7 41985 298 359 89 564 301 98 193 60 0 40 44 19 44 12 81986 81 314 515 493 263 27 168 87 0 38 64 17 44 18 121987 543 297 509 466 249 49 159 114 0 36 84 14 44 24 151988 601 281 502 440 235 70 150 142 0 34 104 9 44 29 191989 1,398 264 495 414 221 92 141 169 0 33 125 3 44 35 231990 115 246 762 186 181 114 90 196 0 94 145 15 44 40 261991 115 278 805 210 204 136 102 49 0 106 36 28 44 10 71992 442 320 403 242 235 158 118 49 0 109 36 40 44 10 71993 613 287 361 217 211 179 105 49 0 98 36 36 44 10 71994 277 280 352 212 206 201 103 49 0 96 36 33 44 10 71995 396 305 384 231 224 223 112 49 0 105 36 29 44 10 71996 319 340 428 257 250 245 125 49 0 117 36 26 44 10 71997 600 250 315 189 184 266 92 49 0 86 36 22 44 10 71998 750 276 347 208 202 288 101 105 0 95 77 19 44 22 141999 379 316 397 239 232 310 116 162 0 110 119 15 44 33 222000 500 285 359 216 210 332 105 165 0 99 122 12 44 34 222001 417 291 366 220 214 354 107 169 0 102 125 8 44 35 232002 335 278 350 211 205 442 102 173 452 97 127 5 44 35 232003 364 296 372 224 217 295 109 199 764 104 147 1 44 41 272004 336 333 419 252 245 187 122 559 1,474 117 412 0 44 115 752005 367 359 451 271 263 196 132 525 1,319 127 387 0 44 108 712006 301 411 517 311 302 98 151 0 0 146 0 0 44 0 02007 280 358 450 271 263 138 131 82 0 127 61 0 44 17 112008 312 356 447 269 261 167 131 567 0 127 418 0 44 117 762009 42 359 452 272 264 0 132 283 302 128 209 0 44 58 382010 13 359 452 272 264 29 132 0 0 129 0 0 44 0 0

1: Trochus spp.; 2: Serranidae; 3: Mugilidae; 4: Lutjanidae; 5: Lethrinidae; 6: Holothuroidea; 7: Caranx spp.; 8: Leiognathidae; 9: Sardinella spp.; 10: Elasmobranchii; 11: Synodontidae; 12: Pinctada spp.; 13: Strombidae; 14: Nemipterus spp.; 15: Penaeidae

70Table A8 continued. Year 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 311950 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391951 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391952 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391953 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391954 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391955 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391956 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391957 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391958 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391959 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391960 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391961 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391962 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391963 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391964 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391965 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391966 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391967 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391968 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391969 10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 391970 11 0 0 0 0 0 0 0 0 0 0 0 0 0 1 421971 12 0 0 0 0 0 0 0 0 0 0 0 0 0 1 451972 13 0 0 0 0 0 0 0 0 0 0 0 0 0 1 481973 13 0 0 0 0 0 0 0 0 0 0 0 0 0 1 521974 14 0 0 0 0 0 0 0 0 0 0 0 0 0 1 551975 15 0 0 0 0 0 0 0 0 0 0 0 0 0 1 581976 22 2 5 5 0 2 2 2 2 2 0 0 1 1 1 1041977 21 0 0 0 0 0 0 0 0 0 0 0 0 0 1 811978 22 3 6 6 0 3 3 3 3 3 0 0 2 2 1 1071979 31 3 7 7 0 3 3 3 3 3 0 0 2 2 1 1271980 13 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1181981 39 3 8 8 0 4 4 4 4 4 0 0 2 2 1 2241982 34 4 2 2 0 1 1 1 1 1 0 0 1 1 1 1781983 0 4 2 2 0 1 1 1 1 1 0 0 1 1 1 1801984 20 4 2 2 0 1 1 1 1 1 0 0 1 1 1 1901985 19 8 4 4 0 2 2 2 2 2 0 0 1 1 1 1881986 16 11 6 6 0 3 3 3 3 3 0 0 1 1 1 2221987 16 15 7 7 0 4 4 4 4 4 0 0 2 2 1 2201988 15 18 9 9 0 5 5 5 5 5 0 0 2 2 1 2181989 14 22 11 11 0 5 5 5 5 5 0 0 3 3 1 2171990 0 25 13 13 0 6 6 6 6 6 0 0 3 3 1 2211991 0 6 3 3 0 2 2 2 2 2 0 0 1 1 1 2011992 0 6 3 3 0 2 2 2 2 2 0 0 1 1 1 1711993 0 6 3 3 0 2 2 2 2 2 0 0 1 1 1 1541994 0 6 3 3 0 2 2 2 2 2 0 0 1 1 1 1511995 0 6 3 3 0 2 2 2 2 2 0 0 1 1 1 1631996 0 6 3 3 0 2 2 2 2 2 0 0 1 1 1 1811997 0 6 3 3 0 2 2 2 2 2 0 0 1 1 1 1361998 0 14 7 7 0 3 3 3 3 3 0 0 2 2 1 1621999 0 21 10 10 0 5 5 5 5 5 0 0 3 3 1 1962000 0 21 11 11 0 5 5 5 5 5 0 0 3 3 1 1812001 0 22 11 11 0 5 5 5 5 5 0 0 3 3 1 1852002 0 22 11 11 25 6 6 6 6 6 15 10 3 3 1 1802003 0 26 13 13 42 6 6 6 6 6 25 17 3 3 1 1952004 0 73 36 36 82 18 18 18 18 18 49 33 9 9 1 3012005 0 68 34 34 73 17 17 17 17 17 44 29 8 8 1 3052006 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2042007 0 11 5 5 0 3 3 3 3 3 0 0 1 1 1 1982008 0 74 37 37 0 18 18 18 18 18 0 0 9 9 1 3142009 0 37 18 18 17 9 9 9 9 9 10 7 5 5 1 2472010 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 179

16: Acanthuridae; 17: Mullidae; 18: Gerreidae; 19: Trichiuridae; 20: Scomberomorus commerson; 21: Parastromateus niger; 22: Platycephalidae; 23: Portunus pelagicus; 24: Soleidae; 25: Tetraodontidae; 26: Sphyraena spp.; 27: Carangidae; 28: Clupeidae; 29: Stomatopoda; 30: Gastropoda; 31: Others

Eritrea - Tesfamichael and Mohamud 71

reConstruCting red sea fisheries of eritrea: a Case study of the relationship between politiCal stability and fisheries development1

Dawit Tesfamichaela,b, Sammy Mohamudc

a Sea Around Us, Fisheries Centre, University of British Columbia,2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada

b Department of Marine Sciences, University of Asmara, Asmara, Eritrea.c Ministry of Fisheries, Massawa, Eritrea

d.tesfamichael @fisheries.ubc.ca; ecmibsammy @gmail.com

abstraCt

The fisheries catch in the Eritrean Red Sea Exclusive Economic Zone (EEZ) was reconstructed from 1950 to 2010 based on published data, government reports, surveys and field interviews. Six major fisheries, different in terms of their operation, the fish they target and their market, were identified. Overall, the fisheries went through major shifts from the state of high catches dominated by small pelagic beach seining in the 1950s (slightly under 30,000 t·year-1) and 1960s to the domination by bottom trawling prevailing since the 1990s. The catches started to decline to less than 2,500 t·year-1, a catch level which lasted from the mid-1970s to the first few years after independence (1991), before recovering and reaching a new peak of about 20,000 t·year-1 at the beginning of 2000s. The artisanal fisheries, which target mainly fresh fish for direct human consumption, have exhibited a relatively steady upward trend since independence. The reconstructed total catch for the period from 1950 to 2010 was 2.2 times the data reported by Eritrea to the Food and Agriculture Organization of the United Nations (FAO). The political events strongly impacted the fisheries of Eritrea, notably its struggle of independence.

introduCtion

Eritrea borders the Red Sea (Figure 1), and its continental shelf, i.e., waters shallower than 200 m, where most of the fishing occurs, covers about 50,000 km2. Due to its harsh environmental conditions, the coast is not densely populated. However, archaeological studies of middle stone-age middens from the Eritrean coast indicate that humans were exploiting near-shore marine organisms such as giant clams and other molluscs about 125,000 years ago (Walter et al. 2000). In the recent past, the most common fishing activity along the Eritrean coast was diving for trochus and pearl oyster by local people, and handlining mainly by Yemeni fishers. In the mid-1940s, beach seining for schools of sardines and anchovies started and it flourished as the main fishing activity for the next few decades (Ben-Yami 1964). In terms of the total catch and the number of people involved either directly or indirectly in the fishery, the Eritrean fishery reached its peak in the 1950s and 1960s. Starting in the 1970s, the fishery went through rapid decline and almost completely disappeared at the end of the 1980s. After the independence of Eritrea in 1991, the fishery started to recover and there has been an increase in fishing activities. The newly recovered fishery does not rely on beach seining. Rather it is dominated by hook and line and gillnet fisheries in the artisanal sector, and bottom trawling in the industrial sector (Tesfamichael 2001). It is important to note that some of the reports written about Eritrean fishery before 1991 refer to the fishery as ‘Ethiopian’ because until then, Eritrea was part of Ethiopia. In 1991, Eritrea gained its de facto independence and international recognition followed in 1993. These reports also frequently use the Ge’ez calendar, based on the Coptic calendar used by the Orthodox church of Eritrea and Ethiopia, which starts in September and is seven and half years behind the Gregorian calendar (GC). All dates in this report refer to the GC unless specified otherwise.

1 Cite as: Tesfamichael, D. and Mohamud, S. (2012) Reconstructing Red Sea fisheries catches of Eritrea: a case study of the relationship between political stability and fisheries development. pp. 51-70. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosysytem by countries (1950-2010). Fisheries Centre Research Reports 20(1). Fisheries Centre, University of British Columbia [ISSN 1198-6727].

Figure 1. Map of Eritrea and its Red Sea coast, shelf area and Exclusive Economic Zone (EEZ).

72

In this report, the catch of fisheries in Eritrean Red Sea EEZ, both by domestic and foreign fleets, are reconstructed from 1950 to 2010. Overall, the fisheries can be divided into three sectors: artisanal, subsistence and industrial. Six major fisheries, categorized by the gear they use and the resources they target, were identified and treated separately. The catch of each gear was further divided to the species or taxa groups that make up the total catch. Each fishery is first briefly introduced, based on its development over time, operation, species targeted and market. The catch reconstruction procedure is then presented and discussed for each gear separately and for the country as a whole.

Artisanal fishery

The artisanal fishery is the most prominent fishery in the Eritrean Red Sea, It is a small-scale fishery with less capital investment (compared to industrial), and locally owned and operated. There are few gears used by the artisanal fishery.

Beach seine fishery

Beach seining started in the mid 1940s (Ben-Yami 1964) and grew until it became the dominant fishing method in the country in the late 1950s and early 1960s, then declined and faded away in the mid-1970s. The beach seine fishery targeted mainly small pelagic fishes (sardines and anchovies) when they approached the coastal waters during the colder months, i.e., starting in October and extending until May. Through many years of practice, the fishers developed a great deal of experience and knowledge in navigating to beach seining areas, spotting fish schools over clear bottoms, encircling them, and hauling their catch. The fishing operation included a mother dhow carrying the seine net and other miscellaneous supplies, and one or two small canoes. The mother dhow would anchor near a spot which the school of fish was expected to approach, and the canoe(s) would encircle the fish, putting one end of the rope on the shore. The catch was hauled to shore manually and left to dry above the tide for 1 to 2 days. Sometimes the catch would be damaged by rain while drying. Women and children from nearby villages used to scare off birds, thus earning the right to collect and sell what was left on the beach by the fishers. The dried fish would be transported to either Massawa or Assab, the major ports in Eritrea (Figure 1). Sardines and small anchovies were used almost exclusively for fishmeal which was exported to Italy, Greece, Spain, Switzerland and other European countries, while large anchovies were sun-dried, handpicked and mechanically cleaned of impurities to be exported for human consumption to Sri Lanka and other Asian countries (Grofit 1971).

Sardines were found only around Massawa and the Dahlak archipelago, while large anchovies were found only in the southern part around Assab. When this fishery was at its peak in the 1950s and 1960s, there were up to 6 factories in Massawa for fishmeal and cleaning of large anchovies for human consumption, while there were a couple of them in Assab, devoted to cleaning anchovies only. The landing in Massawa was about double that of Assab (Ben-Yami 1964). This fishery accounted for up to 90% of the total landed catch and it played a large role in the economic and social life of local coastal communities.

Beach seining was also used, although to a lesser extent, to exploit stocks of Spanish mackerels (Scomberomorus spp.) and mullets (Family Mugilidae) for direct human consumption. Later, starting in the 1970s, when the export of dry fish and fishmeal stopped, beach seining was used to catch fresh fish for a few years and the accidently caught anchovies and sardines were discarded (Ben-Yami 1964; Grofit 1971). At present, although the resource potential still exists, commercial beach seining for small pelagics does not occur.

Handline fishery

Handlining (hook and line fishing) is one of the oldest forms of fishing practiced along the Eritrean coast, and is a technique that has been used continuously almost exclusively by the small-scale fisheries. In the 1940s, fishers of Yemenite origin, which some of them later settled in Eritrea, started to use handlining to supply markets in Eritrea and Yemen (Ben-Yami 1964). Since 1991, the handlining catch is sold both locally, or exported to markets in the Middle East and Europe. The fishery targets mainly reef-associated fishes, such as snappers (Lutjanidae), groupers (Serranidae) and emperors (Lethrinidae). Handline fishery occurs around the Dahlak Archipelago and along the northern part of the Eritrean coast, where coral reefs are more developed. It is also performed while on foot from the shore, or from small canoes. Also wooden boats of about 10m long with inboard or outboard engine are used in this fishery.

Usually, only one hook is tied to one end of the line, which is lowered into the water. When the fishers feel that a fish is biting, they start pulling the line back to the boat with their bare hands; indeed, many fishers have cuts on their hands, sustained when they fight to haul the fish into their boats. Fish caught in previous trips are cut into smaller pieces to be used as bait at the beginning of a given trip. Later, low-grade fish are used as bait. Fishing starts in the late afternoon and is carried out throughout the night, until dawn. Overall trip length may range from a few to 10 days, usually as determined by either fish storage capacity (ice boxes), or the ice supply. Because the technique is very selective, this fishery does not have a discarding problem. Recently handlining and gillnetting represent the major artisanal fisheries in Eritrea.

Eritrea - Tesfamichael and Mohamud 73

Gillnet fishery

Gillnets were used for shark fishing for a long time, but also for other large pelagic species. Gillnets started to be common only in the 1980s, according to interviews with old fishers, and Giudicelli (1984). Once gillnet fishing started, however, it became an important part of the artisanal fisheries. Their main target is Spanish mackerel (Scomberomorus commerson) but also catch barracudas (Sphyraena spp.), jacks (Carangidae) and sharks. They set their nets at night mainly in the central and southern part of the coast. The net is immersed for about 2-3 hours, to avoid the entangled fish from spoilage, and post-capture predation by predators, notably sharks. Gillnet fishing is highly affected by moon phase. The new moon is the best time to catch fish using gillnet, where trips last only up to 2 days to fill the fish storage. However, during full moon, trips are longer and some fishers switch to handlining. This fishery is less selective than the handline fishery and has discards, mainly small tunas like kawakawa (Euthynnus affinis), which fetch a relatively low price.

Shark fishery

Shark fishing has been common along the Eritrean coast for a long time (Ben-Yami 1964). Sharks were caught by handline, bottom longline and inshore gillnet mainly in the central and southern part of the coast. Shark fishing trips are one of the longest. Ice is not needed in this fishery, and as a result, fishers stay up to a month at sea with short stops at villages near their fishing ground to renew their water supply, drying and collecting their catches (fins and meat) until they come back to land their catches. During the 1950s and 1960s, shark fishing used to occur during the hot months of summer, alternating with the beach seine fishery. Whenever the beach seining fishery faced problems, fishers used to switch to shark fishing. For example in 1967 when export of fishmeal was disrupted by the closure of the Suez Canal, most fishers switched to shark fishing, resulting in high catch of sharks. Shark, either the fin or the flesh, is not favored in Eritrea, thus it has been mainly an export-oriented fishery. In the past, the flesh used to be salted and sun dried on the beach after gutting and fining. The dried meat would be tightly stacked and sewn in straw mats locally called ’ferasila’(Campbell 1993), which weighed about 15 kg. About 5 – 6 kg of wet shark flesh were needed to produce 1 kg of dried shark meat (Grofit 1971). Both the dried fin and meat were exported to Aden, Yemen, where they were re-exported to East Asian markets. Because the flesh was dried on the beach, it had sand impurities; hence, it was not the best quality in the Aden market and did not fetch good price. This eventually decreased the demand of shark meat from Eritrea and together with political instability, resulted in the decline of the fishery starting in the early 1970s. After 1991, dried shark fins were exported, but not continuously. However, the flesh was not used and it is common to see rotting shark carcasses on the beaches. The fishers have the tradition of not throwing away the unwanted catch back into the water because they believe it will contaminate the sea and scare off the fish they target.

Sea cucumber fishery

Sea cucumber gathering has been done in shallow waters by women and young kids for many years at low level (Ben-Yami 1964). A major sea cucumber fishery started in 2000 exclusively for export due to the high demand for the product in China and other East Asian countries. Since its start in 2000, the reported local catch (mainly of Holothuria spp. and Actinopyga spp.) increased rapidly, peaked in 2002 and then started to decline (Tewelde and Woldai 2007), despite an increasing demand. The decline could be a sign of overexploitation of the resource, although some of the catch is known to be sold illegally in Yemen where prices are higher, and fishing supplies cheaper (Tewelde and Woldai 2007). Gathering is normally done by skin diving, but as the shallow parts of the stock are getting depleted, the deeper parts are increasingly being exploited as well. Collectors use air compressor and hookah diving to reach deeper waters. As they operate with little or no training and improper equipment, accidents are common, with serious health problems and deaths among divers. Proper SCUBA equipment is used very rarely. The collectors dive with a sack to fill with hand-picked sea cucumbers. The catch is processed first by boiling and then drying the boiled sea cucumbers on the beach. When this fishery started in 2000, the catch was small and used to be sold in markets in Yemen, but later as the catch increased, it was exported directly to East Asian markets.

Other artisanal fisheries

The fisheries included in this category are all for invertebrates: shell fish, lobster, snail ‘nail’ and pearl fisheries. Shell collection in shallow waters by women and young children, and skin diving by men was one of the oldest fishing activities in the Eritrean Red Sea. Most of the shell collection occurred in the summer months, when the water is warm enough for skin diving, and there was no beach seining. The main targets were trochus shells, mother of pearl shells, pearl oyster, and ornamental conchs (Ben-Yami 1964). Similar to those in the shark fishery, the trips were very long, up to 30 days, with 20 – 40 crews and supplies replenished from the settlements near the fishing grounds. No equipment was used except sometimes home-made masks called ‘nadur’, which limited operations to shallow waters although gradually, proper dive masks were introduced. The main product was semi-finished buttons, exported mainly to Italy. The industry was very active in the 1950s when 6 button factories were established in Massawa. Most fishers preferred to sell their catch in Suakin, Sudan, where they received better prices. Based on interviews with old fishers, about 40 sailing boats used to go to Sudan to sell shells until 1978 before it was prohibited by the government for the fishers to sell outside the country. Most of the fishers switched to other fishing activities and the shell fishery was abandoned.

Snail ‘nails’ (operculum) were and still are collected by women and children in shallow waters. The nails are dried and sold for use in the cosmetic industry. Lobster fishing occurs mainly in the Assab area. So far, the main bottleneck of this fishery is a lack of market.

74

Subsistence fishery

The majority of the subsistence catch is associated with the artisanal fishery. It includes part of the artisanal fishery catch that is consumed by the crew, and freely given to family members, friends and people in the community who need help. There is a well-established social tradition locally called ‘kusar’ throughout the Red Sea, where part of the catch is separated to be given freely before the remaining is sold. In some smaller communities, it is a taboo to sell the whole catch before part of the catch is given to people who need the support. It is a local social support system, which is enforced by social ostracism of those who do not conform.

Industrial fishery

The industrial fishery, has higher capital investment, uses more advanced technology (e.g., GPS, winch) and uses bigger vessels compared to the artisanal sector. It includes two gear types namely bottom trawl and longline. The former is almost exclusively owned and operated by foreign companies, while the latter is a local operation. The market for the industrial fishery is mainly export.

Trawl fishery

The trawl fishery in the Eritrean Red Sea, which is operated mainly by foreign vessels, was divided, especially in the early years, into inshore shrimp trawling, which was done mainly around Hirgigo bay, and offshore trawling targeting fish. The operations were different and data reported separately. The protected shallow bays (less than 45 m) along the Eritrean coast were continuously fished for shrimp since the 1940s (Grofit 1971) by small inshore trawlers owned by locals of Italian descendents from the colonial times who were involved in fisheries, which are more advanced in technology, trade and processing products. Mediterranean trawls with a cod end of 10 – 15 mm (stretched) were used to catch shrimp (Penaeidae), which were sold to foreigners living in Eritrea and Ethiopia. About 90% of the catches were discarded, as only shrimps were retained. The shrimp fishery restarted again in the 1990s after being inactive in the 1970s and 1980s, with landings an order of magnitude higher than the 1950s and 1960s. The recent shrimp fishery is geared toward the export market.

The first exploratory offshore trawling survey was done in 1957 by Israeli trawlers, and later a commercial trawl fishery started in 1959 (Ben-Yami 1964). They used Mediterranean trawl at depth ranges of 45 m to more than 100 m around and south of Massawa. The main catch included lizard fish (Saurida spp.) and threadfin bream (Nemipterus spp.), which were refrigerated in the trawlers and landed at Eilat, Israel. This fishery had a lot of discard, consisting of fishes such as Apogonidae, Leiognathidae, Platycephalidae and others, and smaller sizes of the targeted species. The retention size for lizard fish and threadfin bream were 15 cm and 22 cm, respectively. The fishery was active until the mid-1970s, before it was disrupted by war and instability. It started again after 1991 by trawlers mainly from Egypt and sometimes from Saudi Arabia.

Longline fishery

Although longlines were used for shark fishing in the past, a major longline fishery was started in 1999 by an Australian/Eritrean joint venture. It uses mainly fibreglass boats with inboard or outboard engine with a winch to pull in the line. The bait used is Indian mackerel (Rastrelliger kanagurta), caught either by a dedicated seining boat, or sometimes imported. Most of the skippers reported that bait has been the main bottleneck for their operation. They target coral reef-associated carnivorous fishes, but they do not fish in the coral reef area itself because of gear entanglement problems. The fishers mark the spots (using GPS) where they had the best catch and return to the same site again and again until the catch declines. This can cause localized overfishing of some species, especially territorial ones. As the line is hauled in, it is common to see retrieved fish that are half eaten, probably by shark. It is also common to see sharks caught in the line; they are usually thrown back to the sea either dead or alive. The catch of this fishery was very rewarding; about 2 t were caught in 2 days by a fast boat that had 4 crew members, as noted by the first author while onboard in 2000.

materials and methods

An extensive search was made for published papers, reports and other documentations to be used as the basis for the reconstruction of the Eritrean Red Sea fisheries. Most of the materials for the early years were government reports, and expert technical and survey reports. A good description of the fisheries by resource type, gear, operation, total catch, composition and some effort data for the past fisheries was given by Ben-Yami (1964), who was in the Eritrean Red Sea as an expert working for the then Ethiopian government as a master fisher from 1960 to 1963. Grofit (1971), who was also an advisor to the Ethiopian government, from 1966 to 1969, gave a follow-up account of the fisheries based on Ben-Yami (1964) and his own experiences. Most of the information in the 1980s and early 1990s was based on FAO technical reports written by experts who made short visits to the area, notably Giudicelli (1984). For the period after Eritrea became independent in 1991, most of the data were obtained from the Ministry of Fisheries (MOF), which keeps relatively good records of the fisheries activities in the country. Interviews were also done, by the first author, with fishers of a wide age range to obtain a general understanding of the fisheries at different periods and were also used as supplementary information when quantitative data were missing (Tesfamichael et al.

Eritrea - Tesfamichael and Mohamud 75

in press). For example, the qualitative information given by the fishers was used for interpolations where there were data gaps (see below).

For some years, catch data were given in some reports and those were used as anchors points for the reconstruction procedure. The years for which data were unavailable, interpolations or extrapolations were performed using the anchor points and information as to what happened in the fisheries during those years. Different approaches were used for different fisheries based on the information available and the nature of their operations; hence the reconstruction method is given below for each fishery.

Artisanal fishery

Beach seine fishery

The beach seine fishery in Eritrea can be divided into two categories: one targeting export markets for fishmeal and dried fish of small pelagic species such as sardines and anchovies. The other category is beach seining of relatively larger fishes for direct consumption through the local market. The records on the export fishery were thorough and informative, including files from customs office, which provided information on how much of the final products, fish meal powder and dried fish, were exported (Tesfamichael and Pauly 2011). The earliest reported catch of the beach seine fishery for export was 25,000 t for the early 1950s (Johnson 1956). Because this fishery was well established by the mid-1940s (Ben-Yami 1964), 25,000 t is taken as the total annual catch from 1950 to 1955. Catch estimates from 1958 to 1963 were available from Ben-Yami (1964), 1964 – 1967 from Grofit (1971) and 1968–1975 from Sanders and Morgan (1989), which also presented data for 1979 and 1980. The next data for the small pelagic beach seine fishery appeared in FAO database under Ethiopia for 1976 and 1980-1987 (FAO 2010); following that period, the fishery declined, and collapsed in 1990. In 2000, an exploratory project was introduced to exploit the small pelagic resource. The catch was generally very low except for 2006, when 293 t was reported (MOF 2007); after that, the catches were zero from 2007 to 2010 (MOF 2012).

From exported dry sardines and anchovies and fishmeal, Ben-Yami (1964) calculated the total catch using the ratio 4:1 of gross catch to final processed product. For the reconstruction, first the data were assigned to the corresponding Gregorian calendar based on the months the fishing occurred, i.e., from October to May, 3/8 of the catch reported for Ge’ez calendar year 1951 was allocated to Gregorian calendar year 1958 and 5/8 to 1959. Based on the yearly catch calculated for 1959–1962, the ratio of catch for October – December to January – May was computed to be 1:1.9; the few months catch for 1958 and 1963 were scaled up to the whole year using this ratio. The landings in Assab were estimated to be half that of Massawa (Ben-Yami 1964). The national total was calculated by adding the Massawa and Assab landings, which were the only two places where the beach seine catch was landed. To the total landed catch, 5% was added to account for unreported catch from 1950 to 1975 when the fishery was active. Because of fishmeal production, there was no discard in this fishery; however, part of the catch was spoiled by rain during drying, some eaten by birds and some spoiled due to bad handling. Based on interviews with fishers, the unreported catch was estimated to be 5% of the landed catch, a conservative estimate (Tesfamichael and Pitcher 2007). The same procedure was followed for 1964–1967 from Grofit (1971) and 1968–1975 from Sanders and Morgan (1989). For the years 1956 and 1957, interpolations were used to match the decline of the fishery in those years (Figure 2; Table 1).

Table 1. Summary of the Eritrean beach seine fishery reconstruction procedures.Period Dry fish and fishmeal Fresh fish

Source/Remarks Unreported (%)

Reported(t)

Source/Remarks Unrecported (%)

1950-55 Johnson (1956) 5 400 Equal to 1960-62 01956-57 Interpolation 400 Equal to 1960-62 01958-59 Ben-Yami (1964) 5 400 Equal to 1960-62 01960-63 Ben-Yami (1964) 5 400 Ben-Yam (1964) 01964-66 Grofit (1971) 5 400 Equal to 1960-62 01967-68 Grofit (1971);

Sanders and Morgan (1989)5 400 Equal to 1960-62 30

1969-71 Sanders and Morgan (1989) 5 400 Equal to 1960-62 01972-75 Sanders and Morgan (1989) 5 Interpolation 301976-78 FAO (2010) Interpolation 301979 FAO (2010) 331 Sanders and Morgan (1989) 301980 FAO (2010) 269 Sanders and Morgan (1989) 301981-87 FAO (2010) Interpolation 301988-89 Zero catch Interpolation 301990-99 Zero catch Zero catch 02000-10 MOF (2012) Zero catch 0

Figure 2. Sources used for catch reconstruction of the Eritrean beach seine fishery for the export market from 1950 to 2010.

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The species composition of the total catch was calculated based on the information that the landings in Massawa were generally equal amounts of anchovy and sardine; however, for Assab, it was all anchovy (Ben-Yami 1964). As the Massawa landings were double those of Assab, a ratio of 1:2 sardine to anchovies was used for 1950–1971, except for 1967 and 1968, where all the catch was allocated to anchovy. According to Grofit (1971), export of fishmeal stopped in 1967 due to the closure of the Suez Canal, which was the main route to the market in Europe; then, all the fisheries switched to anchovy fishing, shark fishing and handlining. Fishmeal export started again in 1969, as alternative markets were found in neighbouring countries and Asia (Grofit 1971), resulting in increase in catch (Figure 2). Thus, the ratio 1:2 for sardine and anchovies was used. Although the exact year when the fishmeal industry stopped again was not given, we assume that it was in 1972, based on the qualitative information that Giudicelli (1984) gave about the decline in the industry and the fact that the catch was low, back to the same level as in 1968 when fishmeal export stopped. Thus, the catch from 1972 to 1976 and 1980-1987 was allocated only to anchovies (Figure 3, Appendix Table A1). The common species were anchovies: Encrasicholina heteroloba and Thryssa baelama, and sardine Herklotsichthys quadrimaculatus. After 1987, neither anchovy nor sardine was landed as the whole industry was shut down and whatever was reported for beach seine was assumed to be for fresh fish consumption.

The average annual catch of beach seine for fresh fish for direct human consumption was estimated to be 400 t in the early years (Ben-Yami 1964). This value was used from 1950 to 1972, as the fishery was more or less stable during that period. Two data points were available for 1979 and 1980, 331 t and 269 t, respectively (Sanders and Morgan 1989). These data were recorded at the main landing sites where fish were sold through formal market channels, which would usually be delivered to the fish market in Asmara, the capital city of Eritrea. These data points were given in Ge’ez calendar, hence converted to the Gregorian calendar; they pertained only to fresh food fish, as fishmeal and dry fish were not being produced at that time, according to interviews conducted by the first author, and Giudicelli (1984). For the years 1973 to 1979, interpolation was applied to estimate the catch, which suggested a slight decline in the fishery during those years. The fishery stopped in 1990, as was the case with some of the other fisheries as well, due to civil unrest. From 1981 to 1989, the catch was estimated by interpolation. Not all fish that was caught by the beach seine fishery for fresh fish went through the proper market channels where data recordings were possible. The low grade fish were either sold in bulk to the fish meal processing plants, when they were operating, or sold through the informal markets to the local people on the coast. Sometimes not all the low grade fish could be sold to the locals; the rest would be thrown away. For 1967, 1968 and since 1972, when there was not production of fishmeal, the unrecorded catch (consisting mainly of kawakawa (Euthynnus affinis), which did not fetch a good price in the market) was estimated to amount to 30% of the landed catch (Giudicelli 1984). This was added to the landings of food fish by beach seine to calculate the total catch. Table (1) summarizes the procedure of the beach seine catch reconstruction, while Figure (4) shows the reconstructed catch and the sources and interpolations of beach seine fishery for local consumption.

The species composition of fresh fish beach seining for direct consumption was calculated based on data given in Ben-Yami (1964), who reported the catch to consist of jacks (Carangidae; 62.5%), queen fish (Scomberoides spp.; 25%), and mullets (Mugillidae; 12.5%). The unrecorded catches were assumed to consist of 67% kawakawa (Euthynnus affinis) and the rest a mix of many taxa with minor contributions, based on the qualitative information given in Giudicelli (1984) (Figure 5). The overall catch composition of the beach seine fishery is given in Table (A2).

Figure 5. Catch composition of the Eritrean beach seine fishery for local consumption from 1950 to 2010.

Figure 4. Sources used for the catch reconstruction of the Eritrean beach seine fishery for local consumption from 1950 to 2010. The star in 1972 indicates the end of the 400 t assumed catch.

Figure 3. Catch composition of the Eritrean beach seine fishery for export markets from 1950 to 2010.

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Handline fishery

Ben-Yami (1964) estimated the annual landings of the handline fishery to be 300 t, which was used from 1950 to 1965, except for 1960 and 1961, where 100 t were added to reflect the extra effort in those years. In 1966, some fishers, who used to do beach seining, switched to handlining and the catch increased to 1,000 t annually (Grofit 1971). This value was used from 1966 to 1976, a period when the fishery did not change much. In 1977, war broke out in the coastal area and disrupted the artisanal fisheries. After 1977, estimates were given for two years, 1981 and 1983, by Giudicelli (1984), while Sanders and Morgan (1989) compiled total landings from 1977 to 1986. Those landings were assigned only to the artisanal fisheries, which were predominantly handline and gillnet fisheries, as they were the only fisheries operating mainly to supply local communities. Gillnet started to be prominent only later, in the 1970s (Giudicelli 1984). Total artisanal landing for 1992–1995 was obtained from Tesfamichael and Zeremariam (1998) and for 1996–2010 from the Eritrean Ministry of Fisheries database (MOF 2007, 2012), which separated the artisanal catch by gear type.

This fishery uses very selective gear, thus it hardly has any discard. However, not all the fish that is caught is reported in the formal channels. Some of the fish is directly sold to people in areas where data recording does not occur. This is in addition to part of the catch being given freely to family and friends, and which is treated separately, as subsistence fishery, in this report. Based on interviews with old fishers who were active in the 1950s and 1960s, we found out that up to half of their catch did not go to formal market channels (landing sites). Thus, we assumed that the total catch to be double of what was reported, as was also done in a survey of artisanal fisheries in neighbouring Sudan (Chakraborty 1983). Thus, the unreported catch was estimated to be 300 t∙year-1 from 1950 to 1976. From 1966 to 1976, the catches given by Grofit (1971) were taken as an estimate of the total, including unreported. Given that Ben-Yami (1964) estimated a maximum of 700 t, including unreported catch and that, after 1991, when the fishery again was in full swing, an annual maximum of 1,300 t was being caught, the 1,000 t∙year-1 estimate by Grofit (1971) from 1966 to 1976 seemed reasonable to be the total catch. For the period 1977-2010, unreported catch was estimated based on Giudicelli (1984), who estimated the landings to be 328 t for 1981. Based on the assumption that about half of the catch did not go through proper channels, i.e., remained unrecorded, the unreported catch was estimated to be 328 t for 1981. For the rest of the years from 1977 to 2010, population size was used as a proxy to calculate the total unreported catch, here assumed to go only to local consumption. Hence, the unreported catch was calculated by multiplying 328 t by the ratio of population size of the respective year to 1981. Figure (6) shows our estimates of the unreported catch of fresh fish artisanal fisheries, i.e., handline and gillnet fisheries. In 1990 and 1991, the whole of Eritrea was at the peak of the independence war and fishing was much reduced; however, the coastal people were still fishing, and supplied some of the local demand. Thus, we assumed the amount caught to be equal to the unreported catch estimated from demographics.

The artisanal catch from 1977 to 1995 was not divided between handline and gillnet. The first division appeared in the Ministry of Fisheries database starting in 1996 (MOF 2007), and the average ratio of handline to gillnet was 3.13:1. This ratio was used to divide the reconstructed total artisanal landing from 1990 to 1995. From 1977 to 1986, a ratio of 4.5:1 was used as gillnetting was just starting and more catch came from handlining. No data were available from 1987 to 1989, hence they were interpolated (Figure 7).

For 1983, Giudicelli (1984) estimated the total artisanal catch to be around 2,000 t, based on the number of boats during his visit to the Eritrean coast and catch rates from Yemen calculated by Walczak (1977). In his report, Giudicelli (1984) stated that the fishery showed some sign of renewal, following its decline at the end of the 1970s, with the fishers using mainly handline and gillnet, and targeting prime fresh fish species such as snappers, groupers and emperors. However, we fear this estimate is too

Figure 7. Sources used for the catch reconstruction of the Eritrean handline fishery from 1950 to 2010.

Figure 6. Estimation of the unreported catch of the Eritrean artisanal fisheries (1950-2010), using handline and gillnet, with extrapolation based on demographics (see text).

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high: first, the total catch of prime fresh fish, prior to the decline, was 1,000 t according to Grofit (1971). Secondly, the maximum catch was 1,319 t in 2002 when the fishery flourished again after Eritrean independence. Hence, we assume the 2,000 t reported by Giudicelli (1984) were an over estimate, and reduced it to 1,000 t, with an estimated unreported catch of 346 t. Figure (7) shows the reconstructed catch, with interpolations and sources. The decline after 2003 is mainly because fishers shifted from handlining to the more lucrative sea cucumber fishery.

The only taxonomic composition record for the early catches was given to be 57.2% snappers (Lutjanidae), 16.9% groupers (Serranidae), 15.6% scavengers or emperors (Lethrinidae) and 10.3% other taxa (Ben-Yami 1964). These ratios were used from 1950 to 1989. From 1996 to 2004 a detailed catch composition of the handline fishery was available (MOF 2007), and its weighted average was used from 1990 to 1995 and from 2005 to 2010 (Figure 8 and Table A3). Since the list of taxa in the catch composition was usually very large, not all of them can be represented in the figures. Throughout this report, only the major groups are presented in the graph, while more detailed catch composition data are given in the appendix tables.

Gillnet fishery

The gillnet fishery for shark is reported separately (see below); here only the gillnet fishery for fresh food fish is reported. According to Giudicelli (1984) and interviews by the senior author with fishers, gillnets for non-shark fishery, although used for a long time, started to be important to artisanal fishers around 1977. The gillnet catch was calculated from the total, including unreported catch, of the artisanal fishery (see the handline fishery section for the calculations) by dividing it by 5.5 from 1977 to 1986 and by 4.13 from 1990 to 1995, Gillnet landings are given separately in the MOF database for 1996 to 2010 (MOF 2007, 2012). From 1996 to 2010, the unreported catch ratio of gillnet fishery from the total unreported catch of artisanal fishery as described above (see Figure 6) was taken to be proportional to the gillnet to handling reported catch. For the period from 1987 to 1989, the gillnet fishery catch was interpolated (Figure 9). The catch composition was calculated based on data from the database of the Ministry of Fisheries of Eritrea from 1996 to 2004 (MOF 2007). For the rest of the years, the weighted average of 1996–2004 was used (Figure 10 and Table A4). The low catch in 2004 is explained by the fact that the sea cucumber fishery was the first choice for fishers to be involved in because of its high economic return.

Shark fishery

The shark fishery was active for a long time; however, the earliest available catch estimates were from 1963 to 1968 (Grofit 1971); these catches were aggregated with landings of small pelagics. However, from 1966 to 1968, they were disaggregated, and the ratio of shark to small pelagics for 1966 and 1967 were used to disaggregate the landings of 1963–1965. The 1968 ratio was not included because many fishers switched from beach seining for small pelagics to shark fishery by the sudden closure of the Suez Canal, which resulted in a spike in shark catch in 1968. From 1969 to 1977, landings were taken from Sanders and Morgan (1989). All catch reports were given in Ge’ez calendar and were converted to Gregorian calendar based on the fact that in the past, the shark fishery operated mainly during the hot months, i.e., alternating with the beach seine fishery.

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (1

0 t)3

0.0

0.4

0.8

1.2

Snappers

Groupers

Emperors

Others

JacksNarrow-barred Spanish mackerel

Two-spot red snapper

Mackerels

Figure 10. Catch composition of the Eritrean gillnet fishery from 1950 to 2010.

Figure 9. Sources used for the catch reconstruction of the Eritrean gillnet fishery from 1950 to 2010.

Figure 8. Catch composition of the Eritrean handline fishery from 1950 to 2010.

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Catches from 1950 to 1962 were assumed to be the same as in 1963, because the shark fishery had been active for a long time in the area and was relatively stable during that period. Shark catch from 1996 to 2010 were obtained from the MOF database (MOF 2007, 2012). However, the shark catch reported are not all that is caught; a conservative estimate of unreported catch to be 10% of the reported catch was used. The data gap between 1977 and 1996 was filled by estimating the catch to be 14 t·year-1, which is the amount for both 1977 and 1996. This is a reasonable estimate as interviews with fishers revealed that the shark fishery continued during those years (Figure 11).

Sea cucumber fishery

Although the main and latest fishery for sea cucumber started mainly around 2000 (Tewelde and Woldai 2007), catches of sea cucumber together with snail nail and pearl were reported from 1962 to 1965 (Grofit 1971). The average of the total catch over those years was 16 t and was taken to be the annual catch from 1950 to 1976. Out of the 16 t, 15 t were assumed to be sea cucumber (mainly Holothuria spp. and Actinopyga spp.) while the rest is assumed, based on interviews, to be snail nail and pearl. From 1998 to 2006, data were available from Tewelde and Woldai (2007), who reported on an extensive socio-economic survey of the Eritrean sea cucumber fishery. Their catch estimates are likely to be reliable, because the fishery is for export and only few companies were involved. Data were not available from 2007 to 2010, and we used the value of 2006 (Figure 12). All sea cucumber data were expressed as dry weight, after the boiling and drying processes and were converted to wet weight based on data from Purcell et al. (2009). Here we used the mean of their conversion data for boiled and dried Holothuria spp. and Actinopyga spp. (i.e., 10.2% of wet weight).

Other artisanal fisheries

The fisheries included in this category are trochus shells, lobsters, shell fish nail and pearls. Earliest trochus shell collection data available were from Reynolds et al. (1993), who reported 300 t for 1955; the same amount was assumed for 1950–1954 during which the fishery was relatively stable. Data from 1958 to 1962 and 1963 to 1968 were available from Ben-Yami (1964) and Grofit (1971), respectively. From 1969 to 1974 and 1977, data were obtained from Reynolds et al. (1993). From 1978 to 2010, no data were available on shell collection; however, the collection of shell by women and young children in shallow water was still occurring. Thus, a minimum of 1 t·year-1 was assumed for that period. Interpolation was used to estimate the catches for 1956, 1957, 1975 and 1976 (Figure 13).

Figure 12. Sources used for the catch reconstruction of the Eritrean sea cucumber fishery from 1950 to 2010.

Figure 11. Sources used for the catch reconstruction of the Eritrean shark fishery from 1950 to 2010.

Figure 13. Sources used for the catch reconstruction of the Eritrean trochus shell fishery from 1950 to 2010.

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Grofit (1971) reported an annual catch of 5 t of lobster, and this value is used from 1950 to 1977. For the period from 1978 to 2010, a minimum catch of 1 t·year-1 was estimated, which is close to the reports from MOF (2007). Based on observations, interviews and field notes of Eritrean fishery officers, the snail nails and pearl catch was estimated at a conservative minimum value of 1 t·year-1 from 1950 to 2010.

Subsistence fishery

As the source of the subsistence catch is the artisanal fishery catch, its magnitude and composition was estimated as a proportion of the artisanal catch. However, not all the fisheries categorized in the artisanal fishery are represented in the subsistence fishery. The catch or product of the artisanal fishery which are targeted for export–such as shark fin, sea cucumber, shell fishes – are not given freely to family and friends. These products do not contribute to the local food supply. Hence, only the gillnet and handline fisheries were considered for the subsistence fishery reconstruction. For estimating the subsistence fishery, it was divided into two periods. First from 1950 to 1992, when the gillnet and handline fisheries were less commercialized and a good proportion of the catch was given freely to sustain the local communities. Although motorization of boats, which triggers the commercialization of catches, started in the 1960s, we set the less-commercialized period until 1992, because the independence war of Eritrea affected the commercialization of the fishery and kept it very local. We allocated a value equal to 30% of the reconstructed catch of gillnet and handline fisheries to be the amount of subsistence catch from 1950-1992. This is a very conservative value, as interviews with fishers and managers indicated that about half of the catch used to be given for free. The percentage was reduced to 20% for 1993, when fishery infrastructures and markets were flourishing after independence, and for 2010, we assumed the subsistence catch to be only 10% of gillnet and handline fisheries catch. The percentages for the years between 1993 and 2010 were interpolated (Figure 14 and Table A5).

Industrial fishery

Trawl fishery

Since the shrimp fishery was reported separately for most of the period, we estimated it separately from the finfish trawl fishery. A total of 30 t of shrimp were landed from inshore waters around Massawa during the early years (Grofit 1971), and this value was assumed to apply from 1950 to 1970 (Figure 15). The shrimp trawlers were small local boats. Grofit (1971) also reported that shrimp accounted for only 10% of the total catch, which was used to calculate the discard amount to be 270 t∙year-1, which is similar to the estimate by Ben-Yami (1964) for 1960–1963. The main shrimp species caught were Penaeus semisulcatus, Marsupenaeus japonicus, Melicertus latisulcatus and Metapenaeus monoceros, while the discard was composed of small fishes belonging mainly to the families Leiognathidae, Fistulariidae and Trichiuridae. Sanders and Morgan (1989) reported landings of 20 t for 1976, from which the discard was calculated to be 180 t. Giudicelli (1984) reported that trawling totally disappeared by the beginning of the 1980s; as a result, a catch of zero was assigned from 1981 to 1995. The catch from 1971 to 1975 and 1977 to 1980 were interpolated. The first shrimp trawl catch after Eritrea’s independence occurred in 1996 and it was not reported separately as ‘shrimp catch’ as it was in the past. Rather, it was a component of the trawlers’ catch; thus, for 1996-2010, the shrimp catch was calculated from the total catch composition of trawlers (MOF 2007, 2012).

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (1

0 t)3

0

0.1

0.2

0.3

0.4

Lutjanidae

Serranidae

Lethrinidae

Others

Carangidae

Scomberomoruscommerson

Lutjanus boharScomberoidescommersonnianus

Scombridae

Figure 15. Sources used for the catch reconstruction of shrimp fishery in the Eritrean Red Sea from 1950 to 2010.

Figure 14. Catch composition of the subsistence catch of Eritrea from 1950 to 2010.

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The highest catch of shrimp was in 2001, more than 700 t (Figure 15). This is higher than the generally cited 500 t maximum sustainable yield (MSY) of shrimp for Eritrea (Giudicelli 1984). This raises questions about the MSY estimate, which was made in the 1970s and 1980s and based on little research. In addition, the fishery has expanded spatially, i.e., new fishing grounds are fished now, which were not known during the limited surveys of the 1970s and 1980s.

Before the 1970s, the trawlers operating along the Eritrean coast came from Israel, except the small inshore boats mainly for shrimp. The first report of offshore trawling for fish, as opposed to inshore for shrimp, was for the first experimental Israeli trawling off the coast of Eritrea in 1958 (Ben-Yami 1964). The report also contained data of landings until 1962. The landings for 1963 – 1967 were obtained from Grofit (1971). Data from 1968 to 1980 were obtained from Sanders and Morgan (1989), who reported the landings for 1969/70 to be only 100 t. This data point was not used as there was no justification for the sudden drop. It is possible this is a typographic error, hence the average of the landings of the years before and after was taken instead. All records were adjusted from the Ge’ez calendar to the Gregorian calendar. Giudicelli (1984) reported that trawlers were not operating in the 1980s; as a result, the catch was zero until 1994, when trawler landings appeared again. Data for 1994 and 1995 were taken from Tesfamichael and Zeremariam (1998) and those for 1996–2010 from the MOF database (MOF 2007, 2012). Figure (16) shows the reconstructed total trawl landings excluding shrimp.

In addition to the shrimp trawl catch, as described above and shown in Figure (15), the taxonomic composition of the retained catch of non shrimp trawling was calculated from 1958 to 1980 using the ratios given in Ben-Yami (1964). MOF (2007) reported catch composition data from 1996 to 2006. They were used here as presented, while for 1994 and 1995, and 2007-2010 the weighted average ratios of 1996–2006 were used (Figure 17 and Table A6). The dominant taxa are lizard fish and threadfin bream, which account for more than 50% of the total retained catch. There are two clearly separate phases in the trawl fishery in the Eritrea Red Sea based on the origin of the trawlers. The first, from late the 1950s to the end of the 1970s was when trawling was done by Israeli trawlers; the second from the mid-1990s to 2010 was mainly by Egyptian trawlers (Tesfamichael and Mehanna 2012).

The trawl fishery has large amount of discards, and hence they were estimated separately. For the earlier period (1950-1980), the discards were calculated from two separate datasets: trawling for fish and shrimp trawling. For the former, the discarded catch amounted to 44% of the total catch (Ben-Yami 1964), while for the latter it was 90% of total catch (Ben-Yami 1964; Grofit 1971). For the period from 1981 to 2010, unlike the earlier period, there was not separate shrimp dataset, hence discards were calculated all together. Discard data were available from the MOF database from 1996 to 2003 (MOF 2007), and the average of those years, i.e., 43.5% (similar to the value from 1950 to 1980) was used for 1994, 1995 and 2004–2010. As there was no trawling from 1981 to 1993, discards were zero for that period. Once the total discarded catch amounts were established, the next step was to disaggregate them to their taxonomic components. There was no information on the composition of discarded catch from Eritrea during our analysis of Eritrean catch. Thus, it was calculated using data from Yemen (Tesfamichael et al. 2012), which has similar ecosystems and trawling practices. Two separate periods were considered in calculating the composition of discarded catches: 1950 – 1957 and 1958 – 2010. In the earlier period, the sole target of trawling was shrimps and everything else was discarded. In the second period, however, some fish were retained; hence they were eliminated from the calculation and the ratios of the remaining taxa were scaled up to make the total 1 (Figure 18 and Table A7).

Figure 18. Composition of the discarded catch of trawl fisheries in the Eritrean Red Sea from 1950 to 2010.

Figure 17. Catch composition of the retained catch of trawl fisheries in the Eritrean Red Sea from 1950 to 2010.

Figure 16. Sources used for the catch reconstruction of trawl fishery (excluding shrimp) in the Eritrean Red Sea from 1950 to 2010.

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Longline fishery

Before the 1970s, different reports mentioned that longlines were being used in the shark fishery. The recent longline fishery started in 1999 and targeted non-shark fishes that dwell in and near coral reefs. Since the shark fishery is presented separately in this report, we describe here only the recent longline fishery. Catch data were available from 1999 to 2010 (MOF 2007, 2012). Based on the first author’s observation onboard longline fishing boats, about 10% of the total catch was discarded, which included mainly top predators such as sharks. The composition of the landed catch, i.e., excluding discard, was available from the MOF database for 2000, 2001, 2004 and 2006 (MOF 2007). The 10% discard was added to the unidentified group ‘others’. For years for which catch composition data were not available, the weighted mean of the reported composition was used (Figure 19 and Table A8).

Comparing reconstructed catches with FAO data

The reconstructed catch data were compared to what Eritrea (Ethiopia pre 1993) reported to the FAO (http://www.fao.org/fishery/statistics/software/fishstat/en). After the total catch and composition of each gear were reconstructed, whenever the contribution of ‘others’ was more than 10%, it was reduced to 10% and the difference distributed to the rest of the taxa proportional to their values. The comparison was done at taxonomic level. There were few taxa that were in the FAO data but not in the reconstructed catch. They were allocated to the appropriate sector. Their amount in the reconstructed catch was taken to be the same proportion they had in the total FAO data. The amounts were later deducted from the ‘others’ of the sector to which they were allocated. Since the FAO data were only a total by taxon, they were divided into the different gears based on the proportion of the taxa for each gear in the reconstructed catch. Then each taxon in the reconstructed data was compared with its corresponding value in the FAO data. The part of the reconstructed catch that is accounted in the FAO data is referred as ‘reported catch’ in our result. When the catch of any taxon was higher in the reconstructed dataset compared to the FAO data, which was in most cases, the difference was taken to be unreported catch. In a few incidences, the FAO data were higher than the reconstructed catch, and were taken as over-reporting.

results

The reconstructed total fisheries catch in the Eritrean Red Sea Exclusive Economic Zone (EEZ) by the sectors (both domestic and foreign vessels) is shown in Figure (20) and Appendix Table (A9), together with the total reported catch by FAO on behalf of Eritrea. The fishery went through major changes. The total catch was quite high in the 1950s and the late 1960s. It started to decline in the early 1970s and remained very low in the 1970s and 1980s, but started to increase again in the mid-1990s. The artisanal fisheries were dominant by far (76%), followed by the industrial fisheries (22%, 12% retained and 10% discards). The industrial fishery had the highest contribution from 1994 to 2006, where it contributed more than 50% of the total catch (except for 1997 and 1998). The trawl fisheries’ contribution varied depending on whether they received permits.

The reported catch (part of the reconstructed catch accounted in the FAO data) represented 38% of the total catch, which obviously brings the accuracy of the reported data into question (Figure 21, Table A10). The unreported landed catch had the highest contribution to the total catch (52%). The major part of the reported catch was the beach-seine fishery in the 1950s and 1960s (Figure 22), which was under-reported in the FAO data. The discards, which are not reported in the FAO database, contributed 10%, and they became more visible starting the late 1990s, with the increase in the trawl fishery.

Figure 20. Reconstructed catch by sectors and total catch as reported to FAO by Eritrea in its Red Sea EEZ from 1950 to 2010.

Figure 19. Catch composition of the Eritrean longline fishery from 1950 to 2010.

Eritrea - Tesfamichael and Mohamud 83

Taking the individual gears, the main contributor to the high catch in the 1950s and 1960s was the beach seine fishery for small pelagic fishes (Figure 22, Table A11), while the increase in total catch after the mid-1990s was mainly due to bottom trawling. The small-scale artisanal fisheries, which consisted mainly of handlining and gillnetting, were the most steady in their operation. The shark and sea cucumber fisheries made relatively high contributions to the total catch in the late 1960s and early 2000s, respectively (Figure 22). Once these fisheries declined, they did not recover, despite a strong demand. The recent high does not match the highest catch in the early period, mainly because of the absence of the small pelagic purse seine fishery.

The taxonomic composition of the total catch is shown in Figure (23) and the corresponding data are given in Table (A12). The small pelagic fishes (anchovies and sardines) dominated the 1950s and 1960s, while demersal fishes dominated after 1990. The changes in species composition over time are explained largely by the changes in the fishing gear dominating during the periods in question. The catch composition after 1990 shows more diverse groups with sizable catches, unlike in the early years which were dominated by a few taxa. Discards, which are usually omitted from official reports, were high, especially in the latter years. This is due to the fact that demersal trawling became prominent in recent years, and the absence of an industry to make use of the bycatch they generate, e.g. through processing it to fishmeal.

disCussion

The fisheries in Eritrea’s EEZ went through some major fluctuations, with a relatively high total catch up to the mid-1950s, followed by a decline and a recovery starting in the mid-1960s. Then it went through a rapid decline starting in the early 1970s and stayed very low until the beginning of the 1990s. Towards the end of the 1990s, the catch increased again, but not to the high levels it reached in the early years. These fluctuations are explained by major geopolitical changes and market availability for the fishery products. This is in contrast to fisheries that have more stable political and market atmosphere, where the changes that occur are explained in terms of the changes in the fishery resources. In the latter case, the changes are not usually as abrupt as we see them in the Eritrean case.

The first decline, which occurred in 1955, was due to the fact that the small pelagic beach seine fishery, which was dominant at the time, used to be conducted by fishers from Yemen, who were banned from Eritrean waters in late 1954 (Ben-Yami 1964). The (small) next peak, which occurred in 1961, was due to the Yemeni fishers being allowed back into Eritrean waters, but only for one year. Then the fishery recovered, and attained a new peak in 1966, as a result of motorization that allowed the fishers to increase their catch (Grofit 1971). After 1966, a decline occurred, especially in the beach seining fishery, mainly due to the closure of the Suez Canal, due to the 6-Day War between Israel and the neighbouring Arab countries. The Suez Canal was the main route for the export of the beach seine fisheries product, i.e., fishmeal, which was exclusively export-oriented. Although the beach seine fishery declined rapidly after 1966, some of the decline was compensated by the growth of the shark fishery. The next peak was in 1971, and is attributed to the creation of alternative markets in neighbouring countries and Asia for the beach seine fishery catch (Grofit 1971).

The contribution of foreign trawl fishery was important from 1961 to 1971. The major reason for the strong decline after 1971 was political instability. As the Eritrean independence war was gaining momentum, it expanded to the coastal area. As a result, the Ethiopian government, who was in control in Eritrea at the time, declared martial law.

Figure 22. Total catches of the fisheries in the Red Sea EEZ of Eritrea by different gears from 1950 to 2010.

Figure 21. Reconstructed catch by components in the Red Sea EEZ of Eritrea from 1950 to 2010. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.

Figure 23. Taxonomic composition of the reconstructed total catch of the fisheries in the Red Sea EEZ of Eritrea from 1950 to 2010.

84

The fishery infrastructure was destroyed and most of the foreign companies involved in the fishing industry, such as trawling and fishmeal processing plants, left the country. Many local fishers also went into exile in neighbouring countries. Eritrea became independent in 1991, and soon after, the fishery industry started to recuperate. The first peak after 1991 was in 1995 as some foreign trawlers started to operate in Eritrean waters again. They stopped in 1997, however, causing a decline in total catch. But they reinitiated their operations in 1998 and increased rapidly to the next peak in 2000. After 2000, the decline in the trawl fishery catch was partly compensated by the rapidly increasing catch of sea cucumber.

Overall, the most stable fishery throughout the whole period was the artisanal fishery, which targets fish for direct human consumption, particularly handlining, and the gillnet fishery. Most of the fresh fish artisanal fisheries catch is sold in local markets. Some of it is distributed freely, and this sustenance catch goes straight to the households. Fish is the main staple food for the coastal people and that is why handline and gillnet fisheries were active even during the war. The fisheries that showed rapid increase and decline (even while the demand was still high) were those that targeted a small number of vulnerable species, i.e., the shark and sea cucumber fisheries. These two fisheries are similar in many ways. They both yield a dry product, which allows fishers to remain fishing at sea for several days, unlike fisheries that yield fresh product, which forces the fishers to land their catch before it is spoiled. Second, their products are exclusively for export and the demand for shark fin and sea cucumber has been increasing globally. As these products have high market prices, fishers preferred them over other targets, except in the 1950s and 1960s, where the high catch of beach seining made this operation very profitable. The rapid decline of these shark and sea cucumbers fisheries, despite a high effort level, suggest much diminished populations of the target groups, which demands immediate research and action.

This is, to our knowledge, the first attempt to document and standardize the fisheries catches in the Eritrean Red Sea EEZ (both by local and foreign vessels) comprehensively over a long time series (1950–2010), with each gear and type of fishery covered and their catch composition established. We believe this is a crucial step for the assessment of the existing fisheries, and the potential development of new ones (Tesfamichael 2012). The fisheries in Eritrea’s waters went through several shifts due to geopolitical changes and that has affected how data have been recorded – or not. For those years where data were not available, it was necessary to infer catches from other years, combined with the best knowledge available to us regarding what kind of changes had happened during those years. We used all the reports we could find to understand the fisheries in Eritrea and also interviewed more than 200 fishers and managers (Tesfamichael et al. in press). Our procedures and assumptions are transparent and open to objective criticism. We considered it unacceptable to simply ignore certain fisheries or years from consideration because detailed data were not available (Tesfamichael and Pitcher 2006).

However, one aspect that remains problematic is illegal fisheries. Here, we partially account for them through a portion of the unreported catch. Some of the above results may thus change in the future, when new data become available.

aCknowledgements

We would like to express our thanks to the Ministry of Fisheries of Eritrea for their cooperation in using their fishery database, reports and other documents. Heartfelt thanks also go to assistants during the field work: Ahmed, Aron, Bokeretsion and Yonathan. This research was supported by Sea Around Us, a scientific collaboration between the University of British Columbia and The Pew Charitable Trusts. Additional support was obtained from Eritrea’s Coastal, Marine & Island Biodiversity Conservation Project (ECMIB).

referenCes

Ben-Yami M (1964) Report on the Fisheries in Ethiopia. Min. of Foreign Affairs, Dep. for International Cooperation, Jerusalem. 106 p.

Campbell G (1993) The structure of trade in Madagascar, 1750-1810. The International Journal of African Historical Studies 26(1): 111-148.

Chakraborty D (1983) Marine fisheries statistics in Sudan–an expanded plan of development. FAO, Rome. 39 p.FAO (2010) FishStatJ–software for fishery statistical time series. Food and Agriculture Organization of the United

Nations (FAO), Rome. Available at: http://www.fao.org/fishery/statistics/software/fishstatj/en [Accessed: March 13, 2010].

Giudicelli M (1984) The Ethiopian fisheries: situation, development needs and opportunities. A report prepared for the Fishing Planning and Development Project., FAO, Rome. 157 p.

Grofit E (1971) The Red-Sea fisheries of Ethiopia (1966–1969). Min. of Foreign Affairs, Dep. for International cooperation, Jerusalem. 82 p.

Johnson R (1956) Preliminary survey of Ethiopian Fisheries (USOM, Ethiopia). Ethiopian Fisheries Division, Addis Ababa.

MOF (2007) Eritrean Fisheries Database System. Ministry of Fisheries, Massawa, EritreaMOF (2012) Eritrean Fisheries Database System. Ministry of Fisheries, Massawa, EritreaPurcell SW, Gossuin H and Agudo NS (2009) Changes in weight and length of sea cucumbers during conversion

to processed beche-de-mer: Filling gaps for some exploited tropical species. SPC Beche-de-mer Information Bulletin 29: 3–6.

Eritrea - Tesfamichael and Mohamud 85

Reynolds JE, Appleton J, Bellemans MS, Bozon A and Christy LC (1993) The fisheries of Eritrea, pt. 1: Sector review. pt. 2: Proposed national fisheries strategy and development programme. FAO, Rome.

Sanders MJ and Morgan GR (1989) Review of the fisheries resources of the Red Sea and Gulf of Aden. FAO, Rome. 138 p.

Tesfamichael D (2001) Characterising the Eritrean artisanal fisheries using catch and effort data analysis. MSc, Wageningen University, Fish culture and fisheries group, Wageningen. 42 p.

Tesfamichael D (2012) Assessment of the Red Sea ecosystem with emphasis on fisheries. PhD, University of British Columbia, Resource Management and Environmental Studies, Vancouver. 241 p.

Tesfamichael D and Mehanna SF (2012) Reconstructing Red Sea fisheries of Egypt: Heavy investment and fisheries. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D and Pauly D (2011) Learning from the Past for Future Policy: Approaches to Time-series Catch Data Reconstruction. Western Indian Ocean J. Mar. Sci. 10(2): 99-106.

Tesfamichael D and Pitcher TJ (2006) Multidisciplinary evaluation of the sustainability of Red Sea fisheries using Rapfish. Fisheries Research 78(2-3): 227-235.

Tesfamichael D and Pitcher TJ (2007) Estimating the unreported catch of Eritrean Red Sea fisheries. African Journal of Marine Science 29(1): 55-63.

Tesfamichael D, Pitcher TJ and Pauly D (in press) Assessing changes in fisheries using fishers’ knowledge to generate long time series of catch rates: a case study from the Red Sea. Ecology and society.

Tesfamichael D, Rossing P and Awadh H (2012) The marine fisheries of Yemen with emphasis on the Red Sea and cooperatives. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D and Zeremariam S (1998) The status of fisheries in Eritrea. p. 174 In Coetzee L, Gon J and Kulongowski C (eds.), African Fishes and Fisheries Diversity and Utilisation. Poissons et Peches Africains Diversite et Utilisation; International Conference for the Paradi Association and The Fisheries Society of Africa, Grahamstown (South Africa), 13-18 Sept 1998. FISA/PARADI, Grahamstown (South Africa).

Tewelde M and Woldai M (2007) Socioeconomic Study of the Sea Cucumbers Fisheries in Eritrea. Eritrea’s Coastal, Marine & Island Biodiversity Conservation Project (ECMIB), Massawa. 35 p.

Walczak P (1977) The Yemen Arab Republic. A study of the marine resources of the Yemen ArabRepublic. A report prepared for the Fisheries Development Project. FAO, Rome. 67 p.

Walter RC, Buffler RT, Bruggemann JH, Guillaume MMM, Berhe SM, Negassi B, Libsekal Y, Cheng H, Edwards RL, von Cosel R, Neraudeau D and Gagnon M (2000) Early human occupation of the Red Sea coast of Eritrea during the last interglacial. Nature 405(6782): 65-69.

86 Appendix Table A1. Catch composition (in tonnes) of the Eritrean beach seine fishery for export markets from 1950 to 2010.

Year Engraulidae Clupeidae1950 17,500 8,7501951 17,500 8,7501952 17,500 8,7501953 17,500 8,7501954 17,500 8,7501955 17,500 8,7501956 15,173 7,5871957 12,846 6,4231958 10,519 5,2601959 7,731 3,8651960 6,681 3,3401961 8,951 4,4761962 6,366 3,1831963 5,505 2,7531964 6,869 3,4341965 11,803 5,9021966 13,312 6,6561967 14,466 01968 8,006 01969 7,350 3,6751970 10,675 5,3381971 11,200 5,6001972 8,006 01973 2,691 01974 3,084 01975 1,411 01976 250 01977 0 01978 0 01979 0 01980 289 01981 198 01982 200 01983 200 01984 300 01985 250 01986 300 01987 250 01988 0 01989 0 01990 0 01991 0 01992 0 01993 0 01994 0 01995 0 01996 0 01997 0 01998 0 01999 0 02000 0 22001 0 02002 0 02003 0 02004 0 02005 0 02006 0 2932007 0 02008 0 02009 0 02010 0 0

Eritrea - Tesfamichael and Mohamud 87

Appendix Table A2. Catch composition (in tonnes) of the Eritrean beach seine fishery for local consumption from 1950 to 2010.

Year Carangidae Scomberoides spp. Mugilidae Euthynnus affinis Others1950 250 100 50 0 01951 250 100 50 0 01952 250 100 50 0 01953 250 100 50 0 01954 250 100 50 0 01955 250 100 50 0 01956 250 100 50 0 01957 250 100 50 0 01958 250 100 50 0 01959 250 100 50 0 01960 250 100 50 0 01961 250 100 50 0 01962 250 100 50 0 01963 250 100 50 0 01964 250 100 50 0 01965 250 100 50 0 01966 250 100 50 0 01967 250 100 50 80 401968 250 100 50 80 401969 250 100 50 0 01970 250 100 50 0 01971 250 100 50 0 01972 250 100 50 80 401973 244 98 49 78 391974 238 95 48 76 381975 231 93 46 74 371976 225 90 45 72 361977 219 88 44 70 351978 213 85 43 68 341979 207 83 41 66 331980 168 67 34 54 271981 151 60 30 49 241982 134 54 27 43 211983 118 47 24 38 191984 101 40 20 32 161985 84 34 17 27 131986 67 27 13 22 111987 50 20 10 16 81988 34 13 7 11 51989 17 7 3 5 31990 0 0 0 0 01991 0 0 0 0 01992 0 0 0 0 01993 0 0 0 0 01994 0 0 0 0 01995 0 0 0 0 01996 0 0 0 0 01997 0 0 0 0 01998 0 0 0 0 01999 0 0 0 0 02000 0 0 0 0 02001 0 0 0 0 02002 0 0 0 0 02003 0 0 0 0 02004 0 0 0 0 02005 0 0 0 0 02006 0 0 0 0 02007 0 0 0 0 02008 0 0 0 0 02009 0 0 0 0 02010 0 0 0 0 0

88

Appendix Table A3. Catch composition (in tonnes) of the Eritrean handline fishery from 1950 to 2010.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 171950 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01951 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01952 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01953 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01954 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01955 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01956 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01957 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01958 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01959 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01960 400 118 109 0 0 0 0 0 0 0 0 0 0 0 0 0 01961 400 118 109 0 0 0 0 0 0 0 0 0 0 0 0 0 01962 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01963 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01964 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01965 343 101 94 0 0 0 0 0 0 0 0 0 0 0 0 0 01966 572 169 156 0 0 0 0 0 0 0 0 0 0 0 0 0 01967 572 169 156 0 0 0 0 0 0 0 0 0 0 0 0 0 01968 572 169 156 0 0 0 0 0 0 0 0 0 0 0 0 0 01969 572 169 156 0 0 0 0 0 0 0 0 0 0 0 0 0 01970 572 169 156 0 0 0 0 0 0 0 0 0 0 0 0 0 01971 572 169 156 0 0 0 0 0 0 0 0 0 0 0 0 0 01972 572 169 156 0 0 0 0 0 0 0 0 0 0 0 0 0 01973 572 169 156 0 0 0 0 0 0 0 0 0 0 0 0 0 01974 572 169 156 0 0 0 0 0 0 0 0 0 0 0 0 0 01975 572 169 156 0 0 0 0 0 0 0 0 0 0 0 0 0 01976 572 169 156 0 0 0 0 0 0 0 0 0 0 0 0 0 01977 225 66 61 0 0 0 0 0 0 0 0 0 0 0 0 0 01978 229 68 62 0 0 0 0 0 0 0 0 0 0 0 0 0 01979 233 69 64 0 0 0 0 0 0 0 0 0 0 0 0 0 01980 331 98 90 0 0 0 0 0 0 0 0 0 0 0 0 0 01981 294 87 80 0 0 0 0 0 0 0 0 0 0 0 0 0 01982 339 100 92 0 0 0 0 0 0 0 0 0 0 0 0 0 01983 623 184 170 0 0 0 0 0 0 0 0 0 0 0 0 0 01984 533 158 145 0 0 0 0 0 0 0 0 0 0 0 0 0 01985 444 131 121 0 0 0 0 0 0 0 0 0 0 0 0 0 01986 449 133 122 0 0 0 0 0 0 0 0 0 0 0 0 0 01987 379 112 103 0 0 0 0 0 0 0 0 0 0 0 0 0 01988 309 91 84 0 0 0 0 0 0 0 0 0 0 0 0 0 01989 240 71 65 0 0 0 0 0 0 0 0 0 0 0 0 0 01990 32 33 28 43 25 27 8 14 15 14 10 9 8 7 6 4 21991 32 33 28 43 25 27 8 14 15 14 10 9 8 7 6 4 21992 65 66 57 87 50 54 16 29 30 28 20 18 16 15 13 7 51993 67 68 58 89 51 55 16 29 31 28 21 18 16 15 13 7 51994 65 66 56 86 50 54 16 29 30 28 20 17 16 14 13 7 41995 75 76 65 100 58 62 18 33 34 32 23 20 18 17 15 8 51996 215 164 144 99 29 16 0 86 21 8 0 0 0 0 5 0 21997 46 82 26 307 22 15 2 104 84 7 0 22 3 48 27 0 161998 28 60 14 347 20 18 1 98 71 9 6 54 8 37 17 3 231999 122 175 105 210 68 45 11 84 32 15 59 38 3 32 39 6 42000 129 145 104 148 75 149 15 14 35 63 94 25 24 31 34 20 32001 138 62 76 23 144 156 10 0 97 73 42 57 54 30 30 18 82002 126 117 172 1 158 186 47 0 32 127 44 16 71 6 9 16 02003 38 69 97 0 101 67 88 0 1 23 6 0 23 0 0 30 02004 71 87 93 0 186 82 460 0 0 34 12 0 18 0 0 53 02005 28 28 24 37 21 23 7 12 13 12 9 7 7 6 5 3 22006 51 51 44 67 39 42 12 22 23 21 16 14 12 11 10 6 42007 52 52 45 69 40 43 13 23 24 22 16 14 12 12 10 6 42008 10 10 9 13 8 8 2 4 5 4 3 3 2 2 2 1 12009 15 15 13 19 11 12 4 6 7 6 5 4 4 3 3 2 12010 5 5 5 7 4 4 1 2 2 2 2 1 1 1 1 1 0

1: Lutjanidae <Snappers>; 2: Serranidae; 3: Lethrinidae; 4: Lutjanus bohar; 5: Scomberomorus commerson; 6: Carangidae; 7: Scombridae <Tunas>; 8: Pristipomoides multidens; 9: Lethrinus microdon; 10: Sphyraenidae; 11: Lutjanidae <Job fishes>; 12: Epinephelus chlorostigma; 13: Scomberoides commersonnianus; 14: Epinephelus malabaricus; 15: Lutjanus gibbus; 16: Ariidae; 17: Lethrinus mahsena

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Table A3 continuedYear 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 341950 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621951 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621952 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621953 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621954 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621955 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621956 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621957 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621958 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621959 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621960 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 721961 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 721962 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621963 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621964 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621965 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 621966 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1031967 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1031968 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1031969 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1031970 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1031971 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1031972 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1031973 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1031974 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1031975 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1031976 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1031977 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 401978 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 411979 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 421980 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 601981 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 531982 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 611983 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1121984 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 961985 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 801986 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 811987 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 681988 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 561989 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 431990 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 51991 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 51992 0 3 2 0 1 1 1 0 0 0 0 0 0 0 0 0 111993 0 3 2 0 1 1 1 0 0 0 0 0 0 0 0 0 111994 6 3 2 0 1 1 1 1 0 0 0 0 0 0 0 0 111995 7 3 3 0 1 1 1 1 0 0 0 0 0 0 0 0 121996 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 11997 2 0 8 0 0 4 0 0 0 0 0 0 0 0 0 0 11998 1 0 7 0 0 1 0 0 0 0 0 0 0 0 0 1 31999 9 2 6 0 0 0 2 0 0 0 0 0 0 0 0 0 22000 8 5 3 7 0 5 1 2 0 0 0 1 0 0 0 0 32001 13 6 3 6 1 2 3 3 1 1 0 0 0 0 1 0 12002 7 11 0 6 3 1 0 1 1 0 1 0 1 0 0 0 1042003 7 9 0 4 16 1 2 0 3 3 1 0 0 1 0 0 22004 10 14 0 11 7 0 2 0 1 0 0 1 0 0 0 0 12005 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 52006 3 2 2 1 1 1 0 0 0 0 0 0 0 0 0 0 82007 4 2 2 0 1 1 0 0 0 0 0 0 0 0 0 0 82008 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22009 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 22010 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

18: Haemulidae; 19: Rachycentridae; 20: Lethrinus lentjan; 21: Pomadasys argenteus; 22: Bothidae; 23: Scombridae <Mackerels>; 24: Mugilidae; 25: Sparidae; 26: Chanos chanos; 27: Palinuridae; 28: Scaridae; 29: Labridae; 30: Rhinobatidae; 31: Belonidae; 32: Sepiidae; 33: Siganidae; 34: Others

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Appendix Table A4. Catch composition (in tonnes) of the Eritrean gillnet fishery from 1950 to 2010.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 171950 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01967 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01968 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01969 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01970 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01971 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01972 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01973 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01974 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01975 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01976 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01977 21 13 0 8 8 7 0 6 5 4 4 4 4 3 2 0 01978 21 13 0 8 8 7 0 6 5 4 4 4 4 3 2 0 01979 22 13 0 8 8 7 0 6 5 4 4 4 4 3 2 0 01980 30 19 0 11 11 10 0 9 7 6 5 5 5 4 3 0 01981 27 17 0 10 10 9 0 8 6 6 5 5 5 4 3 0 01982 31 19 0 12 11 10 0 9 7 6 5 5 5 4 3 0 01983 56 35 0 21 20 18 0 16 12 11 9 9 9 7 6 0 01984 48 30 0 18 17 16 0 14 11 10 8 8 8 6 5 0 01985 40 25 0 15 15 13 0 11 9 8 7 7 7 5 4 0 01986 40 25 0 15 15 13 0 11 9 8 7 7 7 5 4 0 01987 36 22 0 13 13 12 0 10 8 7 6 6 6 5 4 0 01988 31 19 0 12 11 10 0 9 7 6 5 5 5 4 3 0 01989 26 16 0 10 10 9 0 8 6 5 4 4 4 3 3 0 01990 22 13 0 8 8 7 0 6 5 4 4 4 4 3 2 0 01991 21 13 0 8 8 7 0 6 5 4 4 4 4 3 2 0 01992 43 27 0 16 16 14 0 12 10 9 7 7 7 6 5 0 01993 45 28 0 17 16 15 0 13 10 9 8 8 8 6 5 0 01994 45 28 0 17 16 15 0 13 10 9 7 8 8 6 5 0 51995 53 33 0 20 19 17 0 15 12 11 9 9 9 7 6 0 61996 2 2 95 1 1 0 19 6 0 1 0 0 4 1 2 6 11997 5 7 128 2 2 1 100 3 0 2 1 5 6 1 3 18 01998 9 8 318 5 6 1 33 4 4 3 3 2 0 6 0 39 11999 25 15 154 9 8 8 34 4 14 2 5 0 0 4 1 24 22000 30 9 153 6 7 7 57 3 3 2 3 4 0 1 1 18 12001 9 9 68 5 4 3 89 0 2 3 2 2 0 0 0 35 12002 18 8 99 8 6 9 135 4 1 7 1 0 0 0 2 22 22003 40 13 59 11 7 33 150 1 0 9 2 0 0 0 1 9 42004 41 26 0 16 15 14 0 12 9 8 7 7 7 5 4 0 22005 106 66 0 40 38 35 0 30 23 22 18 18 18 14 11 0 72006 86 53 0 32 31 28 0 25 19 18 14 14 15 11 9 0 62007 112 69 0 42 41 37 0 32 25 23 19 19 19 14 12 0 122008 231 143 0 87 84 76 0 66 51 47 38 39 39 30 25 0 242009 263 163 0 99 95 86 0 75 58 53 44 44 44 34 28 0 72010 257 159 0 96 93 84 0 73 57 52 43 43 43 33 27 0 8

1: Carangidae; 2: Scomberoides commersonnianus; 3: Scomberomorus commerson; 4: Lutjanidae <Snapper>; 5: Lethrinidae; 6: Ariidae; 7: Scombridae <Tunas>; 8: Mugilidae; 9: Penaeidae; 10: Rachycentridae; 11: Lutjanidae <Job fishes>; 12: Lethrinus microdon; 13: Euthynnus affinis; 14: Lutjanus bohar; 15: Chanos chanos; 16: Sphyraenidae; 17: Haemulidae

Eritrea - Tesfamichael and Mohamud 91

Table A4 continuedYear 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 341950 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01967 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01968 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01969 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01970 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01971 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01972 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01973 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01974 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01975 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01976 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01977 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 111978 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 111979 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01980 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 161981 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 151982 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 161983 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 301984 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 261985 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 211986 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 211987 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 191988 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 171989 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 141990 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 121991 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 111992 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 231993 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 241994 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 241995 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 281996 0 0 1 0 0 5 0 0 1 2 0 0 0 0 0 0 181997 0 0 1 1 0 23 0 1 0 2 0 0 0 0 0 0 361998 0 0 12 1 0 0 0 5 2 1 0 0 0 0 1 0 521999 0 0 6 0 0 0 1 1 3 0 0 0 0 0 0 0 362000 1 0 5 0 0 0 0 3 3 2 0 0 0 0 0 0 362001 0 1 4 0 1 0 0 1 0 0 0 0 0 0 0 1 262002 2 1 9 0 6 0 0 0 0 0 0 0 0 0 0 0 312003 2 5 12 0 0 0 0 0 0 0 0 0 0 0 0 0 402004 2 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 222005 5 3 0 2 0 0 1 0 0 0 0 0 0 0 0 0 572006 3 2 0 2 21 0 1 0 0 0 0 0 0 0 0 0 262007 0 3 0 2 0 0 2 0 0 0 0 0 0 0 0 0 602008 2 6 0 4 0 0 3 0 0 0 1 0 1 0 0 0 1232009 23 7 0 5 0 0 4 0 0 0 1 1 1 0 0 0 1402010 21 7 0 4 0 0 4 0 0 0 1 1 1 0 0 0 137

18: Pomadasys argenteus; 19: Bothidae; 20: Serranidae; 21: Mullidae; 22: Portunidae; 23: Thunnus tonggol; 24: Istiophoridae; 25: Epinephelus chlorostigma; 26: Epinephelus malabaricus; 27: Sphyraena barracuda; 28: Belonidae; 29: Rhinobatidae; 30: Pomacanthidae; 31: Scaridae; 32: Scombridae <Mackerels>; 33: Sepiidae; 34: Others

92Appendix Table A5. Catch composition (in tonnes) of the subsistence catch of Eritrea from 1950 to 2010.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 171950 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01951 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01952 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01953 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01954 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01955 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01956 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01957 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01958 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01959 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01960 120 35 33 0 0 0 0 0 0 0 0 0 0 0 0 0 01961 120 35 33 0 0 0 0 0 0 0 0 0 0 0 0 0 01962 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01963 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01964 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01965 103 30 28 0 0 0 0 0 0 0 0 0 0 0 0 0 01966 172 51 47 0 0 0 0 0 0 0 0 0 0 0 0 0 01967 172 51 47 0 0 0 0 0 0 0 0 0 0 0 0 0 01968 172 51 47 0 0 0 0 0 0 0 0 0 0 0 0 0 01969 172 51 47 0 0 0 0 0 0 0 0 0 0 0 0 0 01970 172 51 47 0 0 0 0 0 0 0 0 0 0 0 0 0 01971 172 51 47 0 0 0 0 0 0 0 0 0 0 0 0 0 01972 172 51 47 0 0 0 0 0 0 0 0 0 0 0 0 0 01973 172 51 47 0 0 0 0 0 0 0 0 0 0 0 0 0 01974 172 51 47 0 0 0 0 0 0 0 0 0 0 0 0 0 01975 172 51 47 0 0 0 0 0 0 0 0 0 0 0 0 0 01976 172 51 47 0 0 0 0 0 0 0 0 0 0 0 0 0 01977 70 20 21 6 0 1 4 0 1 2 1 0 0 2 1 1 01978 71 20 21 6 0 1 4 0 1 2 1 0 0 2 1 1 01979 72 21 21 6 0 1 4 0 1 2 1 0 0 2 1 1 01980 103 29 30 9 0 1 6 0 2 3 1 0 0 3 2 2 01981 91 26 27 8 0 1 5 0 1 3 1 0 0 2 2 2 01982 105 30 31 9 0 1 6 0 2 3 2 0 0 3 2 2 01983 193 55 57 17 0 2 10 0 3 6 3 0 0 5 3 4 01984 165 47 49 14 0 2 9 0 2 5 2 0 0 4 3 3 01985 138 39 41 12 0 2 7 0 2 4 2 0 0 3 2 3 01986 139 40 41 12 0 2 7 0 2 4 2 0 0 3 2 3 01987 118 34 35 11 0 1 7 0 2 4 2 0 0 3 2 2 01988 96 27 29 9 0 1 6 0 2 3 2 0 0 3 2 2 01989 75 21 22 8 0 1 5 0 1 3 1 0 0 2 2 2 01990 12 10 11 14 7 14 6 2 6 3 4 4 4 2 2 1 31991 12 10 11 14 8 14 6 2 6 3 4 4 4 2 2 1 31992 24 20 22 29 15 28 13 5 11 6 8 8 9 4 3 3 51993 17 14 15 20 10 19 9 3 8 4 6 6 6 3 2 2 41994 16 13 14 19 10 18 8 3 7 4 5 5 6 3 2 2 31995 18 14 16 22 11 20 10 3 8 5 6 6 6 3 3 2 41996 39 30 26 3 23 18 0 4 4 0 0 3 16 1 0 0 01997 8 15 5 3 27 54 2 18 16 0 0 4 18 1 0 0 41998 6 12 3 5 58 60 3 6 12 1 2 8 17 1 1 1 101999 22 30 19 12 36 35 3 7 5 2 10 6 14 1 1 2 62000 21 24 18 28 36 24 5 11 6 4 15 13 2 1 1 1 42001 22 10 12 25 32 4 10 15 15 3 7 16 0 0 1 0 92002 20 19 26 30 38 0 12 27 5 4 7 22 0 1 3 0 22003 7 11 15 15 23 0 5 34 0 9 1 4 0 0 3 0 02004 12 12 15 17 25 1 6 62 1 9 3 5 0 2 3 1 02005 9 4 8 17 3 7 9 1 4 5 3 2 2 4 3 3 12006 10 6 9 16 5 10 8 2 5 4 4 3 3 3 2 2 22007 11 6 10 18 5 10 10 1 5 5 4 3 3 4 3 3 22008 11 1 10 27 1 5 16 0 5 9 5 0 0 7 5 6 02009 12 2 11 29 1 6 18 0 5 9 5 1 1 8 6 6 02010 10 1 10 26 0 4 16 0 5 8 4 0 0 7 5 6 0

1: Lutjanidae <Snappers>; 2: Serranidae; 3: Lethrinidae; 4: Carangidae; 5: Scomberomorus commerson; 6: Lutjanus bohar; 7: Scomberoides commersonnianus; 8: Scombridae <Tunas>; 9: Lethrinus microdon; 10: Ariidae; 11: Lutjanidae <Job fishes>; 12: Sphyraenidae; 13: Pristipomoides multidens; 14: Mugilidae; 15: Rachycentridae; 16: Penaeidae; 17: Epinephelus chlorostigma

Eritrea - Tesfamichael and Mohamud 93

Table A5 continuedYear 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 341950 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191951 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191952 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191953 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191954 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191955 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191956 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191957 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191958 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191959 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191960 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 221961 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 221962 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191963 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191964 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191965 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 191966 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 311967 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 311968 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 311969 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 311970 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 311971 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 311972 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 311973 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 311974 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 311975 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 311976 0 0 0 0 0 0 0 0 0 0.0 0 0.0 0 0 0.0 0.0 311977 0 1 0 1 0 0 0 0 0 0.1 0 0.1 0 0 0.0 0.0 161978 0 1 0 1 0 0 0 0 0 0.1 0 0.1 0 0 0.0 0.0 161979 0 1 0 1 0 0 0 0 0 0.1 0 0.1 0 0 0.0 0.0 131980 0 2 0 1 0 0 0 0 0 0.2 0 0.1 0 0 0.0 0.0 231981 0 1 0 1 0 0 0 0 0 0.1 0 0.1 0 0 0.0 0.0 201982 0 2 0 1 0 0 0 0 0 0.2 0 0.1 0 0 0.0 0.0 231983 0 3 0 2 0 0 0 0 0 0.3 0 0.2 0 0 0.0 0.1 431984 0 2 0 2 0 0 0 0 0 0.3 0 0.2 0 0 0.0 0.1 371985 0 2 0 1 0 0 0 0 0 0.2 0 0.2 0 0 0.0 0.0 301986 0 2 0 1 0 0 0 0 0 0.2 0 0.2 0 0 0.0 0.0 311987 0 2 0 1 0 0 0 0 0 0.2 0 0.1 0 0 0.0 0.0 261988 0 2 0 1 0 0 0 0 0 0.2 0 0.1 0 0 0.0 0.0 221989 0 1 0 1 0 0 0 0 0 0.1 0 0.1 0 0 0.0 0.0 171990 2 1 2 1 0 1 0 0 0 0.1 0 0.1 0 0 0.0 0.0 51991 2 1 2 1 0 1 0 0 0 0.1 0 0.1 0 0 0.0 0.0 51992 4 2 4 1 0 1 1 0 1 0.2 0 0.2 0 0 0.0 0.1 101993 3 2 3 1 0 1 0 0 0 0.2 0 0.1 0 0 0.0 0.1 71994 3 1 2 1 2 1 0 0 0 0.2 0 0.1 0 0 0.1 0.1 71995 3 2 3 1 2 1 1 0 0 0.2 0 0.2 0 0 0.1 0.1 81996 0 1 1 0 0 0 0 0 0 0.0 1 0.0 0 0 0.0 0.0 31997 9 1 5 1 0 3 0 0 1 0.1 4 0.1 1 0 0.1 0.0 71998 7 0 3 0 0 4 0 0 1 0.1 0 0.0 0 0 0.1 0.0 91999 6 0 6 0 2 1 0 0 1 0.1 0 0.1 0 0 0.1 0.0 62000 5 0 5 0 2 1 0 1 0 0.0 0 0.1 1 0 0.4 0.0 72001 5 0 5 0 2 1 0 1 1 0.0 0 0.0 0 0 0.4 0.0 42002 1 0 1 0 1 0 1 1 0 0.0 0 0.0 0 1 0.2 0.1 212003 0 0 0 1 2 0 3 1 0 0.0 0 0.0 0 0 0.1 0.2 72004 0 1 0 1 2 0 1 2 0 0.1 0 0.1 0 0 0.0 0.0 32005 1 2 1 1 1 0 0 1 0 0.2 0 0.2 0 0 0.0 0.1 82006 1 2 1 1 1 0 0 0 0 0.2 0 0.2 0 3 0.0 0.1 42007 1 2 1 1 2 0 0 0 0 0.2 0 0.2 0 0 0.1 0.1 82008 0 4 0 3 3 0 1 0 0 0.5 0 0.4 0 0 0.0 0.1 142009 0 5 0 3 1 0 1 3 0 0.5 0 0.4 0 0 0.0 0.1 152010 0 4 0 3 1 0 1 2 0 0.4 0 0.4 0 0 0.0 0.1 14

18: Epinephelus malabaricus; 19: Euthynnus affinis; 20: Lutjanus gibbus; 21: Chanos chanos; 22: Haemulidae; 23: Lethrinus mahsena; 24: Bothidae; 25: Pomadasys argenteus; 26: Lethrinus lentjan; 27: Mullidae; 28: Thunnus tonggol; 29: Istiophoridae; 30: Scombridae <Mackerels>; 31: Portunidae; 32: Sparidae; 33: Belonidae; 34: Others

94Appendix Table A6. Catch composition (in tonnes) of the retained catch of trawl fisheries in the Eritrean Red Sea from 1950 to 2010.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 181950 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 01958 20 16 0 1 16 30 0 0 0 0 0 0 0 0 0 0 0 11959 20 16 0 1 16 30 0 0 0 0 0 0 0 0 0 0 0 11960 138 112 0 6 109 30 0 0 0 0 0 0 0 0 0 0 0 101961 398 323 0 17 314 30 0 0 0 0 0 0 0 0 0 0 0 291962 496 402 0 22 391 30 0 0 0 0 0 0 0 0 0 0 0 361963 548 445 0 24 432 30 0 0 0 0 0 0 0 0 0 0 0 401964 450 365 0 20 355 30 0 0 0 0 0 0 0 0 0 0 0 331965 448 363 0 20 353 30 0 0 0 0 0 0 0 0 0 0 0 331966 465 377 0 20 367 30 0 0 0 0 0 0 0 0 0 0 0 341967 448 364 0 20 353 30 0 0 0 0 0 0 0 0 0 0 0 331968 477 387 0 21 376 30 0 0 0 0 0 0 0 0 0 0 0 351969 533 432 0 23 420 30 0 0 0 0 0 0 0 0 0 0 0 391970 478 387 0 21 376 30 0 0 0 0 0 0 0 0 0 0 0 351971 441 358 0 19 348 28 0 0 0 0 0 0 0 0 0 0 0 321972 416 338 0 18 328 27 0 0 0 0 0 0 0 0 0 0 0 301973 318 258 0 14 251 25 0 0 0 0 0 0 0 0 0 0 0 231974 196 159 0 9 154 23 0 0 0 0 0 0 0 0 0 0 0 141975 171 139 0 8 135 22 0 0 0 0 0 0 0 0 0 0 0 121976 166 134 0 7 131 20 0 0 0 0 0 0 0 0 0 0 0 121977 40 32 0 2 31 16 0 0 0 0 0 0 0 0 0 0 0 31978 5 4 0 0 4 12 0 0 0 0 0 0 0 0 0 0 0 01979 29 24 0 1 23 8 0 0 0 0 0 0 0 0 0 0 0 01980 26 21 0 1 20 4 0 0 0 0 0 0 0 0 0 0 0 21981 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01982 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01983 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01984 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01985 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01986 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01987 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01988 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01989 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01990 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01991 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01992 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01993 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01994 910 332 219 184 0 0 148 95 73 0 37 27 22 0 21 0 10 1961995 1,304 476 314 264 0 0 212 136 105 0 53 38 32 0 17 0 5 3051996 3 4 804 174 0 2 366 8 675 0 116 58 0 0 0 0 8 2351997 5 14 1 3 0 0 11 0 0 0 0 0 0 0 0 0 1 21998 0 0 131 31 0 11 49 167 22 3 38 0 1 0 0 0 0 501999 1,881 1654 340 116 0 69 580 195 272 0 136 19 22 19 21 0 0 3302000 3,059 1692 1,799 580 0 456 506 776 326 446 236 188 115 40 5 0 0 1,0862001 2,537 1093 867 416 0 764 280 387 216 128 122 95 122 158 13 0 0 6102002 3,120 644 538 293 0 339 179 158 20 137 55 11 62 114 2 0 0 4302003 1,683 502 250 1,727 0 322 84 135 30 45 95 5 49 94 0 0 0 4522004 3,593 756 161 337 0 296 122 205 28 142 25 6 68 0 2 0 0 4062005 2,230 580 91 180 0 216 50 44 14 38 18 3 18 9 0 0 0 3052006 3,740 1,026 268 572 0 577 250 219 148 107 55 270 85 0 0 28 0 8162007 208 76 50 42 0 32 33 22 17 1 9 6 5 2 0 0 0 542008 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 12009 332 121 80 67 0 51 12 34 27 42 14 10 8 0 0 0 0 882010 547 200 132 111 0 84 25 57 44 64 22 16 13 0 0 0 0 1461: Synodontidae; 2: Nemipteridae; 3: Carangidae; 4: Sphyraenidae; 5: Mugilidae; 6: Penaeidae; 7: Haemulidae; 8: Ariidae; 9: Lethrinidae; 10: Pomadasys argenteus; 11: Lutjanidae; 12: Rastrelliger kanagurta; 13: Bothus pantherinus; 14: Leiognathidae; 15: Platycephalidae; 16: Plectorhinchus schotaf; 17: Psettodes erumei; 18: Others

Eritrea - Tesfamichael and Mohamud 95Appendix Table A7. Composition (in tonnes) of the discarded catch of trawl fisheries in the Eritrean Red Sea from 1950 to 2010. Year 1 2 3 4 5 6 7 8 9 10 111950 84 9 5 5 3 3 3 3 3 1 11951 84 9 5 5 3 3 3 3 3 1 11952 84 9 5 5 3 3 3 3 3 1 11953 84 9 5 5 3 3 3 3 3 1 11954 84 9 5 5 3 3 3 3 3 1 11955 84 9 5 5 3 3 3 3 3 1 11956 84 9 5 5 3 3 3 3 3 1 11957 84 9 5 5 3 3 3 3 3 1 11958 199 22 13 13 6 6 6 6 6 3 31959 199 22 13 13 6 6 6 6 6 3 31960 361 41 23 23 12 12 12 12 12 6 61961 719 81 46 46 23 23 23 23 23 12 121962 854 96 55 55 28 28 28 28 28 14 141963 926 105 60 60 30 30 30 30 30 15 151964 791 89 51 51 26 26 26 26 26 13 131965 787 89 51 51 25 25 25 25 25 13 131966 811 92 52 52 26 26 26 26 26 13 131967 789 89 51 51 25 25 25 25 25 13 131968 827 93 53 53 27 27 27 27 27 13 131969 905 102 58 58 29 29 29 29 29 15 151970 829 94 53 53 27 27 27 27 27 13 131971 769 87 50 50 25 25 25 25 25 12 121972 725 82 47 47 23 23 23 23 23 12 121973 581 66 37 37 19 19 19 19 19 9 91974 403 45 26 26 13 13 13 13 13 6 61975 360 41 23 23 12 12 12 12 12 6 61976 342 39 22 22 11 11 11 11 11 6 61977 146 16 9 9 5 5 5 5 5 2 21978 76 9 5 5 2 2 2 2 2 1 11979 86 10 6 6 3 3 3 3 3 1 11980 58 7 4 4 2 2 2 2 2 1 11981 0 0 0 0 0 0 0 0 0 0 01982 0 0 0 0 0 0 0 0 0 0 01983 0 0 0 0 0 0 0 0 0 0 01984 0 0 0 0 0 0 0 0 0 0 01985 0 0 0 0 0 0 0 0 0 0 01986 0 0 0 0 0 0 0 0 0 0 01987 0 0 0 0 0 0 0 0 0 0 01988 0 0 0 0 0 0 0 0 0 0 01989 0 0 0 0 0 0 0 0 0 0 01990 0 0 0 0 0 0 0 0 0 0 01991 0 0 0 0 0 0 0 0 0 0 01992 0 0 0 0 0 0 0 0 0 0 01993 0 0 0 0 0 0 0 0 0 0 01994 1,107 125 71 71 36 36 36 36 36 18 181995 1,588 179 102 102 51 51 51 51 51 26 261996 464 52 30 30 15 15 15 15 15 7 71997 36 4 2 2 1 1 1 1 1 1 11998 387 44 25 25 12 12 12 12 12 6 61999 3,304 373 213 213 107 107 107 107 107 53 532000 4,463 504 288 288 144 144 144 144 144 72 722001 3,961 447 256 256 128 128 128 128 128 64 642002 1,638 185 106 106 53 53 53 53 53 26 262003 3,414 385 220 220 110 110 110 110 110 55 552004 2,992 338 193 193 97 97 97 97 97 48 482005 1,847 209 119 119 60 60 60 60 60 30 302006 3,971 448 256 256 128 128 128 128 128 64 642007 271 31 17 17 9 9 9 9 9 4 42008 0 0 0 0 0 0 0 0 0 0 02009 431 49 28 28 14 14 14 14 14 7 72010 711 80 46 46 23 23 23 23 23 11 11

1: Leiognathidae; 2: Terapon spp.; 3: Gerres oyena; 4: Trichiurus spp.; 5: Formio niger; 6: Lupa pelgica; 7: Platycephalidae; 8: Soleidae; 9: Tetradontidae; 10: Clupeidae; 11: Mullidae

96Table A7 continued

Year 12 13 14 15 16 17 18 19 20 21 221950 1 41 38 32 12 5 3 3 3 1 111951 1 41 38 32 12 5 3 3 3 1 111952 1 41 38 32 12 5 3 3 3 1 111953 1 41 38 32 12 5 3 3 3 1 111954 1 41 38 32 12 5 3 3 3 1 111955 1 41 38 32 12 5 3 3 3 1 111956 1 41 38 32 12 5 3 3 3 1 111957 1 41 38 32 12 5 3 3 3 1 111958 3 0 0 0 0 0 0 0 0 0 261959 3 0 0 0 0 0 0 0 0 0 261960 6 0 0 0 0 0 0 0 0 0 471961 12 0 0 0 0 0 0 0 0 0 931962 14 0 0 0 0 0 0 0 0 0 1101963 15 0 0 0 0 0 0 0 0 0 1201964 13 0 0 0 0 0 0 0 0 0 1021965 13 0 0 0 0 0 0 0 0 0 1021966 13 0 0 0 0 0 0 0 0 0 1051967 13 0 0 0 0 0 0 0 0 0 1021968 13 0 0 0 0 0 0 0 0 0 1071969 15 0 0 0 0 0 0 0 0 0 1171970 13 0 0 0 0 0 0 0 0 0 1071971 12 0 0 0 0 0 0 0 0 0 991972 12 0 0 0 0 0 0 0 0 0 941973 9 0 0 0 0 0 0 0 0 0 751974 6 0 0 0 0 0 0 0 0 0 521975 6 0 0 0 0 0 0 0 0 0 461976 6 0 0 0 0 0 0 0 0 0 441977 2 0 0 0 0 0 0 0 0 0 191978 1 0 0 0 0 0 0 0 0 0 101979 1 0 0 0 0 0 0 0 0 0 111980 1 0 0 0 0 0 0 0 0 0 81981 0 0 0 0 0 0 0 0 0 0 01982 0 0 0 0 0 0 0 0 0 0 01983 0 0 0 0 0 0 0 0 0 0 01984 0 0 0 0 0 0 0 0 0 0 01985 0 0 0 0 0 0 0 0 0 0 01986 0 0 0 0 0 0 0 0 0 0 01987 0 0 0 0 0 0 0 0 0 0 01988 0 0 0 0 0 0 0 0 0 0 01989 0 0 0 0 0 0 0 0 0 0 01990 0 0 0 0 0 0 0 0 0 0 01991 0 0 0 0 0 0 0 0 0 0 01992 0 0 0 0 0 0 0 0 0 0 01993 0 0 0 0 0 0 0 0 0 0 01994 18 0 0 0 0 0 0 0 0 0 1431995 26 0 0 0 0 0 0 0 0 0 2051996 7 0 0 0 0 0 0 0 0 0 601997 1 0 0 0 0 0 0 0 0 0 51998 6 0 0 0 0 0 0 0 0 0 501999 53 0 0 0 0 0 0 0 0 0 4262000 72 0 0 0 0 0 0 0 0 0 5762001 64 0 0 0 0 0 0 0 0 0 5112002 26 0 0 0 0 0 0 0 0 0 2112003 55 0 0 0 0 0 0 0 0 0 4412004 48 0 0 0 0 0 0 0 0 0 3862005 30 0 0 0 0 0 0 0 0 0 2382006 64 0 0 0 0 0 0 0 0 0 5122007 4 0 0 0 0 0 0 0 0 0 352008 0 0 0 0 0 0 0 0 0 0 02009 7 0 0 0 0 0 0 0 0 0 562010 11 0 0 0 0 0 0 0 0 0 92

12: Squilla spp.; 13: Carangoides malabaricus; 14: Saurida tumbil; 15: Nemipteridae; 16: Pomadasys opercularis; 17: Ariidae; 18: Carangidae; 19: Plotosis angularis; 20: Sphyraenidae; 21: Sepiidae; 22: Others

Eritrea - Tesfamichael and Mohamud 97Appendix Table A8. Catch composition (in tonnes) of the Eritrean longline fishery from 1950 to 2010. Year 1 2 3 4 5 6 7 8 9 10 11 121950 0 0 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 0 0 01967 0 0 0 0 0 0 0 0 0 0 0 01968 0 0 0 0 0 0 0 0 0 0 0 01969 0 0 0 0 0 0 0 0 0 0 0 01970 0 0 0 0 0 0 0 0 0 0 0 01971 0 0 0 0 0 0 0 0 0 0 0 01972 0 0 0 0 0 0 0 0 0 0 0 01973 0 0 0 0 0 0 0 0 0 0 0 01974 0 0 0 0 0 0 0 0 0 0 0 01975 0 0 0 0 0 0 0 0 0 0 0 01976 0 0 0 0 0 0 0 0 0 0 0 01977 0 0 0 0 0 0 0 0 0 0 0 01978 0 0 0 0 0 0 0 0 0 0 0 01979 0 0 0 0 0 0 0 0 0 0 0 01980 0 0 0 0 0 0 0 0 0 0 0 01981 0 0 0 0 0 0 0 0 0 0 0 01982 0 0 0 0 0 0 0 0 0 0 0 01983 0 0 0 0 0 0 0 0 0 0 0 01984 0 0 0 0 0 0 0 0 0 0 0 01985 0 0 0 0 0 0 0 0 0 0 0 01986 0 0 0 0 0 0 0 0 0 0 0 01987 0 0 0 0 0 0 0 0 0 0 0 01988 0 0 0 0 0 0 0 0 0 0 0 01989 0 0 0 0 0 0 0 0 0 0 0 01990 0 0 0 0 0 0 0 0 0 0 0 01991 0 0 0 0 0 0 0 0 0 0 0 01992 0 0 0 0 0 0 0 0 0 0 0 01993 0 0 0 0 0 0 0 0 0 0 0 01994 0 0 0 0 0 0 0 0 0 0 0 01995 0 0 0 0 0 0 0 0 0 0 0 01996 0 0 0 0 0 0 0 0 0 0 0 01997 0 0 0 0 0 0 0 0 0 0 0 01998 0 0 0 0 0 0 0 0 0 0 0 01999 3 2 1 1 1 1 0 0 0 0 0 12000 2 172 0 12 21 12 13 0 6 0 0 262001 2 27 5 19 34 9 14 44 4 7 3 192002 110 83 37 33 32 23 16 16 4 2 2 402003 177 133 60 53 51 38 26 25 6 4 2 642004 130 16 8 54 24 48 2 0 0 1 1 322005 20 15 7 6 6 4 3 3 1 0 0 72006 197 29 94 16 15 4 17 0 0 0 0 412007 1 1 0 0 0 0 0 0 0 0 0 02008 0 0 0 0 0 0 0 0 0 0 0 02009 0 0 0 0 0 0 0 0 0 0 0 02010 0 0 0 0 0 0 0 0 0 0 0 01: Scombridae; 2: Serranidae; 3: Rachycentridae; 4: Ariidae; 5: Lutjanidae; 6: Carangidae; 7: Sphyraenidae; 8: Epinephelus chlorostigma; 9: Lethrinidae; 10: Haemulidae; 11: Pomadasys argenteus; 12: Others

98Appendix Table A9. Reconstructed catch (in tonnes) by sectors and total catch as reported to FAO by Eritrea in its Red Sea EEZ from 1950 to 2010. Year FAO landings Reconstructed total catch Industrial Artisanal Subsistence Discards1950 3,000 28,599 30 28,119 180 2701951 3,000 28,599 30 28,119 180 2701952 4,000 28,599 30 28,119 180 2701953 4,000 28,599 30 28,119 180 2701954 5,000 28,599 30 28,119 180 2701955 6,200 28,599 30 28,119 180 2701956 6,200 25,051 30 24,571 180 2701957 7,100 21,503 30 21,023 180 2701958 7,100 18,054 85 17,475 180 3141959 7,500 13,848 85 13,270 180 3141960 8,000 13,166 405 11,982 210 5701961 8,500 17,684 1,110 15,228 210 1,1361962 9,000 14,157 1,377 11,251 180 1,3501963 8,900 13,159 1,519 9,995 180 1,4641964 11,300 14,661 1,253 11,977 180 1,2511965 15,200 22,657 1,245 19,988 180 1,2441966 15,500 25,695 1,293 22,819 300 1,2831967 15,500 22,325 1,248 19,531 300 1,2471968 13,900 18,365 1,324 15,432 300 1,3081969 13,700 18,888 1,477 15,681 300 1,4301970 16,300 22,406 1,327 19,469 300 1,3101971 18,800 23,797 1,226 21,056 300 1,2151972 13,800 13,886 1,157 11,282 300 1,1471973 3,700 7,162 890 5,054 300 9181974 4,900 7,027 555 5,535 300 6371975 2,430 4,637 487 3,282 300 5681976 970 3,393 470 2,081 300 5411977 172 1,481 123 979 148 2301978 15 1,258 26 961 151 1201979 0 1,314 85 945 149 1351980 407 1,761 74 1,379 216 921981 328 1,368 0 1,175 193 01982 350 1,458 0 1,236 221 01983 400 2,225 0 1,819 407 01984 600 2,037 0 1,689 348 01985 500 1,700 0 1,410 290 01986 600 1,725 0 1,433 292 01987 500 1,453 0 1,204 249 01988 723 981 0 775 206 01989 1,557 759 0 596 163 01990 1,172 533 0 414 119 01991 117 535 0 415 119 01992 100 1,058 0 818 240 01993 475 1,005 0 840 165 01994 2,707 5,017 2,275 834 159 1,7501995 3,559 6,913 3,262 964 178 2,5091996 3,254 4,346 2,455 983 176 7331997 1,042 1,501 38 1,198 208 561998 1,856 2,714 503 1,369 229 6121999 6,998 12,598 5,668 1,472 235 5,2232000 12,713 20,626 11,574 1,761 238 7,0542001 8,882 16,703 7,995 2,244 203 6,2612002 7,854 15,570 6,499 6,241 241 2,5892003 6,691 15,565 6,111 3,916 140 5,3972004 7,406 16,545 6,465 5,170 182 4,7292005 4,030 10,442 3,868 3,554 100 2,9202006 8,816 18,769 8,573 3,810 109 6,2772007 1,934 4,634 561 3,525 120 4282008 1,668 3,853 1 3,716 135 02009 3,032 5,683 886 3,967 149 6812010 3,288 6,721 1,461 4,007 129 1,124

Eritrea - Tesfamichael and Mohamud 99Appendix Table A10. Reconstructed catch (in tonnes) by components in the Red Sea EEZ of Eritrea from 1950 to 2010. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.

Year Reported Unreported Discards1950 2,248 26,080 2701951 2,248 26,080 2701952 3,248 25,080 2701953 3,248 25,080 2701954 3,328 25,000 2701955 4,362 23,967 2701956 4,362 20,419 2701957 5,358 15,875 2701958 5,455 12,286 3141959 5,469 8,066 3141960 6,295 6,301 5701961 6,514 10,034 1,1361962 6,482 6,326 1,3501963 7,414 4,281 1,4641964 10,394 3,016 1,2511965 14,038 7,375 1,2441966 13,420 10,993 1,2831967 13,571 7,508 1,2471968 10,060 6,996 1,3081969 11,875 5,583 1,4301970 14,222 6,874 1,3101971 17,223 5,359 1,2151972 9,898 2,841 1,1471973 3,037 3,207 9181974 4,079 2,311 6371975 1,580 2,489 5681976 530 2,322 5411977 61 1,190 2301978 4 1,134 1201979 0 1,179 1351980 337 1,332 921981 256 1,113 01982 266 1,192 01983 285 1,940 01984 413 1,624 01985 345 1,356 01986 410 1,315 01987 342 1,111 01988 238 743 01989 329 430 01990 105 428 01991 54 481 01992 48 1,010 01993 163 842 01994 1,817 1,450 1,7501995 2,144 2,260 2,5091996 3,059 554 7331997 849 595 561998 1,452 650 6121999 6,701 674 5,2232000 11,541 2,031 7,0542001 7,972 2,469 6,2612002 7,197 5,785 2,5892003 5,865 4,303 5,3972004 6,517 5,300 4,7292005 3,763 3,759 2,9202006 8,318 4,175 6,2772007 720 3,485 4282008 439 3,414 02009 1,342 3,659 6812010 1,882 3,716 1,124

100Appendix Table A11. Total catches (in tonnes) of the fisheries in the Red Sea EEZ of Eritrea by different gears from 1950 to 2010.

Year Beach seine Gill net Handline Shark Dive Longline Trawl1950 26,650 0 780 413 456 0 3001951 26,650 0 780 413 456 0 3001952 26,650 0 780 413 456 0 3001953 26,650 0 780 413 456 0 3001954 26,650 0 780 413 456 0 3001955 26,650 0 780 413 456 0 3001956 23,160 0 780 413 399 0 3001957 19,669 0 780 413 341 0 3001958 16,179 0 780 413 284 0 3991959 11,996 0 780 413 261 0 3991960 10,421 0 910 413 448 0 9751961 13,827 0 910 413 288 0 2,2471962 9,948 0 780 413 290 0 2,7261963 8,658 0 780 413 325 0 2,9831964 10,703 0 780 394 280 0 2,5041965 18,105 0 780 937 346 0 2,4901966 20,367 0 1,300 1,146 306 0 2,5751967 14,986 0 1,300 3,174 371 0 2,4941968 8,526 0 1,300 5,508 398 0 2,6321969 11,425 0 1,300 1,900 1,356 0 2,9071970 16,413 0 1,300 1,500 556 0 2,6371971 17,200 0 1,300 2,300 556 0 2,4411972 8,526 0 1,300 1,100 656 0 2,3041973 3,198 0 1,300 400 456 0 1,8081974 3,579 0 1,300 500 456 0 1,1921975 1,892 0 1,300 30 359 0 1,0561976 718 0 1,300 100 263 0 1,0111977 456 131 510 14 16 0 3541978 443 132 520 14 3 0 1461979 430 118 530 14 3 0 2201980 641 184 752 14 3 0 1661981 515 168 668 14 3 0 01982 482 189 770 14 3 0 01983 447 345 1,416 14 3 0 01984 511 296 1,212 14 3 0 01985 426 248 1,009 14 3 0 01986 441 248 1,019 14 3 0 01987 356 219 861 14 3 0 01988 70 190 703 14 3 0 01989 35 162 545 14 3 0 01990 0 133 383 14 3 0 01991 0 132 385 14 3 0 01992 0 267 774 14 3 0 01993 0 258 730 14 3 0 01994 0 261 714 14 3 0 4,0251995 0 305 820 14 3 0 5,7711996 0 201 938 16 3 0 3,1881997 0 413 976 14 3 0 951998 0 604 970 19 6 0 1,1161999 0 415 1,247 42 3 11 10,8802000 0 412 1,324 143 118 264 18,3632001 0 310 1,221 120 795 188 14,0682002 0 427 1,454 159 4,442 398 8,6902003 0 455 676 135 2,789 639 10,8692004 0 227 1,298 91 3,735 317 10,8762005 0 582 288 49 2,735 73 6,7152006 293 469 523 255 2,378 413 14,4372007 0 607 531 129 2,378 4 9852008 0 1,246 102 127 2,378 0 12009 0 1,408 148 182 2,378 0 1,5672010 0 1,368 53 338 2,378 0 2,585

Eritrea - Tesfamichael and Mohamud 101Appendix Table A12. Taxonomic composition (in tonnes) of the reconstructed total catch of the fisheries in the Red Sea EEZ of Eritrea from 1950 to 2010. Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 151950 17,500 8,751 84 0 150 413 446 253 32 122 132 50 300 3 91951 17,500 8,751 84 0 150 413 446 253 32 122 132 50 300 3 91952 17,500 8,751 84 0 150 413 446 253 32 122 132 50 300 3 91953 17,500 8,751 84 0 150 413 446 253 32 122 132 50 300 3 91954 17,500 8,751 84 0 150 413 446 253 32 122 132 50 300 3 91955 17,500 8,751 84 0 150 413 446 253 32 122 132 50 300 3 91956 15,173 7,588 84 0 150 413 446 253 32 122 132 50 243 3 91957 12,846 6,424 84 0 150 413 446 253 32 122 132 50 185 3 91958 10,519 5,263 199 20 150 413 446 250 16 122 132 66 128 1 221959 7,731 3,869 199 20 150 413 446 250 16 122 132 66 105 1 221960 6,681 3,346 361 138 150 413 521 250 112 142 154 159 292 6 411961 8,951 4,487 719 398 150 413 521 250 323 142 154 364 132 17 811962 6,366 3,197 854 496 150 413 446 250 402 122 132 441 134 22 961963 5,505 2,768 926 548 150 413 446 250 445 122 132 482 169 24 1051964 6,869 3,447 791 450 150 394 446 250 365 122 132 405 124 20 891965 11,803 5,914 787 448 150 937 446 250 363 122 132 403 190 20 891966 13,312 6,669 811 465 150 1,146 744 250 377 203 220 417 150 20 921967 14,466 13 789 448 150 3,174 744 250 364 203 220 403 215 20 891968 8,006 13 827 477 150 5,508 744 250 387 203 220 426 242 21 931969 7,350 3,690 905 533 150 1,900 744 250 432 203 220 470 1,200 23 1021970 10,675 5,351 829 478 150 1,500 744 250 387 203 220 426 400 21 941971 11,200 5,612 769 441 150 2,300 744 250 358 203 220 398 400 19 871972 8,006 12 725 416 150 1,100 744 250 338 203 220 378 500 18 821973 2,691 9 581 318 150 400 744 244 258 203 220 300 300 14 661974 3,084 6 403 196 150 500 744 238 159 203 220 202 300 9 451975 1,411 6 360 171 150 30 744 231 139 203 220 181 203 8 411976 250 6 342 166 150 100 744 225 134 203 220 176 107 7 391977 0 2 146 40 0 14 302 247 32 90 86 83 10 2 161978 0 1 76 5 0 14 308 241 4 91 88 55 1 0 91979 0 1 86 29 0 14 313 235 24 93 90 72 1 1 101980 289 1 58 26 0 14 445 207 21 131 127 65 1 1 71981 198 0 0 0 0 14 395 187 0 117 113 40 1 0 01982 200 0 0 0 0 14 455 174 0 134 130 38 1 0 01983 200 0 0 0 0 14 838 191 0 247 239 44 1 0 01984 300 0 0 0 0 14 717 163 0 212 205 38 1 0 01985 250 0 0 0 0 14 597 136 0 176 171 32 1 0 01986 300 0 0 0 0 14 603 120 0 178 172 28 1 0 01987 250 0 0 0 0 14 510 97 0 151 146 23 1 0 01988 0 0 0 0 0 14 417 74 0 124 119 18 1 0 01989 0 0 0 0 0 14 325 51 0 97 92 13 1 0 01990 0 0 0 0 0 14 53 63 0 47 43 8 1 18 01991 0 0 0 0 0 14 53 63 0 47 43 8 1 18 01992 0 0 0 0 0 14 106 126 0 94 86 17 1 36 01993 0 0 0 0 0 14 100 120 0 89 81 16 1 34 01994 0 18 1,107 910 0 14 98 337 332 160 79 16 1 217 1251995 0 26 1,588 1,304 0 14 113 450 476 205 90 19 1 302 1791996 0 7 464 3 0 16 255 826 4 847 195 7 1 191 521997 0 1 36 5 0 14 57 24 14 33 98 4 1 33 41998 0 6 387 0 3 19 39 163 0 46 84 4 1 86 441999 0 53 3,324 1,881 0 42 153 423 1,654 403 213 8 1 162 3732000 0 74 4,503 3,059 115 143 157 2,018 1,692 461 345 5 1 687 5042001 0 64 4,119 2,537 792 120 165 1,067 1,093 312 103 3 1 554 4472002 0 27 1,751 3,120 4,439 159 154 797 644 228 228 4 1 480 1852003 0 55 3,509 1,683 2,786 135 56 410 502 155 226 4 1 1,789 3852004 0 49 2,992 3,593 3,732 91 98 349 756 151 115 16 1 378 3382005 0 30 1,856 2,230 2,732 49 76 242 580 85 47 35 1 196 2092006 0 357 3,971 3,740 2,375 255 93 416 1,026 232 87 28 1 613 4482007 0 4 273 208 2,375 129 105 223 76 112 59 36 1 67 312008 0 0 1 0 2,375 127 108 266 0 102 11 74 1 5 02009 0 7 431 332 2,375 182 125 384 121 146 16 83 1 74 492010 0 11 711 547 2,375 338 112 419 200 151 6 81 1 113 80

1: Engraulidae; 2: Clupeidae; 3: Leiognathidae; 4: Synodontidae; 5: Holothuriidae; 6: Elasmobranchii; 7: Lutjanidae <Snappers>, 8: Carangidae; 9: Nemipteridae; 10: Lethrinidae; 11: Serranidae ; 12: Mugilidae; 13: Trochus spp.; 14: Sphyraenidae; 15: Terapon spp.

102Table A12 continuedYear 16 17 18 19 20 21 22 23 24 25 26 27 28 29 301950 30 5 100 0 5 5 0 0 0 0 3 3 3 3 31951 30 5 100 0 5 5 0 0 0 0 3 3 3 3 31952 30 5 100 0 5 5 0 0 0 0 3 3 3 3 31953 30 5 100 0 5 5 0 0 0 0 3 3 3 3 31954 30 5 100 0 5 5 0 0 0 0 3 3 3 3 31955 30 5 100 0 5 5 0 0 0 0 3 3 3 3 31956 30 5 100 0 5 5 0 0 0 0 3 3 3 3 31957 30 5 100 0 5 5 0 0 0 0 3 3 3 3 31958 30 0 100 0 13 13 0 0 0 0 6 6 6 6 61959 30 0 100 0 13 13 0 0 0 0 6 6 6 6 61960 30 0 100 0 23 23 0 0 0 0 12 12 12 12 121961 30 0 100 0 46 46 0 0 0 0 23 23 23 23 231962 30 0 100 0 55 55 0 0 0 0 28 28 28 28 281963 30 0 100 0 60 60 0 0 0 0 30 30 30 30 301964 30 0 100 0 51 51 0 0 0 0 26 26 26 26 261965 30 0 100 0 51 51 0 0 0 0 25 25 25 25 251966 30 0 100 0 52 52 0 0 0 0 26 26 26 26 261967 30 0 100 0 51 51 0 0 0 0 25 25 25 25 251968 30 0 100 0 53 53 0 0 0 0 27 27 27 27 271969 30 0 100 0 58 58 0 0 0 0 29 29 29 29 291970 30 0 100 0 53 53 0 0 0 0 27 27 27 27 271971 28 0 100 0 50 50 0 0 0 0 25 25 25 25 251972 27 0 100 0 47 47 0 0 0 0 23 23 23 23 231973 25 0 98 0 37 37 0 0 0 0 19 19 19 19 191974 23 0 95 0 26 26 0 0 0 0 13 13 13 13 131975 22 0 93 0 23 23 0 0 0 0 12 12 12 12 121976 20 0 90 0 22 22 0 0 0 0 11 11 11 11 111977 22 9 88 0 9 9 0 4 17 0 5 5 5 5 51978 18 9 85 0 5 5 0 4 17 0 2 2 2 2 21979 14 9 83 0 6 6 0 4 17 0 3 3 3 3 31980 13 13 67 0 4 4 0 5 24 0 2 2 2 2 21981 8 12 60 0 0 0 0 5 22 0 0 0 0 0 01982 9 13 54 0 0 0 0 5 25 0 0 0 0 0 01983 16 24 47 0 0 0 0 9 45 0 0 0 0 0 01984 14 21 40 0 0 0 0 8 39 0 0 0 0 0 01985 12 17 34 0 0 0 0 7 32 0 0 0 0 0 01986 12 17 27 0 0 0 0 7 32 0 0 0 0 0 01987 10 15 20 0 0 0 0 6 29 0 0 0 0 0 01988 9 13 13 0 0 0 0 5 25 0 0 0 0 0 01989 8 11 7 0 0 0 0 4 21 0 0 0 0 0 01990 6 14 0 0 0 0 32 59 28 10 0 0 0 0 01991 6 14 0 0 0 0 33 60 28 10 0 0 0 0 01992 12 28 0 0 0 0 65 120 55 21 0 0 0 0 01993 12 27 0 0 0 0 62 114 53 20 0 0 0 0 01994 12 121 0 161 71 71 60 110 52 19 56 36 36 36 361995 14 166 0 227 102 102 69 126 60 22 68 51 51 51 511996 2 9 0 367 30 30 147 119 2 23 15 15 15 15 151997 0 2 0 14 2 2 177 363 12 121 1 1 1 1 11998 15 171 0 51 25 25 396 413 18 40 13 12 12 12 121999 85 213 0 592 213 213 258 250 22 52 128 107 107 107 1072000 460 819 0 518 288 288 264 174 37 83 149 144 144 144 1442001 766 430 0 302 256 256 244 27 72 115 140 128 128 128 1282002 340 221 0 192 106 106 295 1 91 210 54 53 53 53 532003 322 259 0 100 220 220 183 0 41 271 111 110 110 110 1102004 307 335 0 137 193 193 211 6 50 523 98 97 97 97 972005 243 93 0 59 119 119 24 57 82 8 60 60 60 60 602006 599 274 0 261 256 256 44 88 74 14 128 128 128 128 1282007 60 70 0 51 17 17 44 93 92 14 9 9 9 9 92008 57 86 0 28 0 0 9 48 162 3 0 0 0 0 02009 115 132 0 19 28 28 12 59 184 4 14 14 14 14 142010 146 150 0 34 46 46 4 44 176 1 23 23 23 23 23

16: Penaeidae; 17: Ariidae; 18: Scomberoides spp.; 19: Haemulidae; 20: Gerres oyena; 21: Trichiurus spp.; 22: Scomberomorus commerson; 23: Lutjanus bohar; 24: Scomberoides commersonnianus; 25: Scombridae <Tunas>; 26: Platycephalidae; 27: Formio niger; 28: Lupa pelgica; 29: Soleidae; 30: Tetradontidae

Eritrea - Tesfamichael and Mohamud 103

Table A12 continuedYear 31 32 33 34 35 36 37 38 39 40 41 42 43 44 451950 0 0 0 0 0 0 0 1 0 1 0 0 0 0 411951 0 0 0 0 0 0 0 1 0 1 0 0 0 0 411952 0 0 0 0 0 0 0 1 0 1 0 0 0 0 411953 0 0 0 0 0 0 0 1 0 1 0 0 0 0 411954 0 0 0 0 0 0 0 1 0 1 0 0 0 0 411955 0 0 0 0 0 0 0 1 0 1 0 0 0 0 411956 0 0 0 0 0 0 0 1 0 1 0 0 0 0 411957 0 0 0 0 0 0 0 1 0 1 0 0 0 0 411958 0 0 0 0 0 0 0 3 0 3 0 0 0 0 01959 0 0 0 0 0 0 0 3 0 3 0 0 0 0 01960 0 0 0 0 0 0 0 6 0 6 0 0 0 0 01961 0 0 0 0 0 0 0 12 0 12 0 0 0 0 01962 0 0 0 0 0 0 0 14 0 14 0 0 0 0 01963 0 0 0 0 0 0 0 15 0 15 0 0 0 0 01964 0 0 0 0 0 0 0 13 0 13 0 0 0 0 01965 0 0 0 0 0 0 0 13 0 13 0 0 0 0 01966 0 0 0 0 0 0 0 13 0 13 0 0 0 0 01967 80 0 0 0 0 0 0 13 0 13 0 0 0 0 01968 80 0 0 0 0 0 0 13 0 13 0 0 0 0 01969 0 0 0 0 0 0 0 15 0 15 0 0 0 0 01970 0 0 0 0 0 0 0 13 0 13 0 0 0 0 01971 0 0 0 0 0 0 0 12 0 12 0 0 0 0 01972 80 0 0 0 0 0 0 12 0 12 0 0 0 0 01973 78 0 0 0 0 0 0 9 0 9 0 0 0 0 01974 76 0 0 0 0 0 0 6 0 6 0 0 0 0 01975 74 0 0 0 0 0 0 6 0 6 0 0 0 0 01976 72 0 0 0 0 0 0 6 0 6 0 0 0 0 01977 75 0 0 5 5 0 6 3 0 2 0 0 0 0 01978 73 0 0 5 5 0 6 2 0 1 0 0 0 0 01979 71 0 0 5 5 0 6 2 0 1 0 0 0 0 01980 61 0 0 7 6 0 8 2 0 1 0 0 0 0 01981 55 0 0 6 6 0 7 1 0 0 0 0 0 0 01982 50 0 0 7 7 0 8 1 0 0 0 0 0 0 01983 50 0 0 12 12 0 15 1 0 0 0 0 0 0 01984 43 0 0 11 10 0 13 1 0 0 0 0 0 0 01985 36 0 0 9 9 0 11 1 0 0 0 0 0 0 01986 30 0 0 9 9 0 11 1 0 0 0 0 0 0 01987 24 0 0 8 8 0 9 1 0 0 0 0 0 0 01988 18 0 0 7 7 0 8 1 0 0 0 0 0 0 01989 11 0 0 6 6 0 7 1 0 0 0 0 0 0 01990 5 0 0 24 18 0 7 0 18 0 0 0 11 9 01991 5 0 0 24 18 0 7 0 19 0 0 0 11 9 01992 9 0 0 49 36 0 15 1 37 0 0 0 23 19 01993 9 0 0 46 34 0 14 1 35 0 0 0 21 18 01994 9 0 37 45 33 27 14 19 34 18 0 22 21 17 01995 11 0 53 52 38 38 17 27 39 26 0 32 24 20 01996 5 0 116 25 1 58 2 7 102 7 0 0 0 1 01997 7 0 0 105 2 0 3 1 122 1 0 0 27 57 01998 0 3 38 86 11 0 4 7 115 6 0 1 69 47 01999 0 0 137 38 74 19 6 54 98 53 3 22 46 41 02000 0 456 256 45 112 188 8 72 16 72 2 115 32 39 02001 0 138 156 114 51 95 15 64 0 64 2 122 112 35 02002 0 148 86 37 52 11 58 26 0 26 110 62 34 7 02003 0 53 146 1 9 5 80 55 0 55 177 49 25 0 02004 8 159 50 8 22 6 34 49 0 48 130 68 0 0 02005 20 45 23 35 30 3 33 32 14 30 20 18 11 7 02006 16 111 70 42 34 270 116 66 25 64 197 85 15 13 02007 21 2 9 48 39 6 28 7 25 4 1 5 16 13 02008 43 2 0 48 46 0 53 4 5 0 0 0 3 2 02009 49 69 14 56 53 10 60 12 7 7 0 8 4 4 02010 47 88 22 50 49 16 58 16 3 11 0 13 2 1 0

31: Euthynnus affinis; 32: Pomadasys argenteus; 33: Lutjanidae; 34: Lethrinus microdon; 35: Lutjanidae <Job fishes>; 36: Rastrelliger kanagurta; 37: Rachycentridae; 38: Mullidae; 39: Pristipomoides multidens; 40: Squilla spp.; 41: Scombridae; 42: Bothus pantherinus; 43: Epinephelus chlorostigma; 44: Epinephelus malabaricus; 45: Carangoides malabaricus

104Table A12 continuedYear 46 47 48 49 50 51 52 53 54 55 56 57 58 59 601950 0 38 0 5 0 0 12 1 0 0 0 0 0 0 951951 0 38 0 5 0 0 12 1 0 0 0 0 0 0 951952 0 38 0 5 0 0 12 1 0 0 0 0 0 0 951953 0 38 0 5 0 0 12 1 0 0 0 0 0 0 951954 0 38 0 5 0 0 12 1 0 0 0 0 0 0 951955 0 38 0 5 0 0 12 1 0 0 0 0 0 0 951956 0 38 0 5 0 0 12 1 0 0 0 0 0 0 951957 0 38 0 5 0 0 12 1 0 0 0 0 0 0 951958 0 0 0 5 0 0 0 1 0 0 0 0 0 0 1071959 0 0 0 5 0 0 0 1 0 0 0 0 0 0 1071960 0 0 0 5 0 0 0 1 0 0 0 0 0 0 1501961 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2151962 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2271963 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2401964 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2151965 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2141966 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2721967 0 0 0 5 0 0 0 1 0 0 0 0 0 0 3081968 0 0 0 5 0 0 0 1 0 0 0 0 0 0 3151969 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2891970 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2761971 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2651972 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2971973 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2711974 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2381975 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2291976 0 0 0 5 0 0 0 1 0 0 0 0 0 0 2261977 0 0 3 5 0 1 0 1 0 0 0 0 0 0 1241978 0 0 3 1 0 1 0 1 0 0 0 0 0 0 1121979 0 0 3 1 0 1 0 1 0 0 0 0 0 0 981980 0 0 4 1 0 1 0 1 0 0 0 1 0 0 1371981 0 0 4 1 0 1 0 1 0 0 0 0 0 0 1151982 0 0 4 1 0 1 0 1 0 0 0 1 0 0 1241983 0 0 8 1 0 2 0 1 0 0 0 1 0 0 2061984 0 0 7 1 0 2 0 1 0 0 0 1 0 0 1761985 0 0 6 1 0 1 0 1 0 0 0 1 0 0 1471986 0 0 6 1 0 1 0 1 0 0 0 1 0 0 1451987 0 0 5 1 0 1 0 1 0 0 0 1 0 0 1221988 0 0 4 1 0 1 0 1 0 0 0 1 0 0 1001989 0 0 4 1 0 1 0 1 0 0 0 0 0 0 771990 8 0 3 1 3 2 0 1 1 0 0 0 0 1 221991 8 0 3 1 3 2 0 1 1 0 0 0 0 1 221992 17 0 6 1 6 3 0 1 3 0 0 1 0 1 441993 16 0 6 1 6 3 0 1 3 0 0 1 0 1 421994 15 0 6 1 5 3 0 1 3 0 0 1 0 1 3921995 17 0 7 1 6 3 0 1 3 0 0 1 0 1 5641996 6 0 3 1 2 0 0 1 1 5 0 0 0 0 3281997 32 0 3 1 19 0 0 1 10 27 0 0 0 5 541998 20 0 0 1 27 0 0 1 8 0 0 0 0 2 1671999 46 0 1 1 5 0 0 1 7 0 0 1 0 0 8032000 39 0 1 1 4 0 0 1 4 0 0 1 0 6 1,7372001 34 0 1 2 10 2 0 1 4 0 1 0 0 3 1,1762002 10 0 3 1 0 4 0 1 0 0 7 0 0 1 8402003 1 0 4 4 0 25 0 1 0 0 0 0 0 1 1,0082004 0 0 6 1 0 9 0 1 0 0 0 1 0 0 8522005 6 0 13 1 2 4 0 1 1 0 0 2 0 1 6212006 11 0 11 1 4 4 0 1 2 0 24 1 29 1 1,4072007 11 0 14 1 4 4 0 1 2 0 0 2 0 1 1672008 2 0 27 1 1 7 0 1 0 0 0 4 0 0 1432009 3 0 31 1 1 8 0 1 1 0 0 4 0 0 3042010 1 0 30 1 0 7 0 1 0 0 0 4 0 0 392

46: Lutjanus gibbus; 47: Saurida tumbil; 48: Chanos chanos; 49: Palinuridae; 50: Lethrinus mahsena; 51: Bothidae; 52: Pomadasys opercularis; 53: Gastropoda; 54: Lethrinus lentjan; 55: Thunnus tonggol; 56: Portunidae; 57: Istiophoridae; 58: Plectorhinchus schotaf; 59: Scombridae <Mackerels>; 60: Others

Yemen - Tesfamichael et al. 105

the marine fisheries of yemen with emphasis on the red sea and Cooperatives1

Dawit Tesfamichaela,b, Peter Rossinga and Hesham Saeedc

a Sea Around Us, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada

b Department of Marine Sciences, University of Asmara, Eritreac Marine Research and Resource Center, Hodeidah, Yemen

d.tesfamichael @fisheries.ubc.ca; p.rossing @fisheries.ubc.ca; alsaeed_co @yahoo.com

abstraCt

The marine fisheries catches in the Exclusive Economic Zone (EEZ) of Yemen are reconstructed from 1950 to 2010 using published literature, local reports, databases and interviews, with emphasis on the Red Sea. Reported catches were first separated into the Red Sea and Gulf of Aden, then into different sectors, artisanal, subsistence and industrial, and further into taxonomic composition. In the Red Sea waters of Yemen, the only active fisheries were the artisanal and subsistence until 1970; then, the industrial fishery started. The total catch remained low (around 10,000 t·year-1 in the 1950s) until the formation of fishery cooperatives and the availability of loans from the Agricultural Credit Bank in the mid-1970s, which allowed for the motorization of many vessels. The peak catch of about 90,000 t·year-1 was achieved at the end of 1990s and then it declined to about 44,000 t·year-1 by the end of 2000s. The industrial fishery picked up only in the mid-1990s, but its catches began to decline around 2003. The reconstructed catches were 1.9 times the Food and Agriculture Organization (FAO) catch data for the Red Sea part of Yemen.

In the Gulf of Aden, inshore pelagic fishes make up the largest amount of the total catch, while the catch of coral reef-associated fishes has declined. The demersal fish catch fluctuated, depending on access agreements for foreign trawlers to operate in Yemeni waters. The total catch was around 40,000 t·year-1 in the 1950s, increased to about 175,000 t·year-1 in the mid-1980s (mainly due to a trawling fishery which did not survive the re-unification of South and North Yemen in 1990) then massively increased, with peak catches of above 350,000 t·year-1 in the 2000s. Overall, reconstructed catches were 2.1 times the FAO data for the Gulf of Aden part of Yemen. Although the total number of taxa in the catch is very high, 7 taxa accounted for more than 50% of the total catch in the Red Sea and 4 in the Gulf of Aden.

introduCtion

The Republic of Yemen is situated on the southwest corner of the Arabian Peninsula, and is bordered by Saudi Arabia to the North, the Red Sea to the West, the Gulf of Aden and the Arabian Sea to the South and Oman to the East (Figure 1). Hence, Yemen has access to both the Red Sea and the Gulf of Aden. Prior to its (re)unification, in 1990, Yemen consisted of two entities, the Yemen Arabic Republic (YAR; or North Yemen) and the People’s Democratic Republic of Yemen (PDRY, or South Yemen). The border between the two entities was where the Red Sea opens to the Gulf of Aden; hence, the Yemeni Red Sea coast was entirely part of the North Yemen (YAR) and the Gulf of Aden under South Yemen (PDRY). This research emphasizes the fisheries along the Red Sea coast of Yemen. All the fisheries, both by domestic fleets and foreign, are included. However, for completeness’ sake, an account of the Gulf of Aden fisheries is also given in Appendix B. In the following, the waters off ‘North Yemen’ and the waters along the ‘Red Sea coast of Yemen’ are treated as synonymous, as are ‘South Yemen’ and ‘Gulf of Aden waters of Yemen’.

Yemen is divided into governorates and three of these border the Red Sea, i.e., Hajja, Al Hodeidah and Ta’izz. Fish are landed at 31 locations along the Red Sea coast with the largest proportion occurring in the Al Hodeidah governorate (Akester 2007). The main ports where fishing is concentrated are Hodeidah, Al Khauka, Al Khoba and Mocha.1 Cite as: Tesfamichael, D., Rossing, P. and Saeed, H. (2012) The marine fisheries of Yemen with emphasis on the Red Sea and cooperatives. pp. 105-152. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosysytem by countries (1950-2010). Fisheries Centre Research Reports 20(1). Fisheries Centre, University of British Columbia [ISSN 1198-6727].

Figure 1. The Red Sea coast of Yemen with its shelf area and Exclusive Economic Zone (EEZ).

106

The waters off Yemen include a shelf area of 41,000 km2 (FAO 2002a). Overall, these waters exhibit a high level of primary and secondary production, and hence the country is endowed with considerable fisheries resources. This is especially true for the Gulf of Aden, whose catches, as it will be shown below, were generally well above those from the Red Sea coast.

To date, over 600 commercial species of fish and invertebrates have been recorded from Yemen (see www .fishbase.org). Of these, 40 species (mainly pelagic) contribute the bulk of the Red Sea catch, notably sharks, jacks and tunas (Brodie et al. 1999). The fisheries are an important source of foreign exchange, generating an estimated 2–3% of Yemen’s GDP in the mid-2000s (Koehn and Aklilu 1999; FAO 2002a).

The Yemeni Ministry of Fish Wealth (MoFW) is mandated with the management of fishery resources, and controls the licensing of boats and the collection of data, while the Marine Research and Resource Center (MRRC) is a government institute active in fisheries and environmental research. Both institutions collaborate when conducting fisheries research, which faces numerous human and financial constraints that have affected the data collection system. Their branch offices in Hodeidah are responsible for the Red Sea coast of Yemen. The fishing activities of Yemen can be broadly divided into (a) artisanal (small scale), (b) subsistence and (c) industrial (large scale). Recreational fishery does not exist in Yemen (Morgan 2006).

Artisanal

Yemen has a long history and tradition of artisanal fisheries. Yemeni fishers are the most experienced in the wider Red Sea, where they operate, legally or not, along the coasts of several countries. Yemeni fishers also venture into the Indian Ocean, and in their wide range of operation, they are similar to the Fante people of West Africa (Atta-Mills et al. 2004). They are also innovative, and were often the first to introduce new fishing practices and gears. Yemeni fishers also benefit from well-organized cooperatives, a financing system and an infrastructure unique among countries in the region, that includes a logistics system which provides them with all the basic necessities for their fishing trips such as fuel, food and gear. There are anecdotal evidences that Yemeni artisanal fishers venture out from the EEZ of Yemen and fish in neighboring countries waters.

Many coastal people of Yemen depend on fishing for their livelihood. In the Red Sea, the number of Yemeni fishers has increased from approximately 3,000–4,500 in the mid-1970s to over 37,000 in 2007, while the number of artisanal boats grew from approximately 1,000 to 7,600 (Walczak and Gudmundsson 1975; Agger 1976; MoFW 2008). The reported artisanal Red Sea landing, however, declined from its peak 51,247 t in 1993 to 28,641 t in 2007 and in 2010, it declined further, to 20,751 t (MoFW 2008, 2012) as many species have become over-exploited (Morgan 2006).

The artisanal or traditional fisheries are mainly restricted inshore, with fishing taking place close to the landing areas and targeting mostly pelagic species (PERSGA 2001). Catches are landed directly on the beach, or are brought beyond the surf line, on the back of porters (Bonfiglioli and Hariri 2004). The primary vessels used in artisanal fisheries are sambouk, a wooden vessel which can range from 12 to 20 m, with an inboard diesel engine, and houri, a smaller canoe like vessel of 7–12 m, fitted with outboard engine and/or sails (Sanders and Morgan 1989). In the 1970s, Yemen’s artisanal fleet underwent massive technological changes; notably, sailing houris were motorized as fishers got access to loans from the Yemeni government and foreign aid agencies (Barraniya 1979). In the mid-1970s, the Agricultural Credit Bank was established and, together with the flourishing of fishery cooperatives, facilitated the growth of fisheries. This trend has continued and engines have become more powerful, enabling skippers to operate further away from shore with larger crew (Walczak and Gudmundsson 1975; Brodie et al. 1999). This, combined with the availability of ice has enabled fishing trips to last for several days (PERSGA 2001). Hook and line fishing (hand or troll); gillnetting (drifting or set) and purse seine are the most important types of gears used (Barraniya 1979). A small number of sambouks have, since the 1980s, also been equipped to trawl for shrimp (Sanders and Morgan 1989). Besides those gears, there are some minor fisheries in which artisanal fishers get involved, such as crabs, cuttlefish and sea cucumber fisheries for which diverse gears such as trap, skin and hookah diving, spears etc… are used.

Most of the artisanal catch is consumed locally; however, export of the higher value component of the catch of artisanal fisheries is growing. The low grade fish, such as Indian mackerel, are dried and sold all the way to the interior of Yemen. Yemeni society, especially along the coast, has a long tradition of seafood consumption. Fisheries are an important part of the socio-economic and cultural part of the community, and command strong political and financial support, partly due to the strength and success of the fishery unions, important in organizing and financing the fishery.

Subsistence

Subsistence fishing takes place at beaches free of rocks and coral reefs using beach seines to catch sardines, anchovy and other small pelagic species, locally referred to as ‘wasif’ fishery (Walczak 1977). This is the least capital intensive fishery and solely for consumption by local communities; hence it is here categorized as a subsistence fishery. In addition to the small pelagic fishery, the subsistence fishery includes the catch of the artisanal fishery that is consumed by the crew and the catch that is freely given to family, friends and part of the communities who need such help. This portion can be as much as half of the total catch in the earlier years. Hence, it is important to explicitly represent this component in the catch reconstruction, even though it declined as the marketing of seafood grew.

Yemen - Tesfamichael et al. 107

Industrial

Prior to reunification, the PDRY and YAR sought to develop their fisheries in different ways. The government of South Yemen focused on the development of industrial foreign and state-owned fisheries in the 1970s and the early 1980s, while that of North Yemen aimed to develop its artisanal small scale fisheries, notably by offering loans to fishers to improve their boats and equipment (Koehn and Aklilu 1999). Thus, industrial fishing was extremely rare in the YAR, one of the exceptions being shrimp trawling by a Kuwaiti company operating along the Red Sea coast of Yemen from 1970 to 1978 (Walczak and Gudmundsson 1975; Sanders and Morgan 1989; Morgan 2006). However, following reunification, industrial vessels that had been operating in the Gulf of Aden were granted access to the Red Sea as well. From 1993 to 2010, most of the trawlers were from Egypt and a few from Lebanon. In 1998, there were 63 licensed boats in the Red Sea, catching a total of 4,200 t (FAO 2005). At present, the landings from industrial vessels consists mostly of shrimp, cuttlefish, emperor, snappers, lizardfish and threadfin fish. Estimates from Brodie et al. (1999) suggested that industrial vessels were typically 20–40 meter long, with motors of 500–800 hp, and caught 600–800 kg/day of shrimp, which is much higher than the 25 kg of shrimp caught daily by sambouks in the same period. The rapid growth of effort and the changes it induced in the last few decades have led to dramatic decline in catch rates, which could be a sign of overfishing in many areas and leading, among other things, to conflict between artisanal and industrial fisheries (Bonfiglioli and Hariri 2004).

While Yemen has introduced recent measures to better control industrial fishing, its limited capacity to effectively monitor existing regulations has limited the impact of these measures (Pramod et al. 2008). Compounding the overfishing issue, official catch statistics greatly misreport what is caught (Morgan 2006). Reported landings have historically not accounted for all species and have failed to include the recent drastic increase in the number of artisanal boats (Herrera and Lepere 2005). Official landing statistics have overlooked significant illegal, unregulated and unreported (IUU) catches, known to be substantial in Yemen’s industrial fishing sector (Koehn and Aklilu 1999).

Thus, the aim of this study is to reconstruct Yemen’s catch statistics from 1950 to 2010 in order to provide fisheries scientists and managers with more reliable information on which to base their fisheries policies. The main focus of this report is Yemen’s fishery in the Red Sea. However, a brief description and catch reconstruction of the Gulf of Aden is also included, to obtain a comprehensive understanding of Yemeni fisheries and also to allow for comparison between Yemen’s Red Sea and Gulf of Aden fisheries. Catches are reconstructed and presented by sectors and taxonomic composition of each sector. Further, the reconstructed catches are compared with the data Yemen reported to FAO.

materials and methods

Separating the FAO data into Red Sea and Gulf of Aden

Yemen reports its catch annually to the FAO through one data set for the country which combines both the Red Sea and Gulf Aden, and thus needs to be split, as the two seas are here treated separately. For this, we used sources which reported the catch of the two seas separately, i.e., the catch ratios they provided were used to divide the total Yemen catch in the FAO records into their respective seas. Sanders and Morgan (1989), PERSGA (2001), (FAO 2002b), MoFW (2004) and MoFW (2008) provided reported total landings for both the Red Sea and the Gulf of Aden/Arabian Sea for the periods 1976–1986, 1986–1994, 1998, 2002–2003 and 2006–2007, respectively (Table 1). For 1986, data were obtained from Sanders and Morgan (1989) for the Red Sea and from (PERSGA 2001) for the Gulf of Aden and Arabian Sea. We used the reported proportions to divide the FAO data into Gulf of Aden and Red Sea components for these years. Also, in absence of a better alternative, the estimated catch proportion for 1976 was used for the period 1950–1975. All other missing years were estimated using interpolation except for 2009 and 2010, where the average ratio from 2006 to 2008 was used (Table 1, Figure 2). This split was used as an initial value to compare the reconstructed values with the FAO data and to calculate the reconstructed catch as a proportion of the FAO data for the reconstruction of Yemeni catch in the Gulf of Aden (see below). The final FAO data for each sea, however, were calculated latter by taking into account the taxonomic breakdown information which caused the proportions to change slightly, so this first split is not necessarily representative of the final data set.

Figure 2. Marine fisheries catch of Yemen, 1950–2010, as reported to FAO by Yemen for both the Red Sea and the Gulf of Aden.

108

Catch reconstruction for the Red Sea waters of Yemen, 1950–2010

No catch statistics exist that present Yemen’s landings in the Red Sea as a complete time series from 1950 to 2010. Similarly, no published information was found that accounts for the unreported catches in Yemen. Catch time series were therefore estimated using a reconstruction method based on assumption-driven inferences (Pauly 1998; Zeller and Pauly 2007). Such an approach is justified, despite data uncertainties, given the less acceptable alternatives that users of official data will interpret non-reported or missing data components as zero catches (Pauly 1998; Pitcher et al. 2002; Tesfamichael and Pitcher 2007). Using data from published, gray literature and interview sources as anchor points, time series data can be reconstructed using interpolation and extrapolation (Tesfamichael and Pauly 2011). Anchor points included fishery surveys, national reported catch data, peer-reviewed literature, and field trip interviews and data collected in Yemen by the first author in 2007. We worked in close collaboration with local experts from Yemen’s Ministry of Fish Wealth (MoFW) and Marine Research and Resource Center (MRRC) to get feedback, and update our results.

The Yemeni artisanal and industrial catches in the Red Sea (i.e., of pre-unification North Yemen) were estimated separately. For the artisanal fisheries, this involved reconstructing landings and unreported catch for the major fisheries targeting large pelagics and coral reef-associated fishes using houri and sambouk, which constitute the ‘artisanal fisheries’. The same procedure was needed for the beach seine fishery (a subsistence fishery). Also reconstructed were the catches of the minor artisanal fisheries for sea cucumber, crabs, and cuttlefish. For the industrial fishery, the elements involved in the reconstruction included estimating reported landings, discards and unreported landings. The estimation of catch composition was mostly based on reports with reliable data and the database of the Ministry of Fish Wealth (MoFW), with interpolations for missing years. Last but not least, we also classified the reconstructed total catch into their taxonomic composition and ecological guilds.

Artisanal fisheries

Reported landings

The first catch estimates for Yemen in the Red Sea were made in the 1970s by the staff of FAO field projects, based on surveys of the artisanal fisheries for the number of boats, number of fishing days and catch rates to derive yearly catches for the various boat types (Agger 1976; Campleman 1977; Walczak 1977; Barraniya 1979). They provided reliable estimates for Yemen’s houri and sambouk catches for the 1970s, which are used as anchor points.

Barraniya (1979) presented two different sets of catch statistics covering 1970–1978: one based on the General Directorate of Hodeidah and another based on the Central Planning Agency of Yemen. The former data set was used because its data matched the results of an independent extensive survey for 1973 by Agger (1976). As these data did not pertain to a calendar year, but applied from June to May of the next year (Walczak 1977), they were adjusted to the calendar year using monthly catch ratios for 1975 (Barraniya 1979). This approach reconstructed only 6 months of the catches for 1970 and 1978. For those two years, total annual catch was calculated using the average proportions from 1971 to 1977. Since most of the catch by the artisanal fisheries was for local consumption, we assumed, to estimate the total catch from 1950 to 1969, that catches grew proportionally with Yemen’s population. Hence, catches from 1950 to 1969 were estimated using 1970 as an anchor point and population sizes given in www

.populstat.info/ (Table 2).

Table 1. Sources used to split the total catch data submitted by Yemen to FAO into Red Sea, and Gulf of Aden and Arabian Sea components from 1950 to 2010.Period Red Sea Gulf of Aden Source/Remarks1950–75 0.20 0.80 Assumed 1976 value1976 0.20 0.80 Sanders and Morgan (1989)1977 0.21 0.79 Sanders and Morgan (1989)1978 0.29 0.71 Sanders and Morgan (1989)1979 0.26 0.74 Sanders and Morgan (1989)1980 0.16 0.84 Sanders and Morgan (1989)1981 0.17 0.83 Sanders and Morgan (1989)1982 0.17 0.83 Sanders and Morgan (1989)1983 0.20 0.80 Sanders and Morgan (1989)1984 0.18 0.82 Sanders and Morgan (1989)1985 0.19 0.81 Sanders and Morgan (1989)1986 0.20 0.80 Sanders and Morgan (1989), PERSGA (2001)1987 0.19 0.81 PERSGA (2001)1988 0.24 0.76 PERSGA (2001)1989 0.24 0.76 PERSGA (2001)1990 0.35 0.65 PERSGA (2001)1991 0.42 0.58 PERSGA (2001)1992 0.46 0.54 PERSGA (2001)1993 0.50 0.50 PERSGA (2001)1994 0.54 0.46 PERSGA (2001)1995 0.50 0.50 Interpolation1996 0.47 0.53 Interpolation1997 0.43 0.57 Interpolation1998 0.39 0.61 FAO (2002)1999 0.34 0.66 Interpolation2000 0.29 0.71 Interpolation2001 0.25 0.75 Interpolation2002 0.20 0.80 MoFW (2004)2003 0.15 0.85 MoFW (2004)2004 0.14 0.86 Interpolation2005 0.14 0.86 Interpolation2006 0.14 0.86 MoFW (2008)2007 0.17 0.83 MoFW (2008)2008 0.24 0.76 MoFW (2012)2009–10 0.18 0.82 Average of 2006–08

Yemen - Tesfamichael et al. 109

Brodie et al. (1999) reported landings were used for 1979–1982 and 1987–1997. Landings provided by Sanders and Morgan (1989) were used, instead of the ones reported by Brodie et al. (1999), for the years 1983 – 1986, as these data had a better species breakdown. A dataset of the Ministry of Fish Wealth was used for the years 1998 – 2007 (MoFW 2004, 2008) and 2008 – 2010 (MoFW 2012). Table (2) summarizes the equations, assumptions and sources used to estimate the reported artisanal catch landings from 1950 to 2010.

Unreported catch

Reported landings for Yemen’s artisanal fisheries are believed to be severely underestimated (Chakraborty 1984; Koehn and Aklilu 1999; PERSGA 2001; Herrera and Lepere 2005; Morgan 2006; Pramod et al. 2008). In Yemen, fishers do not necessarily land their catches at landing sites where landings are recorded. Based on interviews with fishers, a sizeable fraction of the total catch is landed in areas remote from major landing sites, where it goes unreported (Tesfamichael et al. in press).

In the 1970s, reported landings were based on the number of boats multiplied by observed landings, based on observations for some landing places and some days of the year (Chakraborty 1984). Interviews with fishers who were active since the 1950s suggest that they graded their catch. Usually the high grade fish and the big size fish of the chosen fishes were sold in the formal market where fishery statistics were recorded, and the rest was sold in the informal markets. This is supported by the relatively small number of taxa reported in early statistics. Sanders and Morgan (1989) noted that grading was an issue in the artisanal fisheries. Species now landed, notably catfish, sharks and the smaller grunts, were not preferred in the past. So, we assumed, conservatively, the level of under-reporting, to have been 30% of the reported landing from 1950 to 1975.

In the mid-1970s, Yemen’s catch statistics for the Red Sea improved considerably as a more comprehensive system of fisheries data collection was put in place (Sanders and Morgan 1989). The catch data we used from 1983 to 1986, provided by Sanders and Morgan (1989), were therefore considered quite reliable (Herrera and Lepere 2005). The level of underreporting was assumed to be 20% and 10% for 1976–1982 and 1983–1990, respectively. For about a decade after 1991, no reliable analysis of landings statistics, resource surveys or stock assessments were undertaken, due to the system for collecting fisheries statistics having broken down after the re-unification of Yemen. This resulted in gross underestimation of artisanal catches. Thus, for example, statistics were not adjusted for the growth of the artisanal fishery, including the number of boats, failed to account for fish sold outside auctions and relied on historical prices to convert auction sales to weight (Koehn and Aklilu 1999; PERSGA 2001; Herrera and Lepere 2005; Morgan 2006). We assumed the level of unreported catch to be 20% for the period 1991–2001. Catch statistics after 2002 are believed to have improved, as Yemen took a number of steps to improve its fisheries management with external financial and technical assistance (Morgan 2006). Thus, 10% was assumed to be the level of unreported catch from 2001 to 2010. Table (3) summarizes the values used to estimate the unreported catches from 1950 to 2010.

Catch composition

Catch composition data for 1974–1976 were available in Walczak (1977), which were used to disaggregate our reconstructed total catch (reported and unreported) for the period 1950–1978. However, the constituents of a few groups were modified. Walczak (1977) reported catch ratio for ‘jacks’, a group we split into two, i.e., ‘jacks’ (Carangidae) and ‘queen fish’ (Scomberoides spp.), contributing 72% and 28%, respectively, based on the catch ratio of these species for the years 1979–1986. This was done as interviewed fishers indicated that they always historically caught queen fish. Similarly, snappers (Lutjanidae) and emperors (Letrinidae), which were reported together, were split in a similar way using data from 1979 to 1986, with relative contributions of 25% and 75%, respectively.

The average of the 1983–1986 catch composition reported by Sanders and Morgan (1989) was used to disaggregate total landings from 1979 to 1982. From 1983 to 2010, the data were already reported by taxonomic composition. We used Sanders and Morgan (1989) for 1983–1986, Brodie et al. (1999) for 1987–1997, MoFW (2004, 2008) for 1998–2007 and MoFW (2012) for 2008 – 2010 who reported catch compositions for the periods indicated (See Appendix Table A1).

Table 2. Methods for estimating artisanal fisheries landings 1950 – 2010.Year Procedure Source/Remarks1950-69 (Popn/Pop1970)* Land1970

n = year 1950-1969Catches grew proportional to population size

1970-78 Adjusted reported landings Barraniya (1979)1979-82 Reported Brodie (1999)1983-86 Reported Sanders and Morgan (1989)1987-97 Reported Brodie (1999)1998-2007 Reported MoFW (2004, 2008)2008-10 Reported MoFW (2012)Pop = population; Land = landings

Table 3. Percentages used to estimate unreported catches of the artisanal fisheries in Yemeni Red Sea, 1950–2010.

Year %1950-75 301976-82 201983-90 101991-2001 202002-10 10

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Other minor artisanal fisheries

The relatively minor artisanal fisheries included in this group target sea cucumber (Holothuroidea), crabs (Brachyura) and cuttlefish (Sepiidae). Sea cucumbers have been harvested for many years, but have traditionally been omitted from the catch statistics (Bonfiglioli and Hariri 2004). Catch data for this fishery are therefore very sporadic. Walczak (1977) indicated that 20 t of sea cucumber were exported in 1975. Sea cucumber landings were also reported from 2000 to 2010 (MoFW 2012). As sea cucumber catches are reported in dry weight units we converted the reported catch data to wet weight by multiplying them by a factor of 9.54 based on Purcell et al. (2009). Based on qualitative information from interviews, we assumed that catches began in 1970 and used interpolations between anchor points to derive the missing years 1971–1974 and 1976–1999.

Records of the artisanal catches for crab and cuttlefish were only available for 2002–2003 (MoFW 2004) and for 2006 – 2010 (MoFW 2012). Based on interviews, these taxa are likely to have been caught in the past as well, but remained unrecorded, as is the case for the sea cucumber fishery. Catches for 1950–2001 were estimated by adjusting the catch from 2002 relative to estimated population size. The catches for 2004–2005 were interpolated between the landings of 2003 and 2006. Tables (4 and 5) summarize the equations, assumptions and sources used to estimate the reported artisanal landings of sea cucumber, cuttlefish and crabs from 1950 to 2010.

Subsistence fishery

The subsistence fishery includes beach seining for small pelagic fishes, which is considered an entirely subsistence fishery, and the catch of the artisanal fishery that is consumed by the crew and/or given to family, friends and people in the fishing communities who need help.

The beach seine fishery for sardines and anchovies was estimated to be 1,500 t in 1976 (Walczak 1977). Unfortunately, no other data point was available. However, based on interviews with fishers, it appeared that the fishery has been active for a long time at subsistence levels. The catch for the whole period 1950–2010 was calculated by assuming that it was directly proportional to Yemen’s population size. This is reasonable, because the beach seine fishery catches were mainly subsistence and strongly affected by population size. However, an adjustment was applied to the population-related catches from 1976 to 2010, where a multiplier of 1 was used for 1976 and 0.5 for 2010 and the multipliers between the two points were interpolated. This was done to reflect the likely decrease in catch per unit effort of the fishery over its long period of operation and arrive at a conservative catch estimate.

The subsistence fishery catch that comes from the artisanal fishery was calculated from a ratio of the artisanal fishery catch (excluding the minor artisanal fishery described above). We assumed the subsistence catch to be 30% of the artisanal catch from 1950 to 1974. The ratio was reduced to 20% for 1975, when the motorization of the artisanal fleet was in full swing and the artisanal fishery started to become more commercialized, hence likely decreasing the proportion of the catch freely given to the community. The ratio was assumed to be 10% in 2010 and the ratios between 1975 and 2010 were interpolated. Based on interviews with fishers and the fishery administration in Yemen, fishers used to give up to 50% of their catch away, so these ratios are quite conservative.

Industrial fisheries

The industrial fisheries in the Yemeni Red Sea waters are operated by foreign vessels. Reported, unreported catches and discards were reconstructed as three separate components of industrial fisheries from 1950 to 2010 in Yemen’s Red Sea. Industrial fishing in Yemen’s Red Sea went through three distinct phases. First, there was a period of limited shrimp trawling in the 1970s (Agger 1976; Walczak 1977), followed by a period of no industrial fishing lasting from the 1980s to the early 1990s (Chakraborty 1984; PERSGA 2001), and lastly a period characterized by an in-flux of foreign bottom trawlers from 1992 to 2010 MoFW (2004, 2008, 2012).

Table 5. Methods used for estimating landings of cuttlefish and crabs 1950 – 2010.

Year Procedure Source/Remarks1950-2001 Popi* Per capita catch2002;

i= 1950-2001Catches grew proportionally with population

2002-03 Reported catch MoFW (2004)2004-05 Interpolation between

2003-06Catches changed steadily between anchor point years

2006-10 Reported catch MoFW (2012)

Table 4. Methods used for estimating catches of sea cucumbers in Yemen (Red Sea), 1950–2010. Note all dry weights were converted to wet weight.

Year Procedure Source/Remarks1970-74 Interpolation between

1970-75 Sea cucumbers were not caught prior to 1970

1975 Reported dry catch * 9.54 Walczak (1977)1976-99 Interpolation between

1975-2000Catches changed steadily between anchor point years

2000-10 Reported dry catch * 9.54 MoFW (2012)

Yemen - Tesfamichael et al. 111

Reported catch

Industrial fisheries did not begin in Yemen’s Red Sea until the late 1960s. Agger (1976) indicated that the Greek Achilles Frangistas Co. had gained permission to trawl in the waters of Yemen’s Red Sea, Saudi Arabia and Eritrea with at least two 86 m 2,000 HP factory trawlers from the period 1966/1967. As this operation was a form of exploratory fishing with very limited catches, it is not considered here.

Shrimp catches reported by the General Directorate of the Hodeidah from 1970/71 to 1977/78 were used as basis to reconstruct industrial catches for 1970 – 1978 (Barraniya 1979). The catches from 1970/71 to 1973/74 were identical to those reported for the United Fishing Company of Kuwait, or UFCK, formerly Gulf Fisheries. The company operated a total of 43 trawlers and two mother ships until it stopped in May 1974 due to declining catches (Walczak 1977). As the records were for the period lasting from June to May of the next year (Walczak 1977), the catches were recomputed for calendar year based on the assumption that monthly catches had the same distribution as observed in 1975 (Barraniya 1979). This gave an estimate of the industrial shrimp catches for 1970–1978. For 1970 and 1978, this approach only allocates half a year of catch data. These two years where raised to annual catches using seasonal average for 1971–1977.

We assumed industrial catches to be nil between 1979 and 1992, as no industrial fishing occurred in Yemen’s Red Sea in the 1980s and the early 1990s (Chakraborty 1984; PERSGA 2001). It recommenced when Yemen, after reunification, changed its policy to allow foreign fishing fleets access to the Red Sea, beginning with two Lithuanian double-rigged shrimpers in 1993 (PERSGA 2001). The fishing was carried out mainly by Egyptian trawlers and to a less extent by Lebanese from 1993 to 2000, and from 2001 to 2010 by Egyptian only. In 1998, it was reported that 40–44 foreign industrial bottom trawlers caught 4,186 t of shrimp and fin fish (FAO 2002a). Total reported industrial landings for the Red Sea were also available for 2002 and 2003 (MoFW 2004) and 2006 and 2007 (MoFW 2008). These years were used as anchor points, and for the missing years 1993–1997; 1999–2001 and 2004–2005, catches were estimated by interpolation between these anchor points. The total catch for 2008–2010 was estimated using the average ratio between reconstructed catch and FAO data for 2006 and 2007. The average total industrial reconstructed catch, including retained, unreported and discarded, for 2006 and 2007 was 47% of Yemen’s FAO data for the Red Sea. The total was divided between retained and discard using the ratio 1:2, the ratio used from 1993 to 2007 (see discard calculation below). Table (6) summarizes the sources and procedures used to estimate the reported industrial landings from 1950 to 2010.

Unreported catch

The unreported catch refers to the catch that is landed but not recorded in the official statistics, while the discards (see below) refer to the catch that is not recorded nor landed. We added a conservative 10% to the reported landings for the industrial fleet from 1970 to 1978, as the catches of the United Fishing Company of Kuwait (UFCK) fleet were thought to be underreported (Walczak 1977). Yemen now requires observers onboard industrial vessels, but this has not solved the problem, because observer coverage is partial (Pramod et al. 2008), and the effectiveness of the limited onboard observation is also very questionable. Local experts estimate the unreported catch, in the Red Sea, to be 75% of the total catch from 1993 to 2007. Table (7) summarizes the equations, assumptions and sources used to estimate the unreported industrial landings from 1950 to 2007. The unreported catch from 2008 to 2010 is calculated as part of the total industrial catch using the reconstructed catch to FAO ratio as described above.

Discards

Discards are catch that are not landed, hence not recorded as well. Discards from trawling, especially from shrimp, are substantial and must therefore be added as a component of industrial fisheries catch. However, data regarding Yemen’s discard levels in the Red Sea were limited. Lisac (1971), while onboard a United Fishing Company of Kuwait trawler, observed discards from shrimping to be up to three times that of shrimp caught. Losse (1973) found that boats fishing for shrimp discarded approximately 4.4–5.6 t of fish for every tonne of shrimp caught. For 1950–1969, discards were zero as industrial fishing did not occur during these years. For the period 1970–1978, we assumed discards to be 75% of total catch (reported + unreported catch + discards) based on Lisac (1971). A reduced discard

Table 6. Reported landings of industrial fishing vessels in Yemen’s Red Sea.

Year Source/Remarks1950-69 Zero catch Agger (1976)1970-78 Barraniya (1979)1979-92 Zero catch: Chakraborty (1984); PERSGA (2001)1993-97 Interpolation1998 FAO Fishstat (Year)1999-2001 Interpolation2002-03 MoFW (2004)2004-05 Interpolation2006-07 MoFW (2008) 2008-10 Using reconstructed/FAO ratio

Table 7. Industrial fishing boats unreported landings in Yemen’s Red Sea 1950–2010.

Year Procedure Source/Remarks1950-69 n/a Zero catch Agger (1976)1970- 78 Rep. landingsi * 0.1;

i=year 1970-78 Unreported landings were 10% of the reported landings.

1979-92 n/aZero catch Chakraborty (1984); PERSGA (2001)

1993-2007 Rep. landingsi * 0.75; i=year 1993-2007

Unreported landings were 75% of the reported landings.

2008-10 Used reconstructed/FAO ratio

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rate of 67% was assumed from 1993 to 2007, as shrimp were no longer the only species retained. The discard amount from 2008 to 2010 was calculated as part of the total catch, using the average ratio of reconstructed catch (including retained, unreported and discard) to FAO data for 2006 and 2007, i.e., reconstructed catch was 47% of FAO data for the Red Sea. The discarded catch was 67% of the total industrial catch, the ratio used from 1993 to 2007. Table (8) summarizes the equations, assumptions and sources used to estimate industrial discards from 1950 to 2010.

Species composition

The species composition of industrial catches was estimated separately for total retained catches and for discards. For the retained catch, total catches from 1970 to 1978 were assumed to be shrimp only (Barraniya 1979), reflecting the nature of the fishery then. The earliest catch composition data available for Yemen since the industrial fishery started to retain non-shrimp taxa in 1993 were for 2002 and 2003 (MoFW 2004). For the years 1993–2001 we used the weighted average ratios of 2002 and 2003 to calculate the catch composition. Catch composition data were available for 2006 and 2007 (MoFW 2008) whose average values were used for 2004 and 2005. From 2008 to 2010, for which the total retained catch was calculated using the FAO to reconstructed catch ratio of the previous years, the composition was calculated using the weighted average of the ratios from 1998 to 2007. The data for 2002 and 2003 had more generalized categories for which ‘deep water fishes’ accounted for more than 85%. This was later subdivided to taxa using ratios from 2006 and 2007 (Table 9).

Surveys estimating the species composition of trawlers’ discards were available from the FAO research vessel R/V Orion from 1974 to 1977 (Walczak 1977). These percentages were used in unaltered form to breakdown discard totals by species from 1970 to 1978. However, in recent years, many species previously discarded are retained, as the most sought-after species are getting scarcer. Thus, these were removed from the survey, and the total of the ratio of the remaining discarded species was scaled up to 100% to divide the discard into its composition from 1993 to 2010 (Table 10).

Comparing reconstructed catches with FAO data

The catch composition of each sector was compared with the taxonomic composition of the data Yemen reported to FAO (www .fao.org/fishery/statistics/software/fishstat/en). Only the artisanal and industrial sectors were compared with the FAO data, as the subsistence and discarded catches are not reported to FAO. A few taxa were reported to the FAO, but were not in our reconstructed catch composition. They were allocated to the appropriate sector in the reconstruction. Their amount in the reconstructed catch was taken to be the same proportion they had in the total FAO catch. The amounts were later deducted from the ‘others’ of the sector to which they were allocated. For each sector, for the years the group ‘others’ was higher than 10% it was reduced to 10% and the rest distributed to the taxa already identified according to their proportion in each sector.

Table 9. Species composition (%) of total industrial landings in Yemen’s Red Sea 1950–2010.Year Penaeidae Brachyura Sepiidae Nemipterus spp. Synodontidae Lethrinidae Lutjanidae Sources/Remarks1970-78 100.00 0 0 0 0 0 0 Barraniya (1979)1993-2001 7.00 0.64 4.90 27.49 49.98 6.25 3.75 Weighted average of 2002-032002 2.49 0.52 2.08 29.83 54.23 6.78 4.07 MoFW (2004)2003 11.30 0.74 7.58 25.26 45.92 5.74 3.44 MoFW (2004)2004-05 3.12 0.05 20.86 23.88 43.41 5.43 3.26 Weighted average of 2006-072006 2.70 0.08 29.38 21.32 38.77 4.85 2.91 MoFW (2008)2007 3.96 0.00 3.64 29.04 52.80 6.60 3.96 MoFW (2008)2008-10 5.47 0.40 10.40 26.32 47.85 5.98 3.59 Weighted average of 1998-2007

Table 10. Species composition (%) of the discards of the industrial fishery in Yemen’s Red Sea. Main source was Walczak (1977).

Taxon 1970-78 1993-2010Pony fish 31.0 62Malabar jacks 15.0 0Lizard fish 14.0 0Threadfin bream 12.0 0Grunts 4.5 0Grunters 3.5 7Mojarra 2.0 4 Cutlass fish 2.0 4Ariid catfish 2.0 0Other jacks 1.0 0Flatheads 1.0 2Puffers 1.0 2Soles 1.0 2Barracudas 1.0 0Jack pomfret 1.0 2Blue swimming crab 1.0 2Sardines, anchovies 0.5 1Goatfish 0.5 1Mantis shrimp 0.5 1Cuttlefish 0.5 0Other fish 5.0 10

Table 8. Discards from industrial fishing boats fishing in Yemen’s Red Sea 1950–2010.

Year Procedure Source/Remarks1950-69 n/a Zero catch Agger (1976)1970-78 3 * (report. landi + unreport. landi)

i=year 1970-78 Discards were 75% of total catch Lisac (1971)

1979-92 n/a Zero catch Chakraborty (1984); PERSGA (2001)

1993-2007 2 * (report. landi + unreport. landi)i=year 1993-2007

Discards were 67% of total catch using Lisac (1971) as a base

2008-10 Used reconstructed/FAO ratio and discards were 67% of total catch

report. land = reported landing; unreport. land = unreported landing

Yemen - Tesfamichael et al. 113

After the reconstructed and the corresponding FAO catch by taxa were tabulated, comparison was done at the taxonomic level. The part of the reconstructed catch that is accounted in the FAO data is referred as ‘reported catch’ in our result. If the value of a taxon in the reconstructed catch was higher than its value in the FAO data, then the difference was labeled as ‘unreported catch’. If the FAO value for a taxon was higher than the reconstructed catch, the difference is over-reported catch in the EEZ of Yemen into the Red Sea. At this stage, each sector had a more detailed catch composition than it started with in the catch composition methods presented above. Since, the comparison of the reconstructed catch with the FAO data has modified the catch composition of the reconstructed catch, the final ratios are not exactly what is reported in the methodological tables given in the above, including Table (1) that has the ratios to divide the FAO data between the Red Sea and Gulf of Aden. This procedure was done for the Gulf of Aden as well, which his presented in Appendix B.

results

The total catch in Yemen’s EEZ in the Red Sea (both by domestic and foreign fleets) was low, and started to increase in the early 1970s (Figure 3, Appendix Table A2). It reached its peak at the end of 1990s. The majority of Yemen’s catch in its Red Sea EEZ is generated by the artisanal fisheries (66%).

The artisanal catch went through different phases: relatively low level until the beginning of the 1970s, a slow increase until the mid-1980s, followed by a rapid increase until a peak was reached in 1993 and a phase of rapid decline since (Figure 3). The rapid increase was due to motorization of boats. The decline could be caused by a conflict with Eritrea over the Hanish Islands, in the southern part of the Red Sea, which prevented Yemeni from accessing some major fishing grounds. The unreported catch of the artisanal fishery accounted for 40% of the total artisanal catch from 1950 to 2010.

For the period 1993–2007, when the industrial fishery was active, the artisanal catch was on average 58% of the total catch. The contribution of industrial fisheries increased only after 1990, the year of Yemen’s re-unification, when industrial fishing was encouraged, and permission was given to foreign fleets to operate in the Red Sea waters. Overall, the industrial sector accounted for 18% of the reconstructed catch with only 6% being retained. The subsistence catch, third in its contribution (16%), follows the trend of the artisanal fishery, because its main component is computed as a proportion of the artisanal catch. Discards accounted for 12% of the total catch (all from the industrial sector) and appeared mainly after the 1990s with the resumption of industrial fishery.

The category ‘reported’ in Figure (4) and Table (A3) is the amount of the reconstructed catch reported in the FAO data for Yemen for its EEZ in the Red Sea, while the unreported catch is the difference between our reconstructed catch and the FAO data. The reported catch and unreported landings each accounted for 44% of the total catch. Unreported landed catches existed throughout the whole period and had more stable values than the other components. The discarded catch appeared in the latter period when the industrial fishery was active (Figure 3). Both the unreported catch and discards are not recorded in the official statistics, the main difference is that the unreported catches are landed while discards are not. The artisanal fisheries use selective gear; hence, almost all the catch is retained. However, not all their catch is reported.

The number of taxa in the catch of the artisanal fishery is quite high. The dominant taxa are Indian mackerel (Rastrelliger kanagurta), narrow-barred Spanish mackerel (Scomberomorus commerson), emperors (Lethrinidae), and sharks (Carcharhinidae) (Figure 5). The taxa represented in Figure (5) are only the dominant ones; a detailed catch composition is given in Appendix Table (A4). Most of the dominant species are caught by gillnet, the major gear for artisanal fishers of Yemen in the Red Sea. The number of taxa increased in later years, because, based on interviews with fishers, the species that were very important in the earlier years started to decrease and fishing effort switched to previously non-targeted taxa.

Figure 4. Reconstructed catch in Yemeni Red Sea waters from 1950 to 2010 by components. Reported catch refers to the part of reconstructed catch accounted in the FAO data.

Figure 3. Reconstructed catch in Yemeni Red Sea waters from 1950 to 2010 by sectors compared to the total supplied to FAO.

114

The total catch of the minor artisanal fisheries for sea cucumber, cuttlefish and crabs is very low, compared to the major artisanal fishery or other sectors. Sea cucumbers were the largest component of the total catch, and hence, their catch time series shapes the pattern of the total catch of the minor artisanal fisheries (Figure 6, Table A5). The sea cucumber fishery started only in the 1970s. Before 1970, the catch of cuttlefish and crabs was very low, but then increased.

The subsistence beach seine fishery for small pelagic fish is not detailed in the fishery statistics of Yemen. Although, its economic value may not be as important compared to the other fisheries, the amounts caught are quite significant and their contribution to food security are very important, as beach seining is a fishery whose catch is fully consumed and distributed within all of Yemen. In the absence of other data, it is reasonable to assume that the total catch of this fishery changes with population size. Accordingly, the catch was low, around 1,200 t·year-1, until the 1980s and then started to increase continuously even after we have assumed the catch per capita in 2010 to be only half of that of 1975, which we believe is a very conservative estimate (Figure 7).

The other subsistence fishery catch (i.e., the fraction of the artisanal catch that is given away) has relatively less difference in its amount from 1950 to 2010 compared to the other fisheries, with the exception of a sharp increase in the 1990s (Figure 8), during which time the artisanal fishery – the main source of subsistence catch – achieved its peak. Even for the 1990s, however, the change is gentler for subsistence than artisanal fishery as can be seen by comparing Figures (5 and 8). This is a realistic representation for a subsistence fishery, as it is not thought to be strongly affected by market fluctuations. A more detailed catch composition of the subsistence fishery is given in Table (A6).

Industrial fisheries played an important role in the Red Sea part of Yemen only since the mid-1990s. Prior to this, in the 1970s, it was relatively small, and caught only shrimps. After the reunification in 1992, the industrial fishery became more important, targeting shrimp and a wide variety of finfish. Since the fishery uses non-selective trawling gear, a huge proportion of the catch is thrown overboard. The highest peak of the industrial fishery occurred in 2003, when a large number of foreign vessels were given permits to fish along Yemen’s Red Sea coast. However, the number of licences was reduced after 2003, because the government wanted to restrict this fishery (Akester 2007), hence the decline in total catch (Figure 9). According to our catch reconstruction, from 1950 to 2010, reported catch, unreported catch and discards accounted for 22%, 11% and 67% of the total catch, respectively.

Lizard fish and threadfin bream, with a combined 73%, are the dominant taxa that are retained by the industrial fishery. There are a number of other taxa that appear in the retained catch, but their contribution is limited (Figure 10 and Table A7). The main target of the industrial fishery was and still is shrimp, which accounts for less than 10% of the total hauled catch. Some of the taxa that are not the prime target are retained (Figure 10), but the majority, mainly demersal species, are discarded. The number of taxa in the discarded catch is quite large and they are usually discarded because they lack economic value (Figure 11 and Table A8 for more details). The dominant group in the discards is ponyfishes (Leiognathidae) with 61%.

Figure 7. Reconstructed catch of beach seine fishery of Yemen in the Red Sea from 1950 to 2010.

Figure 6. Reconstructed catch of the minor artisanal fisheries of Yemen in the Red Sea from 1950 to 2010.

Figure 5. Taxonomic composition of the reconstructed catch of the artisanal fishery of Yemen in the Red Sea from 1950 to 2010.

Yemen - Tesfamichael et al. 115

With regard to the taxonomic composition of the total catch in Yemeni Red Sea EEZ, Indian mackerel (Rastrelliger kanagurta) and kingfish (Scomberomorus commerson) are dominant at the species level (Figure 12), with 17% and 9%, respectively. They are so dominant that they are represented individually in Yemeni fisheries statistics, while other taxa are usually lumped together at family level. A total of 43 taxa make up 94% of the total catch in the Red Sea, while the rest are taxa with minor contributions. Only the major taxa are shown in Figure (12), the rest were added to the group ‘others’. Ponyfish (Leiognathidae), a discarded group in the bottom trawl fishery, started to increase since the early 1990s, when the industrial fishery increased its effort. A more detailed catch composition is given in Table (A9).

When the total catch is broken into ecological groups (Table 11), the pelagic (predominantly inshore taxa) group was dominant and more or less stable throughout the entire period (Figure 13). This is the group targeted by the gillnet fishery of the artisanal sector–which, unlike the industrial fishery is rather stable. The coral reef-associated species group increased its contribution to the total catch starting in the mid-1980s, but declined drastically at the end of the 1990s. The contribution of the demersal fish targeted by the industrial fishery was high starting in the early 1990s. Sharks and rays also contributed significantly to the total catches in the 1990s. The classification of the taxa into ecological groups is based on the dominant behavior they exhibit in relation to the fishery and gear used to catch them. Otherwise, some of them could inhabit different habitats. The group ‘others’ includes all the minor taxa and hence cannot be put to any ecological group. The coral reef-associated group, which shows the least fluctuation, has been fished for a long time and plays an important role in domestic food security (Figures 14 – 17).

disCussion

Lack of a structured data recording system is a serious hindrance for assessing the catch of Yemen in the Red Sea by different gears and taxonomic compositions. Although such data do not exist continuously for the whole period from 1950 to 2010, pieces of information exist from different periods reported by various authors and institutions in Yemen. In this report, the total catch in the Red Sea EEZ of Yemen is reconstructed from 1950 to 2010; the catch is divided into artisanal, subsistence and industrial sectors and, as well, into the taxa that compose the catch. Assumptions were made to fill in some of the data gaps. These assumptions are made based on the best knowledge available to us about the fisheries at the time of the research. The artisanal sector is more important in the Yemeni Red Sea than the industrial sector. The artisanal fishery is locally owned and operated while the industrial fishery is almost exclusively foreign and its operation is sporadic. The artisanal fishery is the main livelihood for many coastal communities, and hence also the source of subsistence catches.

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (1

0 t)3

0

10

20

30

40

Discards

Reported

Unreported

Figure 9. Components of the industrial fishery catch in Yemeni Red Sea from 1950 to 2010.

Figure 8. Taxonomic composition of the reconstructed subsistence catch (part of the artisanal fishery given away freely) of Yemen in the Red Sea from 1950 to 2010.

Figure 10. Taxonomic composition of the retained industrial fishery catch in Yemeni Red Sea from 1950 to 2010.

116Yemen’s artisanal fishery is one of the best established in the Red Sea. It has a large number of boats and fishers, a strong cooperative system, a relatively smoothly working financing system, and an effective marketing system that meets a high demand. Yemen has a long and strong fishing tradition and Yemeni’s fishers are found throughout the Red Sea and Indian Ocean, actively spreading their fishing skills to neighboring countries (Tesfamichael and Pitcher 2006). For example, Yemeni fisheries were active in the small pelagic fishing industry in Eritrea, where they fished in the EEZ of Eritrea and sold their catches to the fish meal processing plants within Eritrea in the 1950s and 1960s (Tesfamichael and Mohamud 2012).

The increase in total catch of the artisanal fishery in the mid-1970s, from its near constant value of around 10,000 t·year-1 to more than 20,000 t·year-1 in the 1980s is due to the strengthening of the sector by the formation of fishery cooperatives and the establishment of the Agricultural Credit Bank of Yemen. These two institutes allowed the availability of loans for the fishers to buy new boats and more importantly motorization of the boats. Although, the Agricultural Credit Bank was established in 1976 and opened the door for fishers requiring loans for motorization, it took several years for the fishers to adopt the new technology. The momentum increased and major motorization occurred at the end of the 1970s (Barraniya 1979), which further increased the number of artisanal fishers. The number of boats and fishers increased significantly at the end of the 1980s resulting in a rapid increase of total catch (Brodie et al. 1999). Although fishers reported a decline in their catch rates, the larger number of boats combined with bigger engines and availability of ice, which allowed the fishers to stay longer at sea and go to further fishing grounds, resulting in higher total catch.

Table 11. Ecological groups of the major taxa in the catch of Yemen in the Red Sea.Pelagic Coral reef-associated Demersal Sharks and raysAtule mate Lethrinidae Leiognathidae CarcharhinidaeCarangidae Lutjanidae Synodontidae DasyatidaeCarangoides malabaricus Nemipterus spp. Holothuroidea RhinobatidaeClupeidae Priacanthidae PenaeidaeRastrelliger kanagurta Rachycentron canadum SepiidaeScomberoides spp. Scaridae AriidaeScomberomorus commerson Serranidae MugilidaeScombridae Terapon spp. GerreidaeSphyraenidae Haemulidae TrichiuridaeTrachurus spp. Chrysoblephus spp. Epigonus spp.Euthynnus affinis Parastromateus nigerThunnus tonggol Platycephalidae

Portunus pelagicusSoleidaeTetraodontidaeBrachyuraMullidaeStomatopoda

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (1

0 t)3

0

30

60

90

Indian mackerel

Scomberomorus commerson

Leiognathidae

LethrinidaeCarcharhinidae

ClupeidaeSphyraenidaeHolothuroidea

Chrysobiephus spp.Scomberoides spp.

Lutjanidae

Others

Figure 11. Taxonomic composition of the discarded industrial fishery catch in Yemeni Red Sea from 1950 to 2010.

Figure 12. Reconstructed total catch by major taxa in the Red Sea EEZ of Yemen from 1950 to 2010.

Yemen - Tesfamichael et al. 117

As far as the industrial fishery is concerned, its contribution to the total catch was considerable during the years it was given permission to operate. The official reports of the industrial fishery do not account for the discards that can be up to 90% of the total catch. This omission can be misleading in any fishery management decision-making process. It is helpful to present the discards clearly so that by-catch mitigation strategies can be investigated. This can be either by spatial allocation of trawling, by designating mesh size or by-catch excluding devices. On the other hand, if the discard information is not presented at all, as is currently the case, there will not be any urgency to deal with the real problem that it represents.

Pelagic fish contributed the largest proportion throughout the whole period and did not exhibit any considerable decline, as compared to demersal and reef-associated fish. The high fluctuation of the trawl fishery is due to whether or not permits were given to the foreign vessels. An interesting case is the difference between the catch of pelagic and reef fish. They are both generated by artisanal fisheries; however, reef fishes exhibit a sharper increase and later decrease than pelagic fishes, which may be due to the migrations which pelagic fish undertake. The southern part of the Red Sea gets replenishment of migratory pelagic species from the more productive Gulf of Aden; hence, it can sustain a larger fishery. On the other hand, reef-associated fish are territorial and hence their biomass will be strongly affected by localized effort increases.

Overall, the reconstructed catch is higher than the catch that Yemen reported to the FAO. This is critical information for future plans in Yemen. Due attention to the reconstructed catch can prevent some serious mistakes in the assumption on the status of the resources (Tesfamichael 2012). The fact that the total catch is declining should alert the decision makers to initiate ways of managing effort before the resources get too depleted.

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (1

0 t)3

0

30

60

90

Pelagic

Coral reef associated

Demersal

Sharks and rays

Others

Figure 15. Taxonomic composition of coral reef-associated fishes caught in the Red Sea EEZ of Yemen from 1950 to 2010.

Figure 14. Taxonomic composition of pelagic fishes caught in the Red Sea EEZ of Yemen from 1950 to 2010.

Figure 13. Reconstructed catch by major ecological groups of the fisheries in the Red Sea EEZ of Yemen from 1950 to 2010.

Figure 16. Taxonomic composition of the demersal fishes caught in the Red Sea EEZ of Yemen from 1950 to 2010.

Figure 17. Taxonomic composition of the sharks and rays caught in the Red Sea EEZ of Yemen from 1950 to 2010.

118

aCknowledgements

We would like to thank the personnel of the Marine Research and Resource Center in Hodeidah, especially to Fahad Shooi Zabaan for his help with interviews and data acquisition, and Aref for helping in the arrangement of this work and for hospitality. We also thank the personnel of the Ministry of Fish Wealth, especially Khalid Hezaam Al Makrami. Margaret North’s inputs after proof reading the first draft are appreciated. This research was supported by Sea Around Us, a scientific collaboration between the University of British Columbia and The Pew Charitable Trusts.

referenCes

Agger P (1976) Yemen Arab Republic–Stock Assessment FI: DP YEM/74/003/3, FAO, Rome. 1-42 p.Akester S (2007) Yemen’s fisheries: the need for management. The British-Yemeni Society, Vol. 15.Atta-Mills J, Alder J and Sumaila UR (2004) The decline of a regional fishing nation: The case of Ghana and West

Africa. Natural Resources Forum 28(1): 13-21.Barraniya AA (1979) Socioeconomic aspects of the Red Sea fisheries in the Yemen Arab Republic. FAO/UNDP Proj. for

Development of Fisheries in Areas of the Red Sea and Gulf of Aden, Rome.Bonfiglioli A and Hariri KI (2004) Small-scale fisheies in Yemen: Social assessment and development prospects. FAO,

The World Bank. 11 p.Brodie J, M., Al-Sorimi and Turak E (1999) Fish and fisheries of Yemen’s Red Sea. In DouAbul A, Rouphael TS and

Marchant R (eds.), Ecosystems of the Red Sea coast of Yemen. Protection of Marine Ecosystems of the Red Sea Coast of Yemen. Hassell & Assoc., AMSAT and UNOPS.

Campleman G (1977) Fisheries and Marketing in YAR FAO, Rome.Chakraborty D (1984) Fishery Statistics in Yemen Arab Republic–An Expanded Plan of Development. FAO/UNDP,

SUEZ (EGYPT). 1-48 p.FAO (2002a) Fishery Country Profile–The Republic of Yemen. www.fao.org.FAO (2002b) Information on Fisheries Management in the Republic of Yemen, February 2002. www.fao.orgFAO (2005) The FAO Yearbook of Fishery Statistics–Capture production 2003. FAO Fishery Information, Data and

Statistics Unit, Rome.Herrera M and Lepere L (2005) Revised catch estimates for tuna and tuna-like species caught by artisinal boats in

Yemen Indian Ocean Tuna Commitee (IOTC) 15 p.Koehn D and Aklilu P (1999) Republic of Yemen–Fisheries Sector Strategy Note World Bank. 1-23 p.Lisac H (1971) Report to travel to Yemen Arabic and the People’s Republic of Southern Yemen, (16 January–1 February

1972) FAO Fish. Travel Aide Mem., FAO, Rome.Losse G (1973) Marine resources of the Yemen Arabic Republic. A report prepared for the the UNEP/FAO Food and

Nutrition programme 1973.MoFW (2004) Fisheries Statistics Book. Ministry of Fish Wealth, General Department for Planning and Statistic. 224

p.MoFW (2008) Catch Statistics Yemen 1990-2007. Ministry of Fish Wealth, General Department for Planning and

Statistic.MoFW (2012) Catch Statistics Yemen 2008-2010. Ministry of Fish Wealth, General Department for Planning and

Statistic.Morgan G (2006) Country Review: Yemen. p. 458 In De Young C (ed.), Review of the state of world marine capture

fisheries management: Indian Ocean. FAO Fisheries Technical Paper. No. 488. FAO, Rome.Pauly D (1998) Rationale for reconstructing catch time series. Bulletin. EC Fisheries Cooperation/Bulletin. CE

Cooperation Peche. Brussels 11(2): 4-10.PERSGA (2001) Strategic action programme for the Red Sea and Gulf of Aden. Regional Organization for the

Conservation of the Environment of the Red Sea and Gulf of Aden (PERSGA), Jeddah, Saudi Arabia. 149-180 p.Pitcher TJ, Watson R, Forrest R, Valtysson HP and Guenette S (2002) Estimating illegal and unreported catches from

marine ecosystems: a basis for change. Fish and Fisheries 3(4): 317-339.Pramod G, Pitcher TJ, Pearce J and Agnew D (2008) Sources of information supporting estimates of unreported fishery

catches (IUU) for 59 countries and the high seas fisheries. Fish. Cent. Res. Rep. Vol. 16, No. 14, Vancouver. 243 p.

Purcell SW, Gossuin H and Agudo NS (2009) Changes in weight and length of sea cucumbers during conversion to processed beche-de-mer: Filling gaps for some exploited tropical species. SPC Beche-de-mer Information Bulletin 29: 3–6.

Sanders MJ and Morgan GR (1989) Review of the fisheries resources of the Red Sea and Gulf of Aden. FAO, Rome. 138 p.

Tesfamichael D (2012) Assessment of the Red Sea ecosystem with emphasis on fisheries. PhD, University of British Columbia, Resource Management and Environmental Studies, Vancouver. 241 p.

Tesfamichael D and Mohamud S (2012) Reconstructing Red Sea fisheries of Eritrea: A case study of the relationship between political stability and fisheries development. In: Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Yemen - Tesfamichael et al. 119

Tesfamichael D and Pauly D (2011) Learning from the Past for Future Policy: Approaches to Time-series Catch Data Reconstruction. Western Indian Ocean J. Mar. Sci. 10(2): 99-106.

Tesfamichael D and Pitcher TJ (2006) Multidisciplinary evaluation of the sustainability of Red Sea fisheries using Rapfish. Fisheries Research 78(2-3): 227-235.

Tesfamichael D and Pitcher TJ (2007) Estimating the unreported catch of Eritrean Red Sea fisheries. African Journal of Marine Science 29(1): 55-63.

Tesfamichael D, Pitcher TJ and Pauly D (in press) Assessing changes in fisheries using fishers’ knowledge to generate long time series of catch rates: a case study from the Red Sea. Ecology and society.

Walczak P (1977) The Yemen Arab Republic. A study of the marine resources of the Yemen ArabRepublic. A report prepared for the Fisheries Development Project. FAO, Rome. 67 p.

Walczak P and Gudmundsson J (1975) Yemen Arab Republic–Summary of fish stock assessment work. FAO, Rome. 14 p.

Zeller D and Pauly D (2007) Reconstruction of marine fisheries catches for key countries and regions (1950-2005). Fisheries Centre Research Report. Volume 15 (2), Vancouver. 163 p.

120

appendix a

Appendix Table A1. Percentages and sources used to disaggregate the catch of artisanal fisheries by taxa.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1950-78 46 19 5 5 6 3 0 0 0 0 2 3 2 01979-82 24 14 10 6 6 5 5 0 2 4 2 0 3 1

1983 38 15 10 6 7 3 5 2 0 4 0 0 0 01984 23 17 10 4 2 6 3 0 0 4 2 0 4 11985 11 12 11 7 7 7 6 6 6 4 3 0 4 21986 22 12 11 5 5 5 4 5 6 1 3 0 4 21987 25 10 9 4 4 5 4 4 12 2 2 1 4 11988 23 9 9 5 3 4 4 6 11 2 3 1 4 11989 22 10 9 6 2 5 5 9 9 3 3 3 3 11990 22 10 9 7 2 6 5 6 7 4 4 5 2 11991 19 8 9 8 7 5 4 5 9 1 5 4 4 01992 3 7 9 8 14 6 5 8 8 3 3 4 4 01993 2 6 9 6 13 6 5 0 11 3 2 1 7 11994 2 6 9 6 13 5 5 0 9 5 5 2 5 11995 2 7 9 6 10 5 5 0 7 5 6 3 4 21996 2 7 9 7 11 5 5 0 7 5 6 3 4 21997 2 7 9 8 10 5 5 0 8 5 7 3 4 11998 9 7 9 7 10 6 5 6 0 4 5 3 0 11999 3 8 9 9 12 6 5 8 0 6 8 3 0 12000 12 14 6 7 7 4 13 6 0 5 1 6 0 72001 14 14 10 8 5 6 10 8 0 2 1 4 0 62002 24 13 8 8 1 5 9 8 0 1 1 3 0 62003 34 11 9 8 3 8 5 6 0 1 2 4 0 52004 22 13 9 8 3 8 6 6 0 1 2 2 1 42005 20 16 9 8 5 8 8 4 0 1 2 3 0 52006 22 12 10 7 5 8 8 4 0 1 2 2 2 62007 21 14 9 7 5 8 8 4 0 1 2 3 1 52008 29 3 6 5 6 8 6 1 0 9 1 5 3 32009 25 0 5 16 6 2 2 1 0 5 0 5 3 52010 30 3 8 12 5 2 3 1 0 5 0 3 3 2

1: Rastrelliger kanagurta; 2: Scomberomorus commerson; 3: Lethrinidae; 4: Carangidae; 5: Carcharhinidae; 6: Sphyraenidae; 7: Serranidae; 8: Nemipterus spp.; 9: Chrysoblephus spp.; 10: Scombridae; 11: Scomberoides spp.; 12: Euthynnus affinis; 13: Lutjanidae; 14: Penaeidae

Yemen - Tesfamichael et al. 121

Table A1 continuedYear 15 16 17 18 19 20 21 22 23 24 25 26 Source/remark

1950-78 1 0 0 0 2 0 0 3 0 0 2 2 Walczak (1977) 1979-82 2 0 3 0 0 1 0 0 0 0 0 12 Average of 1983-1986

1983 0 0 1 0 0 0 0 0 0 0 0 9 Sanders and Morgan (1989)1984 1 0 5 0 0 3 0 0 0 0 0 16 Sanders and Morgan (1989)1985 5 1 2 0 0 2 0 0 0 0 0 4 Sanders and Morgan (1989)1986 3 1 6 2 0 2 0 0 0 0 0 2 Sanders and Morgan (1989)1987 2 0 0 2 0 0 0 0 0 0 0 11 Brodie (1999)1988 1 0 0 2 0 0 0 0 0 0 0 11 Brodie (1999)1989 1 0 0 1 0 0 0 0 0 0 0 6 Brodie (1999)1990 1 0 0 1 0 0 0 0 0 0 0 7 Brodie (1999)1991 1 1 0 1 0 0 0 0 0 0 0 8 Brodie (1999)1992 2 1 0 3 0 0 0 0 0 0 0 11 Brodie (1999)1993 2 1 0 3 0 0 0 0 0 0 0 22 Brodie (1999)1994 3 2 0 2 0 0 0 0 0 0 0 20 Brodie (1999)1995 2 4 0 4 0 0 0 0 0 0 0 18 Brodie (1999)1996 3 4 0 0 0 0 0 0 0 0 0 19 Brodie (1999)1997 3 4 0 0 0 0 0 0 0 0 0 19 Brodie (1999)1998 3 7 3 2 0 0 0 0 0 0 0 12 MoFW (2004, 2008)1999 3 5 2 1 0 0 0 0 0 0 0 12 MoFW (2004, 2008)2000 1 0 1 1 0 0 0 0 0 0 0 8 MoFW (2004, 2008)2001 4 0 2 1 0 0 0 0 0 0 0 4 MoFW (2004, 2008)2002 0 1 2 1 0 0 0 0 0 0 0 9 MoFW (2004, 2008)2003 0 0 1 0 0 0 0 0 0 0 0 2 MoFW (2004, 2008)2004 0 1 1 1 0 0 4 0 0 0 0 8 MoFW (2004, 2008)2005 1 1 2 0 0 0 0 0 0 0 0 9 MoFW (2004, 2008)2006 1 1 1 1 0 0 0 0 0 0 0 8 MoFW (2004, 2008)2007 1 1 1 0 0 0 0 0 0 0 0 8 MoFW (2004, 2008)2008 0 2 1 1 2 0 1 0 1 0 0 6 MoFW (2012)2009 1 1 1 0 3 0 0 0 1 0 0 17 MoFW (2012)2010 0 5 1 0 2 0 0 0 1 0 0 13 MoFW (2012)

15: Rachycentridae; 16: Haemulidae; 17: Mugilidae; 18: Ariidae; 19: Thunnus tonggol; 20: Priacanthidae; 21: Synodontidae; 22: Dasyatidae; 23: Atule mate; 24: Scaridae; 25: Rhinobatidae; 26: Others

122Appendix Table A2. Reconstructed catch (in tonnes) in Yemeni Red Sea waters from 1950 to 2010 by sectors compared to the total supplied to FAO.Year FAO landings Reconstructed total catch Industrial Artisanal Subsistence Discards1950 4,111 11,500 0 8,140 3,320 01951 4,135 11,600 0 8,260 3,370 01952 4,934 11,800 0 8,410 3,430 01953 4,953 12,100 0 8,570 3,500 01954 4,990 12,300 0 8,750 3,570 01955 5,900 11,900 0 8,470 3,460 01956 4,065 12,200 0 8,690 3,550 01957 4,019 12,500 0 8,910 3,640 01958 3,964 12,900 0 9,130 3,730 01959 4,299 13,200 0 9,350 3,820 01960 4,055 13,500 0 9,590 3,910 01961 4,020 13,800 0 9,830 4,010 01962 4,061 14,200 0 10,080 4,120 01963 4,101 14,600 0 10,330 4,220 01964 4,556 14,900 0 10,580 4,320 01965 4,055 15,200 0 10,810 4,410 01966 5,210 15,500 0 11,020 4,500 01967 4,783 15,800 0 11,230 4,580 01968 4,921 16,100 0 11,420 4,660 01969 6,291 16,400 0 11,620 4,740 01970 5,730 20,500 965 11,820 4,830 2,8941971 6,253 20,400 912 11,860 4,850 2,7361972 6,608 19,700 657 12,110 4,940 1,9711973 7,149 19,500 326 13,010 5,220 9781974 8,467 21,400 224 14,720 5,760 6731975 10,100 22,800 137 17,360 4,870 4121976 10,939 24,400 150 18,720 5,100 4491977 11,887 27,100 208 20,790 5,460 6251978 13,633 28,600 330 21,760 5,570 9901979 17,622 28,000 0 22,380 5,630 01980 15,830 27,500 0 21,990 5,540 01981 16,725 31,500 0 25,290 6,220 01982 17,991 34,200 0 27,660 6,560 01983 17,024 27,800 0 22,330 5,520 01984 21,105 27,100 0 21,730 5,340 01985 17,539 29,700 0 24,000 5,650 01986 17,125 32,500 0 26,500 6,030 01987 26,669 33,900 0 27,700 6,160 01988 28,803 37,000 0 30,530 6,510 01989 27,756 42,400 0 35,240 7,190 01990 29,657 42,900 0 35,690 7,170 01991 40,482 59,000 0 49,690 9,330 01992 41,241 63,500 0 53,700 9,840 01993 48,027 79,400 1,221 64,450 11,270 2,4421994 48,325 81,400 2,442 63,170 10,910 4,8841995 52,063 78,500 3,663 57,450 10,070 7,3261996 38,659 66,000 4,884 43,370 7,950 9,7671997 43,128 88,000 6,105 59,680 10,050 12,2091998 41,620 89,500 7,326 57,870 9,650 14,6511999 37,946 89,900 8,918 54,170 9,000 17,8352000 23,462 69,800 10,510 32,220 6,020 21,0192001 22,433 69,700 12,102 27,620 5,780 24,2032002 32,767 78,400 13,694 31,160 6,160 27,3882003 32,286 80,400 14,352 31,620 5,720 28,7042004 41,324 76,300 11,770 35,310 5,700 23,5402005 41,007 64,900 9,188 31,620 5,750 18,3762006 44,334 58,900 6,606 33,210 5,850 13,2132007 36,785 48,900 3,269 33,190 5,880 6,5382008 34,510 49,800 4,770 29,850 5,590 9,5392009 40,983 46,700 4,564 27,760 5,280 9,1282010 44,992 44,400 5,486 23,140 4,760 10,971

Yemen - Tesfamichael et al. 123Appendix Table A3. Reconstructed catch (in tonnes) in Yemeni Red Sea waters from 1950 to 2010 by components. Reported catch refers to the part of reconstructed catch accounted in the FAO data.

Year Reported Unreported Discards1950 3,530 7,930 01951 3,560 8,070 01952 4,100 7,740 01953 4,120 7,950 01954 4,160 8,150 01955 4,690 7,240 01956 3,390 8,850 01957 3,460 9,080 01958 3,420 9,430 01959 3,630 9,550 01960 3,520 9,980 01961 3,490 10,350 01962 3,540 10,660 01963 3,580 10,970 01964 4,030 10,870 01965 3,810 11,420 01966 4,890 10,630 01967 4,250 11,560 01968 4,390 11,700 01969 5,700 10,660 01970 5,070 12,540 2,8941971 5,570 12,050 2,7361972 5,790 11,920 1,9711973 6,300 12,260 9781974 7,160 13,540 6731975 8,570 13,800 4121976 9,260 14,700 4491977 10,110 16,350 6251978 11,430 16,220 9901979 13,310 14,710 01980 12,010 15,520 01981 13,440 18,070 01982 14,370 19,850 01983 13,250 14,600 01984 17,580 9,480 01985 15,590 14,060 01986 15,560 16,970 01987 21,870 12,000 01988 24,330 12,710 01989 23,650 18,780 01990 26,820 16,040 01991 37,050 21,960 01992 36,830 26,710 01993 42,020 34,930 2,4421994 42,680 33,840 4,8841995 43,450 27,730 7,3261996 34,570 21,640 9,7671997 40,880 34,940 12,2091998 38,380 36,470 14,6511999 35,490 36,590 17,8352000 20,840 27,910 21,0192001 19,510 25,990 24,2032002 25,870 25,150 27,3882003 22,660 29,030 28,7042004 27,070 25,710 23,5402005 25,830 20,730 18,3762006 26,700 18,950 13,2132007 25,400 16,950 6,5382008 27,210 13,010 9,5392009 27,820 9,780 9,1282010 25,720 7,670 10,971

124

Appendix Table A4. Taxonomic composition of the reconstructed catch (in tonnes) of the artisanal fishery of Yemen in the Red Sea from 1950 to 2010.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 141950 3,700 1,530 362 483 242 288 0 0 158 0 0 242 121 1181951 3,760 1,550 368 490 245 292 0 0 160 0 0 245 123 1201952 3,830 1,580 374 499 250 297 0 0 163 0 0 250 125 1221953 3,900 1,610 382 509 254 303 0 0 166 0 0 254 127 1241954 3,980 1,640 389 519 260 309 0 0 170 0 0 260 130 1271955 3,860 1,590 377 503 252 300 0 0 164 0 0 252 126 1231956 3,960 1,630 387 516 258 307 0 0 169 0 0 258 129 1261957 4,050 1,670 397 529 264 315 0 0 173 0 0 264 132 1291958 4,150 1,720 406 542 271 323 0 0 177 0 0 271 135 1321959 4,260 1,760 416 555 278 331 0 0 181 0 0 278 139 1361960 4,360 1,800 427 569 285 339 0 0 186 0 0 285 142 1391961 4,470 1,850 438 584 292 348 0 0 191 0 0 292 146 1431962 4,590 1,900 449 599 299 357 0 0 196 0 0 299 150 1461963 4,700 1,940 460 614 307 365 0 0 200 0 0 307 153 1501964 4,820 1,990 471 628 314 374 0 0 205 0 0 314 157 1541965 4,920 2,030 481 642 321 382 0 0 210 0 0 321 160 1571966 5,020 2,070 491 655 327 390 0 0 214 0 0 327 164 1601967 5,110 2,110 500 667 333 397 0 0 218 0 0 333 167 1631968 5,200 2,150 509 678 339 404 0 0 222 0 0 339 170 1661969 5,290 2,180 517 690 345 411 0 0 225 0 0 345 172 1691970 5,380 2,220 527 702 351 418 0 0 229 0 0 351 176 1721971 5,380 2,220 527 702 351 418 0 0 229 0 0 351 176 1721972 5,480 2,260 536 714 357 425 0 0 233 0 0 357 179 1751973 5,870 2,420 574 766 383 456 0 0 250 0 0 383 191 1871974 6,640 2,740 650 866 433 516 0 0 283 0 0 433 217 2121975 7,830 3,240 766 1,022 511 608 0 0 334 0 0 511 255 2501976 8,390 3,470 821 1,095 547 652 0 0 358 0 0 547 274 2681977 9,280 3,830 908 1,211 605 721 0 0 396 0 0 605 303 2961978 9,660 3,990 945 1,260 630 750 0 0 412 0 0 630 315 3081979 5,220 3,150 2,260 1,227 1,174 864 1,045 491 383 855 0 0 603 3551980 5,090 3,070 2,204 1,196 1,145 842 1,019 478 374 834 0 0 588 3461981 5,850 3,530 2,534 1,376 1,317 969 1,172 550 430 959 0 0 676 3981982 6,390 3,860 2,768 1,503 1,438 1,058 1,280 601 470 1,048 0 0 739 4341983 7,930 3,070 2,092 1,497 571 902 1,046 0 0 796 380 0 0 3701984 4,940 3,650 2,056 525 1,375 558 645 0 397 795 0 0 795 2291985 2,470 2,590 2,495 1,548 1,525 1,064 1,363 1,415 733 924 1,286 0 993 4371986 5,420 2,940 2,699 1,133 1,157 854 892 1,470 724 338 1,336 0 964 3511987 6,430 2,470 2,397 1,008 1,294 700 1,008 3,099 452 393 937 350 974 2871988 6,540 2,530 2,658 759 1,224 1,031 1,140 3,235 942 466 1,869 307 1,120 4231989 7,290 3,140 3,039 776 1,660 1,424 1,515 3,070 1,117 966 3,118 1,031 1,013 5851990 7,180 3,430 3,067 690 1,937 1,685 1,741 2,464 1,168 1,411 2,092 1,727 752 6921991 8,730 3,840 4,347 3,282 2,236 2,762 1,658 4,049 2,444 642 2,377 1,932 1,717 1,1341992 1,340 3,490 4,738 7,286 3,219 2,853 2,474 3,943 1,698 1,617 4,310 1,950 2,187 1,1711993 1,260 4,280 6,556 8,994 4,528 2,857 3,452 7,563 1,499 2,378 0 699 4,921 1,1731994 1,460 4,370 6,219 8,688 3,627 2,803 3,223 5,877 3,155 3,086 0 1,566 3,542 1,1511995 1,270 4,030 5,521 5,901 3,110 2,487 2,996 4,223 3,610 2,921 0 1,620 2,640 1,0211996 950 2,950 4,098 4,732 2,396 2,349 2,326 3,231 2,804 2,208 0 1,188 1,922 9641997 1,550 4,200 5,759 6,267 3,134 3,346 3,163 4,705 4,221 3,155 0 2,100 2,609 1,3741998 5,190 4,020 5,212 5,322 3,266 2,703 2,985 0 2,721 2,178 3,511 1,634 0 1,1101999 1,520 4,060 4,549 6,321 3,043 3,225 2,528 0 4,051 3,043 4,061 1,763 0 1,3242000 3,400 4,000 1,610 2,075 1,216 1,379 3,649 0 265 1,513 1,647 1,747 0 5662001 3,720 3,640 2,627 1,327 1,657 1,454 2,678 0 359 606 2,185 1,091 0 5972002 7,420 4,080 2,359 414 1,570 1,633 2,620 0 387 372 2,426 790 144 6702003 9,290 3,140 2,355 762 2,200 1,586 1,283 0 546 255 1,644 992 5 6512004 6,240 3,600 2,427 869 2,305 1,497 1,593 0 452 261 1,740 443 234 6152005 5,800 4,530 2,589 1,309 2,345 1,612 2,183 0 442 234 1,083 1,008 3 6622006 6,570 3,700 2,898 1,434 2,363 1,459 2,378 0 684 421 1,255 674 527 5992007 6,520 4,410 2,894 1,449 2,496 1,637 2,409 0 584 338 1,231 910 254 6722008 8,430 890 1,823 1,876 2,339 1,009 1,868 0 167 2,565 228 1,468 1,028 4142009 7,260 20 1,403 1,680 449 3,210 494 0 110 1,500 344 1,452 946 1,3182010 6,760 580 1,793 1,076 550 1,927 747 0 86 1,148 270 685 742 7911: Rastrelliger kanagurta; 2: Scomberomorus commerson; 3: Lethrinidae; 4: Carcharhinidae; 5: Sphyraenidae; 6: Trachurus spp.; 7: Serranidae; 8: Chrysoblephus spp.; 9: Scomberoides spp.; 10: Scombridae; 11: Nemipterus spp.; 12: Euthynnus affinis; 13: Lutjanidae; 14: Carangidae

Yemen - Tesfamichael et al. 125

Table A4 continuedYear 15 16 17 18 19 20 21 22 23 24 25 26 27 281950 0 81 0 0 0 242 161 161 0 0 0 0 0 1611951 0 82 0 0 0 245 163 163 0 0 0 0 0 1631952 0 83 0 0 0 250 166 166 0 0 0 0 0 1661953 0 85 0 0 0 254 170 170 0 0 0 0 0 1701954 0 87 0 0 0 260 173 173 0 0 0 0 0 1731955 0 84 0 0 0 252 168 168 0 0 0 0 0 1681956 0 86 0 0 0 258 172 172 0 0 0 0 0 1721957 0 88 0 0 0 264 176 176 0 0 0 0 0 1761958 0 90 0 0 0 271 181 181 0 0 0 0 0 1811959 0 93 0 0 0 278 185 185 0 0 0 0 0 1851960 0 95 0 0 0 285 190 190 0 0 0 0 0 1901961 0 97 0 0 0 292 195 195 0 0 0 0 0 1951962 0 100 0 0 0 299 200 200 0 0 0 0 0 2001963 0 102 0 0 0 307 205 205 0 0 0 0 0 2051964 0 105 0 0 0 314 209 209 0 0 0 0 0 2091965 0 107 0 0 0 321 214 214 0 0 0 0 0 2141966 0 109 0 0 0 327 218 218 0 0 0 0 0 2181967 0 111 0 0 0 333 222 222 0 0 0 0 0 2221968 0 113 0 0 0 339 226 226 0 0 0 0 0 2261969 0 115 0 0 0 345 230 230 0 0 0 0 0 2301970 0 117 0 0 0 351 234 234 0 0 0 0 0 2341971 0 117 0 0 0 351 234 234 0 0 0 0 0 2341972 0 119 0 0 0 357 238 238 0 0 0 0 0 2381973 0 128 0 0 0 383 255 255 0 0 0 0 0 2551974 0 144 0 0 0 433 289 289 0 0 0 0 0 2891975 0 170 0 0 0 511 341 341 0 0 0 0 0 3411976 0 182 0 0 0 547 365 365 0 0 0 0 0 3651977 0 202 0 0 0 605 404 404 0 0 0 0 0 4041978 0 210 0 0 0 630 420 420 0 0 0 0 0 4201979 220 455 64 52 599 0 0 0 0 322 0 0 0 2,1481980 214 443 62 51 584 0 0 0 0 314 0 0 0 2,0951981 246 510 72 58 672 0 0 0 0 361 0 0 0 2,4091982 269 557 78 64 734 0 0 0 0 394 0 0 0 2,6311983 19 47 0 87 212 0 0 0 0 0 0 0 0 1,8131984 280 215 0 0 1,074 0 0 0 0 546 0 0 0 2,0091985 352 1,063 185 63 508 0 0 0 0 416 0 0 0 7931986 475 627 168 603 1,470 0 0 0 0 482 0 0 0 4711987 237 451 19 555 0 0 0 0 0 0 0 0 0 2,5631988 303 411 74 458 0 0 0 0 0 0 0 0 0 2,8311989 256 424 83 373 0 0 0 0 0 0 0 0 0 1,9951990 166 380 82 224 0 0 0 0 0 0 0 0 0 2,2911991 217 659 379 635 0 0 0 0 0 0 0 0 0 3,9881992 104 1,096 681 1,645 0 0 0 0 0 0 0 0 0 5,0891993 490 1,711 1,038 1,951 0 0 0 0 0 0 0 0 0 6,1501994 678 1,682 1,534 1,396 0 0 0 0 0 0 0 0 0 6,0061995 1,296 1,488 2,392 2,233 0 0 0 0 0 0 0 0 0 5,4171996 881 1,213 1,747 0 0 0 0 0 0 0 0 0 0 3,9951997 713 1,571 2,628 0 0 0 0 0 0 0 0 0 0 5,6111998 734 1,634 3,812 1,073 1,634 0 0 0 0 0 0 0 0 5,4161999 694 1,521 2,544 257 771 0 0 0 0 0 0 0 0 5,0312000 2,078 181 51 364 268 0 0 0 0 0 0 0 0 2,2022001 1,667 1,109 17 286 656 0 0 0 376 0 0 0 28 6712002 1,788 75 178 224 504 0 0 0 433 0 1 0 79 2,2252003 1,465 101 58 136 251 0 0 0 457 0 0 0 22 1902004 1,192 81 195 367 324 12 0 0 496 0 1,118 0 35 1,8202005 1,423 199 226 110 452 80 0 0 465 0 132 0 92 2,0732006 1,762 336 347 178 221 83 0 0 577 0 113 0 69 1,8462007 1,672 277 298 149 369 86 0 0 596 0 131 0 86 2,0412008 843 105 695 379 312 20 700 0 331 0 204 325 133 1,3192009 1,395 431 309 16 241 23 834 0 504 0 135 333 100 2,7232010 516 33 1,177 0 149 18 458 0 597 0 106 261 63 2,257

15: Penaeidae; 16: Rachycentridae; 17: Haemulidae; 18: Ariidae; 19: Mugilidae; 20: Dasyatidae; 21: Thunnus tonggol; 22: Rhinobatidae; 23: Epigonus spp.; 24: Priacanthidae; 25: Synodontidae; 26: Atule mate; 27: Scaridae; 28: Others

126Appendix Table A5. Reconstructed catch (in tonnes) of the minor artisanal fisheries of Yemen in the Red Sea from 1950 to 2010.Year Holothuroidea Sepiidae Brachyura1950 0 65 211951 0 66 211952 0 67 211953 0 68 221954 0 70 221955 0 67 221956 0 69 221957 0 71 231958 0 73 231959 0 74 241960 0 76 241961 0 78 251962 0 80 261963 0 82 261964 0 84 271965 0 86 271966 0 88 281967 0 89 291968 0 91 291969 0 93 301970 0 94 301971 38 96 311972 76 98 311973 115 100 321974 153 102 331975 191 105 331976 330 107 341977 469 110 351978 608 113 361979 747 117 371980 886 123 391981 1,025 138 441982 1,163 141 451983 1,302 144 461984 1,441 147 471985 1,580 150 481986 1,719 156 501987 1,858 161 511988 1,997 163 521989 2,136 168 541990 2,275 174 561991 2,414 188 601992 2,553 197 631993 2,692 202 641994 2,831 208 661995 2,970 229 731996 3,109 237 761997 3,248 241 771998 3,387 249 801999 3,526 256 822000 3,664 263 842001 506 271 872002 401 279 892003 3,206 914 1072004 6,232 1,070 922005 1,269 1,227 772006 1,269 1,383 622007 1,269 390 292008 102 239 422009 144 231 1542010 44 202 101

Yemen - Tesfamichael et al. 127

Appendix Table A6. Taxonomic composition of the reconstructed subsistence catch (in tonnes), part of the artisanal fishery given away freely, of Yemen in the Red Sea from 1950 to 2010.

Year 1 2 3 4 5 6 7 8 9 10 11 12 13 141950 906 1,111 459 109 145 72 86 0 0 47 72 36 0 01951 920 1,128 466 110 147 74 88 0 0 48 74 37 0 01952 936 1,148 474 112 150 75 89 0 0 49 75 37 0 01953 955 1,170 483 114 153 76 91 0 0 50 76 38 0 01954 974 1,194 493 117 156 78 93 0 0 51 78 39 0 01955 944 1,157 478 113 151 75 90 0 0 49 75 38 0 01956 968 1,187 490 116 155 77 92 0 0 51 77 39 0 01957 992 1,216 502 119 159 79 94 0 0 52 79 40 0 01958 1,016 1,246 515 122 163 81 97 0 0 53 81 41 0 01959 1,042 1,277 528 125 167 83 99 0 0 54 83 42 0 01960 1,068 1,309 541 128 171 85 102 0 0 56 85 43 0 01961 1,095 1,342 554 131 175 88 104 0 0 57 88 44 0 01962 1,123 1,377 569 135 180 90 107 0 0 59 90 45 0 01963 1,151 1,411 583 138 184 92 110 0 0 60 92 46 0 01964 1,178 1,445 597 141 188 94 112 0 0 62 94 47 0 01965 1,204 1,476 610 144 193 96 115 0 0 63 96 48 0 01966 1,228 1,505 622 147 196 98 117 0 0 64 98 49 0 01967 1,250 1,533 633 150 200 100 119 0 0 65 100 50 0 01968 1,272 1,560 644 153 203 102 121 0 0 66 102 51 0 01969 1,294 1,587 655 155 207 103 123 0 0 68 103 52 0 01970 1,317 1,615 667 158 211 105 125 0 0 69 105 53 0 01971 1,341 1,615 667 158 211 105 125 0 0 69 105 53 0 01972 1,367 1,643 679 161 214 107 128 0 0 70 107 54 0 01973 1,394 1,761 727 172 230 115 137 0 0 75 115 57 0 01974 1,430 1,992 823 195 260 130 155 0 0 85 130 65 0 01975 1,464 1,567 647 153 204 102 122 0 0 67 102 51 0 01976 1,500 1,654 683 162 216 108 129 0 0 70 108 54 0 01977 1,536 1,804 745 176 235 118 140 0 0 77 118 59 0 01978 1,551 1,849 764 181 241 121 144 0 0 79 121 60 0 01979 1,583 983 594 426 231 221 163 197 93 72 0 114 161 01980 1,647 944 570 409 222 213 156 189 89 69 0 109 155 01981 1,813 1,069 646 463 252 241 177 214 101 79 0 124 175 01982 1,823 1,150 694 498 270 259 190 230 108 85 0 133 189 01983 1,832 1,405 543 371 265 101 160 185 0 0 0 0 141 671984 1,839 861 636 358 92 240 97 112 0 69 0 139 139 01985 1,846 424 443 428 265 261 182 234 243 126 0 170 158 2201986 1,885 914 496 455 191 195 144 150 248 122 0 162 57 2251987 1,914 1,066 410 397 167 214 116 167 514 75 58 161 65 1551988 1,897 1,064 412 433 124 199 168 186 527 153 50 182 76 3041989 1,927 1,167 503 486 124 266 228 242 491 179 165 162 154 4991990 1,958 1,129 539 482 108 304 265 274 387 184 271 118 222 3291991 2,073 1,346 593 671 506 345 426 256 625 377 298 265 99 3671992 2,130 202 529 717 1,103 487 432 375 597 257 295 331 245 6531993 2,137 187 636 974 1,336 673 424 513 1,124 223 104 731 353 01994 2,163 213 636 906 1,266 529 408 470 856 460 228 516 450 01995 2,332 181 576 789 843 444 355 428 603 516 231 377 417 01996 2,359 133 412 574 663 336 329 326 452 393 166 269 309 01997 2,352 213 576 790 860 430 459 434 645 579 288 358 433 01998 2,376 697 540 700 715 439 363 401 0 365 219 0 292 4711999 2,386 200 534 598 831 400 424 332 0 532 232 0 400 5342000 2,393 437 514 207 267 156 177 469 0 34 225 0 195 2122001 2,415 468 457 330 167 208 183 337 0 45 137 0 76 2752002 2,424 912 501 290 51 193 201 322 0 48 97 18 46 2982003 2,428 1,115 377 283 91 264 190 154 0 66 119 1 31 1972004 2,430 731 422 284 102 270 175 187 0 53 52 27 31 2042005 2,428 663 517 296 150 268 184 250 0 50 115 0 27 1242006 2,448 732 413 323 160 263 163 265 0 76 75 59 47 1402007 2,463 708 479 314 157 271 178 262 0 63 99 28 37 1342008 2,473 891 94 193 198 247 107 198 0 18 155 109 271 242009 2,479 747 2 144 173 46 330 51 0 11 149 97 154 352010 2,480 676 58 179 108 55 193 75 0 9 69 74 115 27

1: Clupeidae; 2: Rastrelliger kanagurta; 3: Scomberomorus commerson; 4: Lethrinidae; 5: Carcharhinidae; 6: Sphyraenidae; 7: Trachurus spp.; 8: Serranidae; 9: Chrysoblephus spp.; 10: Scomberoides spp.; 11: Euthynnus affinis; 12: Lutjanidae; 13: Scombridae; 14: Nemipterus spp.

128

Table A6 continuedYear 15 16 17 18 19 20 21 22 23 24 25 26 27 28 291950 35 24 0 0 72 0 48 48 0 0 0 0 0 0 481951 36 25 0 0 74 0 49 49 0 0 0 0 0 0 491952 37 25 0 0 75 0 50 50 0 0 0 0 0 0 501953 37 25 0 0 76 0 51 51 0 0 0 0 0 0 511954 38 26 0 0 78 0 52 52 0 0 0 0 0 0 521955 37 25 0 0 75 0 50 50 0 0 0 0 0 0 501956 38 26 0 0 77 0 52 52 0 0 0 0 0 0 521957 39 26 0 0 79 0 53 53 0 0 0 0 0 0 531958 40 27 0 0 81 0 54 54 0 0 0 0 0 0 541959 41 28 0 0 83 0 56 56 0 0 0 0 0 0 561960 42 28 0 0 85 0 57 57 0 0 0 0 0 0 571961 43 29 0 0 88 0 58 58 0 0 0 0 0 0 581962 44 30 0 0 90 0 60 60 0 0 0 0 0 0 601963 45 31 0 0 92 0 61 61 0 0 0 0 0 0 611964 46 31 0 0 94 0 63 63 0 0 0 0 0 0 631965 47 32 0 0 96 0 64 64 0 0 0 0 0 0 641966 48 33 0 0 98 0 65 65 0 0 0 0 0 0 651967 49 33 0 0 100 0 67 67 0 0 0 0 0 0 671968 50 34 0 0 102 0 68 68 0 0 0 0 0 0 681969 51 34 0 0 103 0 69 69 0 0 0 0 0 0 691970 51 35 0 0 105 0 70 70 0 0 0 0 0 0 701971 51 35 0 0 105 0 70 70 0 0 0 0 0 0 701972 52 36 0 0 107 0 71 71 0 0 0 0 0 0 711973 56 38 0 0 115 0 77 77 0 0 0 0 0 0 771974 64 43 0 0 130 0 87 87 0 0 0 0 0 0 871975 50 34 0 0 102 0 68 68 0 0 0 0 0 0 681976 53 36 0 0 108 0 72 72 0 0 0 0 0 0 721977 58 39 0 0 118 0 78 78 0 0 0 0 0 0 781978 59 40 0 0 121 0 80 80 0 0 0 0 0 0 801979 67 86 41 12 0 10 0 0 113 0 61 0 0 0 4051980 64 82 40 12 0 9 0 0 109 0 58 0 0 0 3891981 73 93 45 13 0 11 0 0 123 0 66 0 0 0 4401982 78 100 48 14 0 11 0 0 132 0 71 0 0 0 4741983 66 8 3 0 0 15 0 0 38 0 0 0 0 0 3211984 40 37 49 0 0 0 0 0 187 0 95 0 0 0 3501985 75 182 60 32 0 11 0 0 87 0 71 0 0 0 1361986 59 106 80 28 0 102 0 0 248 0 81 0 0 0 791987 48 75 39 3 0 92 0 0 0 0 0 0 0 0 4251988 69 67 49 12 0 75 0 0 0 0 0 0 0 0 4611989 94 68 41 13 0 60 0 0 0 0 0 0 0 0 3191990 109 60 26 13 0 35 0 0 0 0 0 0 0 0 3601991 175 102 33 59 0 98 0 0 0 0 0 0 0 0 6151992 177 166 16 103 0 249 0 0 0 0 0 0 0 0 7711993 174 254 73 154 0 290 0 0 0 0 0 0 0 0 9141994 168 245 99 224 0 203 0 0 0 0 0 0 0 0 8751995 146 213 185 342 0 319 0 0 0 0 0 0 0 0 7741996 135 170 123 245 0 0 0 0 0 0 0 0 0 0 5591997 188 215 98 360 0 0 0 0 0 0 0 0 0 0 7701998 149 219 99 512 0 144 0 0 219 0 0 0 0 0 7271999 174 200 91 334 0 34 0 0 101 0 0 0 0 0 6612000 73 23 267 7 0 47 0 0 34 0 0 0 0 0 2832001 75 139 210 2 0 36 0 0 82 47 0 0 0 3 842002 82 9 220 22 0 27 0 0 62 53 0 0 0 10 2732003 78 12 176 7 0 16 0 0 30 55 0 0 0 3 232004 72 9 140 23 1 43 0 0 38 58 0 131 0 4 2132005 76 23 163 26 9 13 0 0 52 53 0 15 0 10 2372006 67 37 196 39 9 20 0 0 25 64 0 13 0 8 2062007 73 30 181 32 9 16 0 0 40 65 0 14 0 9 2222008 44 11 89 73 2 40 74 0 33 35 0 22 34 14 1392009 136 44 143 32 2 2 86 0 25 52 0 14 34 10 2802010 79 3 52 118 2 0 46 0 15 60 0 11 26 6 226

15: Carangidae; 16: Rachycentridae; 17: Penaeidae; 18: Haemulidae; 19: Dasyatidae; 20: Ariidae; 21: Thunnus tonggol; 22: Rhinobatidae; 23: Mugilidae; 24: Epigonus spp.; 25: Priacanthidae; 26: Synodontidae; 27: Atule mate; 28: Scaridae; 29: Others

Yemen - Tesfamichael et al. 129

Appendix Table A7. Taxonomic composition of the retained industrial fishery catch (in tonnes) in Yemeni Red Sea from 1950 to 2010.Year Synodontidae Nemipterus spp. Sepiidae Penaeidae Lethrinidae Lutjanidae Brachyura1950 0 0 0 0 0 0 01951 0 0 0 0 0 0 01952 0 0 0 0 0 0 01953 0 0 0 0 0 0 01954 0 0 0 0 0 0 01955 0 0 0 0 0 0 01956 0 0 0 0 0 0 01957 0 0 0 0 0 0 01958 0 0 0 0 0 0 01959 0 0 0 0 0 0 01960 0 0 0 0 0 0 01961 0 0 0 0 0 0 01962 0 0 0 0 0 0 01963 0 0 0 0 0 0 01964 0 0 0 0 0 0 01965 0 0 0 0 0 0 01966 0 0 0 0 0 0 01967 0 0 0 0 0 0 01968 0 0 0 0 0 0 01969 0 0 0 0 0 0 01970 0 0 0 965 0 0 01971 0 0 0 912 0 0 01972 0 0 0 657 0 0 01973 0 0 0 326 0 0 01974 0 0 0 224 0 0 01975 0 0 0 137 0 0 01976 0 0 0 150 0 0 01977 0 0 0 208 0 0 01978 0 0 0 330 0 0 01979 0 0 0 0 0 0 01980 0 0 0 0 0 0 01981 0 0 0 0 0 0 01982 0 0 0 0 0 0 01983 0 0 0 0 0 0 01984 0 0 0 0 0 0 01985 0 0 0 0 0 0 01986 0 0 0 0 0 0 01987 0 0 0 0 0 0 01988 0 0 0 0 0 0 01989 0 0 0 0 0 0 01990 0 0 0 0 0 0 01991 0 0 0 0 0 0 01992 0 0 0 0 0 0 01993 610 336 60 85 76 46 81994 1,220 671 120 171 153 92 161995 1,831 1,007 179 256 229 137 231996 2,441 1,342 239 342 305 183 311997 3,051 1,678 299 427 381 229 391998 3,661 2,014 359 513 458 275 471999 4,457 2,451 437 624 557 334 572000 5,253 2,889 515 736 657 394 672001 6,048 3,327 593 847 756 454 772002 7,426 4,084 285 341 928 557 722003 6,591 3,625 1,089 1,622 824 494 1072004 5,110 2,810 2,455 367 639 383 62005 3,989 2,194 1,916 287 499 299 52006 2,561 1,409 1,941 179 320 192 52007 1,726 949 119 130 216 129 02008 2,282 1,255 496 261 285 171 192009 2,184 1,201 475 250 273 164 182010 2,625 1,444 570 300 328 197 22

130 Appendix Table A8. Taxonomic composition of the discarded industrial fishery catch (in tonnes) in Yemeni Red Sea from 1950 to 2010. Year 1 2 3 4 5 6 7 8 9 101950 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 01967 0 0 0 0 0 0 0 0 0 01968 0 0 0 0 0 0 0 0 0 01969 0 0 0 0 0 0 0 0 0 01970 897 101 58 58 29 29 29 29 29 141971 848 96 55 55 27 27 27 27 27 141972 611 69 39 39 20 20 20 20 20 101973 303 34 20 20 10 10 10 10 10 51974 209 24 13 13 7 7 7 7 7 31975 128 14 8 8 4 4 4 4 4 21976 139 16 9 9 4 4 4 4 4 21977 194 22 13 13 6 6 6 6 6 31978 307 35 20 20 10 10 10 10 10 51979 0 0 0 0 0 0 0 0 0 01980 0 0 0 0 0 0 0 0 0 01981 0 0 0 0 0 0 0 0 0 01982 0 0 0 0 0 0 0 0 0 01983 0 0 0 0 0 0 0 0 0 01984 0 0 0 0 0 0 0 0 0 01985 0 0 0 0 0 0 0 0 0 01986 0 0 0 0 0 0 0 0 0 01987 0 0 0 0 0 0 0 0 0 01988 0 0 0 0 0 0 0 0 0 01989 0 0 0 0 0 0 0 0 0 01990 0 0 0 0 0 0 0 0 0 01991 0 0 0 0 0 0 0 0 0 01992 0 0 0 0 0 0 0 0 0 01993 1,514 171 98 98 49 49 49 49 49 241994 3,028 342 195 195 98 98 98 98 98 491995 4,542 513 293 293 147 147 147 147 147 731996 6,056 684 391 391 195 195 195 195 195 981997 7,570 855 488 488 244 244 244 244 244 1221998 9,084 1,026 586 586 293 293 293 293 293 1471999 11,058 1,248 713 713 357 357 357 357 357 1782000 13,032 1,471 841 841 420 420 420 420 420 2102001 15,006 1,694 968 968 484 484 484 484 484 2422002 16,980 1,917 1,096 1,096 548 548 548 548 548 2742003 17,796 2,009 1,148 1,148 574 574 574 574 574 2872004 14,595 1,648 942 942 471 471 471 471 471 2352005 11,393 1,286 735 735 368 368 368 368 368 1842006 8,192 925 529 529 264 264 264 264 264 1322007 4,054 458 262 262 131 131 131 131 131 652008 5,914 668 382 382 191 191 191 191 191 952009 5,660 639 365 365 183 183 183 183 183 912010 6,802 768 439 439 219 219 219 219 219 110

1: Leiognathidae; 2: Terapon spp.; 3: Gerreidae; 4: Trichiuridae; 5: Parastromateus niger; 6: Platycephalidae; 7: Portunus pelagicus; 8: Soleidae; 9: Tetraodontidae; 10: Clupeidae

Yemen - Tesfamichael et al. 131

Table A8 continuedYear 11 12 13 14 15 16 17 18 19 20 211950 0 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 0 01967 0 0 0 0 0 0 0 0 0 0 01968 0 0 0 0 0 0 0 0 0 0 01969 0 0 0 0 0 0 0 0 0 0 01970 14 14 434 405 347 130 58 29 29 14 1451971 14 14 410 383 328 123 55 27 27 14 1371972 10 10 296 276 237 89 39 20 20 10 991973 5 5 147 137 117 44 20 10 10 5 491974 3 3 101 94 81 30 13 7 7 3 341975 2 2 62 58 49 19 8 4 4 2 211976 2 2 67 63 54 20 9 4 4 2 221977 3 3 94 88 75 28 13 6 6 3 311978 5 5 149 139 119 45 20 10 10 5 501979 0 0 0 0 0 0 0 0 0 0 01980 0 0 0 0 0 0 0 0 0 0 01981 0 0 0 0 0 0 0 0 0 0 01982 0 0 0 0 0 0 0 0 0 0 01983 0 0 0 0 0 0 0 0 0 0 01984 0 0 0 0 0 0 0 0 0 0 01985 0 0 0 0 0 0 0 0 0 0 01986 0 0 0 0 0 0 0 0 0 0 01987 0 0 0 0 0 0 0 0 0 0 01988 0 0 0 0 0 0 0 0 0 0 01989 0 0 0 0 0 0 0 0 0 0 01990 0 0 0 0 0 0 0 0 0 0 01991 0 0 0 0 0 0 0 0 0 0 01992 0 0 0 0 0 0 0 0 0 0 01993 24 24 0 0 0 0 0 0 0 0 2441994 49 49 0 0 0 0 0 0 0 0 4881995 73 73 0 0 0 0 0 0 0 0 7331996 98 98 0 0 0 0 0 0 0 0 9771997 122 122 0 0 0 0 0 0 0 0 1,2211998 147 147 0 0 0 0 0 0 0 0 1,4651999 178 178 0 0 0 0 0 0 0 0 1,7842000 210 210 0 0 0 0 0 0 0 0 2,1022001 242 242 0 0 0 0 0 0 0 0 2,4202002 274 274 0 0 0 0 0 0 0 0 2,7392003 287 287 0 0 0 0 0 0 0 0 2,8702004 235 235 0 0 0 0 0 0 0 0 2,3542005 184 184 0 0 0 0 0 0 0 0 1,8382006 132 132 0 0 0 0 0 0 0 0 1,3212007 65 65 0 0 0 0 0 0 0 0 6542008 95 95 0 0 0 0 0 0 0 0 9542009 91 91 0 0 0 0 0 0 0 0 9132010 110 110 0 0 0 0 0 0 0 0 1,097

11: Mullidae; 12: Stomatopoda; 13: Carangoides malabaricus; 14: Synodontidae; 15: Nemipterus spp.; 16: Haemulidae; 17: Ariidae; 18: Carangidae; 19: Sphyraenidae; 20: Sepiidae; 21: Others

132Appendix Table A9. Reconstructed total catch (in tonnes) by major taxa in the Red Sea EEZ of Yemen from 1950 to 2010.

Year 1 2 3 4 5 6 7 8 9 10 11 12 13 141950 4,815 1,989 0 471 628 906 314 0 374 0 0 0 0 2051951 4,887 2,019 0 478 637 920 319 0 380 0 0 0 0 2081952 4,975 2,055 0 487 649 936 324 0 386 0 0 0 0 2121953 5,071 2,095 0 496 661 955 331 0 394 0 0 0 0 2161954 5,175 2,137 0 506 675 974 337 0 402 0 0 0 0 2201955 5,014 2,071 0 491 654 944 327 0 389 0 0 0 0 2141956 5,143 2,124 0 503 671 968 335 0 399 0 0 0 0 2191957 5,271 2,177 0 516 688 992 344 0 409 0 0 0 0 2251958 5,400 2,231 0 528 704 1,016 352 0 419 0 0 0 0 2301959 5,534 2,286 0 541 722 1,042 361 0 430 0 0 0 0 2361960 5,672 2,343 0 555 740 1,068 370 0 441 0 0 0 0 2421961 5,816 2,402 0 569 759 1,095 379 0 452 0 0 0 0 2481962 5,967 2,465 0 584 778 1,123 389 0 463 0 0 0 0 2541963 6,115 2,526 0 598 798 1,151 399 0 475 0 0 0 0 2611964 6,260 2,586 0 612 817 1,178 408 0 486 0 0 0 0 2671965 6,398 2,642 0 626 834 1,204 417 0 497 0 0 0 0 2731966 6,524 2,695 0 638 851 1,228 425 0 507 0 0 0 0 2781967 6,643 2,744 0 650 866 1,250 433 0 516 0 0 0 0 2831968 6,759 2,792 0 661 882 1,272 441 0 525 0 0 0 0 2881969 6,875 2,840 0 673 897 1,294 448 0 534 0 0 0 0 2931970 6,997 2,890 897 684 913 1,331 485 347 543 0 405 0 0 2981971 6,997 2,890 848 684 913 1,355 484 328 543 0 383 38 0 2981972 7,120 2,941 611 697 929 1,377 484 237 553 0 276 76 0 3031973 7,632 3,152 303 747 996 1,398 508 117 593 0 137 115 0 3251974 8,632 3,565 209 844 1,126 1,433 570 81 671 0 94 153 0 3681975 9,400 3,883 128 920 1,226 1,466 617 49 730 0 58 191 0 4011976 10,047 4,150 139 983 1,310 1,502 660 54 780 0 63 330 0 4281977 11,087 4,579 194 1,085 1,446 1,539 729 75 861 0 88 469 0 4721978 11,509 4,754 307 1,126 1,501 1,556 761 119 894 0 139 608 0 4901979 6,199 3,743 0 2,686 1,458 1,583 1,396 0 1,027 1,242 0 747 583 4561980 6,030 3,640 0 2,613 1,418 1,647 1,358 0 999 1,208 0 886 567 4431981 6,917 4,176 0 2,997 1,627 1,813 1,557 0 1,146 1,386 0 1,025 651 5091982 7,538 4,551 0 3,266 1,773 1,823 1,697 0 1,248 1,511 0 1,163 709 5541983 9,337 3,610 0 2,463 1,762 1,832 672 447 1,062 1,231 0 1,302 0 01984 5,801 4,288 0 2,415 617 1,839 1,615 0 656 757 0 1,441 0 4671985 2,894 3,029 0 2,922 1,813 1,846 1,786 1,506 1,247 1,597 0 1,580 1,657 8581986 6,336 3,436 0 3,154 1,324 1,885 1,352 1,561 998 1,042 0 1,719 1,717 8461987 7,497 2,883 0 2,794 1,175 1,914 1,508 1,092 816 1,175 0 1,858 3,613 5271988 7,600 2,939 0 3,091 883 1,897 1,423 2,173 1,198 1,326 0 1,997 3,761 1,0951989 8,462 3,647 0 3,526 900 1,927 1,925 3,617 1,652 1,757 0 2,136 3,561 1,2961990 8,310 3,968 0 3,549 798 1,958 2,242 2,421 1,950 2,015 0 2,275 2,851 1,3511991 10,073 4,435 0 5,017 3,789 2,073 2,581 2,744 3,189 1,914 0 2,414 4,674 2,8211992 1,539 4,023 0 5,455 8,389 2,130 3,706 4,963 3,286 2,849 0 2,553 4,540 1,9551993 1,442 4,916 1,514 7,607 10,331 2,162 5,201 336 3,282 3,965 610 2,692 8,686 1,7221994 1,678 5,004 3,028 7,277 9,953 2,211 4,156 671 3,211 3,693 1,220 2,831 6,733 3,6141995 1,449 4,606 4,542 6,539 6,744 2,405 3,554 1,007 2,842 3,424 1,831 2,970 4,826 4,1251996 1,085 3,358 6,056 4,977 5,395 2,457 2,732 1,342 2,678 2,651 2,441 3,109 3,684 3,1971997 1,767 4,777 7,570 6,930 7,127 2,474 3,564 1,678 3,805 3,597 3,051 3,248 5,350 4,8001998 5,884 4,565 9,084 6,369 6,036 2,523 3,705 5,996 3,067 3,386 3,661 3,387 0 3,0861999 1,721 4,594 11,058 5,703 7,152 2,565 3,443 7,046 3,649 2,860 4,457 3,526 0 4,5832000 3,838 4,509 13,032 2,474 2,341 2,603 1,373 4,747 1,556 4,118 5,253 3,664 0 2992001 4,191 4,094 15,006 3,714 1,494 2,658 1,866 5,786 1,637 3,015 6,048 506 0 4042002 8,337 4,576 16,980 3,577 465 2,697 1,763 6,808 1,834 2,942 7,427 401 0 4352003 10,409 3,519 17,796 3,462 853 2,715 2,464 5,466 1,777 1,437 6,591 3,206 0 6112004 6,967 4,022 14,595 3,350 970 2,665 2,575 4,754 1,673 1,780 6,358 6,232 0 5052005 6,462 5,045 11,393 3,383 1,459 2,612 2,613 3,400 1,796 2,433 4,136 1,269 0 4922006 7,299 4,115 8,192 3,541 1,594 2,580 2,626 2,803 1,621 2,643 2,687 1,269 0 7602007 7,226 4,887 4,054 3,424 1,606 2,528 2,767 2,314 1,815 2,671 1,872 1,269 0 6482008 9,324 981 5,914 2,300 2,074 2,568 2,586 1,507 1,116 2,066 2,507 102 0 1852009 8,007 18 5,660 1,821 1,853 2,570 495 1,581 3,540 545 2,332 144 0 1222010 7,438 640 6,802 2,301 1,184 2,590 605 1,740 2,120 821 2,741 44 0 95

1: Rastrelliger kanagurta; 2: Scomberomorus commerson; 3: Leiognathidae; 4: Lethrinidae; 5: Carcharhinidae; 6: Clupeidae; 7: Sphyraenidae; 8: Nemipterus spp.; 9: Trachurus spp.; 10: Serranidae; 11: Synodontidae; 12: Holothuroidea; 13: Chrysoblephus spp.; 14: Scomberoides spp.

Yemen - Tesfamichael et al. 133Table A9 continuedYear 15 16 17 18 19 20 21 22 23 24 25 26 27 28 291950 157 0 314 0 154 105 65 0 0 0 0 314 0 0 2091951 159 0 319 0 156 106 66 0 0 0 0 319 0 0 2121952 162 0 324 0 159 108 67 0 0 0 0 324 0 0 2161953 165 0 331 0 162 110 68 0 0 0 0 331 0 0 2201954 169 0 337 0 165 112 70 0 0 0 0 337 0 0 2251955 164 0 327 0 160 109 67 0 0 0 0 327 0 0 2181956 168 0 335 0 164 112 69 0 0 0 0 335 0 0 2241957 172 0 344 0 168 115 71 0 0 0 0 344 0 0 2291958 176 0 352 0 172 117 73 0 0 0 0 352 0 0 2351959 180 0 361 0 176 120 74 0 0 0 0 361 0 0 2411960 185 0 370 0 181 123 76 0 0 0 0 370 0 0 2471961 190 0 379 0 185 126 78 0 0 0 0 379 0 0 2531962 195 0 389 0 190 130 80 0 0 0 0 389 0 0 2591963 199 0 399 0 195 133 82 0 0 0 0 399 0 0 2661964 204 0 408 0 200 136 84 0 0 0 0 408 0 0 2721965 209 0 417 0 204 139 86 0 0 0 0 417 0 0 2781966 213 0 425 0 208 142 88 0 0 0 0 425 0 0 2841967 217 0 433 0 212 144 89 0 0 0 0 433 0 0 2891968 220 0 441 0 216 147 91 0 0 0 0 441 0 0 2941969 224 0 448 0 219 149 93 0 0 0 0 448 0 0 2991970 228 0 456 965 252 152 109 130 101 58 0 456 58 58 3041971 228 0 456 912 250 152 110 123 96 55 0 456 55 55 3041972 232 0 464 657 247 155 108 89 69 39 0 464 39 39 3101973 249 0 498 326 253 166 105 44 34 20 0 498 20 20 3321974 281 0 563 224 282 188 106 30 24 13 0 563 13 13 3751975 307 0 613 137 304 204 107 19 14 8 0 613 8 8 4091976 328 0 655 150 325 218 110 20 16 9 0 655 9 9 4371977 362 0 723 208 360 241 113 28 22 13 0 723 13 13 4821978 375 0 751 330 377 250 118 45 35 20 0 751 20 20 5001979 717 1,017 0 261 422 540 117 76 0 62 712 0 0 0 01980 697 989 0 254 410 526 123 74 0 60 693 0 0 0 01981 800 1,134 0 291 470 603 138 85 0 69 795 0 0 0 01982 872 1,236 0 318 513 657 141 93 0 75 866 0 0 0 01983 0 937 0 22 436 56 144 0 0 102 250 0 0 0 01984 933 933 0 329 269 252 147 0 0 0 1,261 0 0 0 01985 1,164 1,082 0 412 512 1,245 150 216 0 73 595 0 0 0 01986 1,126 395 0 555 410 733 156 197 0 704 1,717 0 0 0 01987 1,136 458 409 276 335 526 161 22 0 647 0 0 0 0 01988 1,302 542 357 352 492 478 163 86 0 533 0 0 0 0 01989 1,175 1,120 1,196 296 678 491 168 97 0 433 0 0 0 0 01990 870 1,633 1,998 193 800 440 174 95 0 259 0 0 0 0 01991 1,982 741 2,230 250 1,309 760 188 438 0 733 0 0 0 0 01992 2,518 1,862 2,245 119 1,349 1,262 197 784 0 1,895 0 0 0 0 01993 5,698 2,731 803 648 1,347 1,965 262 1,193 171 2,241 0 0 98 98 01994 4,149 3,536 1,794 948 1,318 1,927 328 1,757 342 1,599 0 0 195 195 01995 3,155 3,338 1,852 1,738 1,167 1,700 409 2,734 513 2,552 0 0 293 293 01996 2,375 2,517 1,354 1,346 1,099 1,383 476 1,991 684 0 0 0 391 391 01997 3,196 3,588 2,388 1,238 1,562 1,786 540 2,988 855 0 0 0 488 488 01998 275 2,470 1,854 1,345 1,259 1,854 608 4,324 1,026 1,217 1,854 0 586 586 01999 334 3,443 1,995 1,409 1,498 1,721 693 2,878 1,248 291 873 0 713 713 02000 394 1,708 1,972 3,081 639 204 777 58 1,471 411 302 0 841 841 02001 454 683 1,228 2,724 672 1,248 864 19 1,694 322 738 0 968 968 02002 719 418 887 2,349 753 84 564 200 1,917 251 566 0 1,096 1,096 02003 500 285 1,111 3,263 729 113 2,003 64 2,009 153 281 0 1,148 1,148 02004 645 291 495 1,698 687 90 3,525 218 1,648 410 362 13 942 942 02005 303 261 1,123 1,873 737 222 3,143 252 1,286 122 503 90 735 735 02006 777 468 750 2,137 666 373 3,324 386 925 198 246 92 529 529 02007 411 375 1,009 1,983 745 307 509 330 458 165 409 96 262 262 02008 1,307 2,836 1,623 1,193 458 117 735 768 668 419 345 23 382 382 7742009 1,207 1,654 1,602 1,788 1,453 475 705 341 639 17 266 25 365 365 9202010 1,013 1,262 754 868 870 36 773 1,295 768 0 164 20 439 439 504

15: Lutjanidae; 16: Scombridae; 17: Euthynnus affinis; 18: Penaeidae; 19: Carangidae; 20: Rachycentridae; 21: Sepiidae; 22: Haemulidae; 23: Terapon spp.; 24: Ariidae; 25: Mugilidae; 26: Dasyatidae; 27: Gerreidae; 28: Trichiuridae; 29: Thunnus tonggol

134Table A9 continuedYear 30 31 32 33 34 35 36 37 38 39 40 41 42 43 441950 209 0 0 0 0 0 0 21 0 0 0 0 0 0 2091951 212 0 0 0 0 0 0 21 0 0 0 0 0 0 2121952 216 0 0 0 0 0 0 21 0 0 0 0 0 0 2161953 220 0 0 0 0 0 0 22 0 0 0 0 0 0 2201954 225 0 0 0 0 0 0 22 0 0 0 0 0 0 2251955 218 0 0 0 0 0 0 22 0 0 0 0 0 0 2181956 224 0 0 0 0 0 0 22 0 0 0 0 0 0 2241957 229 0 0 0 0 0 0 23 0 0 0 0 0 0 2291958 235 0 0 0 0 0 0 23 0 0 0 0 0 0 2351959 241 0 0 0 0 0 0 24 0 0 0 0 0 0 2411960 247 0 0 0 0 0 0 24 0 0 0 0 0 0 2471961 253 0 0 0 0 0 0 25 0 0 0 0 0 0 2531962 259 0 0 0 0 0 0 26 0 0 0 0 0 0 2591963 266 0 0 0 0 0 0 26 0 0 0 0 0 0 2661964 272 0 0 0 0 0 0 27 0 0 0 0 0 0 2721965 278 0 0 0 0 0 0 27 0 0 0 0 0 0 2781966 284 0 0 0 0 0 0 28 0 0 0 0 0 0 2841967 289 0 0 0 0 0 0 29 0 0 0 0 0 0 2891968 294 0 0 0 0 0 0 29 0 0 0 0 0 0 2941969 299 0 0 0 0 0 0 30 0 0 0 0 0 0 2991970 304 0 29 29 29 29 29 30 0 14 14 434 0 0 4491971 304 0 27 27 27 27 27 31 0 14 14 410 0 0 4411972 310 0 20 20 20 20 20 31 0 10 10 296 0 0 4081973 332 0 10 10 10 10 10 32 0 5 5 147 0 0 3811974 375 0 7 7 7 7 7 33 0 3 3 101 0 0 4091975 409 0 4 4 4 4 4 33 0 2 2 62 0 0 4291976 437 0 4 4 4 4 4 34 0 2 2 67 0 0 4591977 482 0 6 6 6 6 6 35 0 3 3 94 0 0 5131978 500 0 10 10 10 10 10 36 0 5 5 149 0 0 5501979 0 0 0 0 0 0 0 37 383 0 0 0 0 0 2,5531980 0 0 0 0 0 0 0 39 372 0 0 0 0 0 2,4841981 0 0 0 0 0 0 0 44 427 0 0 0 0 0 2,8491982 0 0 0 0 0 0 0 45 465 0 0 0 0 0 3,1051983 0 0 0 0 0 0 0 46 0 0 0 0 0 0 2,1351984 0 0 0 0 0 0 0 47 641 0 0 0 0 0 2,3591985 0 0 0 0 0 0 0 48 487 0 0 0 0 0 9291986 0 0 0 0 0 0 0 50 563 0 0 0 0 0 5511987 0 0 0 0 0 0 0 51 0 0 0 0 0 0 2,9881988 0 0 0 0 0 0 0 52 0 0 0 0 0 0 3,2921989 0 0 0 0 0 0 0 54 0 0 0 0 0 0 2,3141990 0 0 0 0 0 0 0 56 0 0 0 0 0 0 2,6511991 0 0 0 0 0 0 0 60 0 0 0 0 0 0 4,6031992 0 0 0 0 0 0 0 63 0 0 0 0 0 0 5,8601993 0 0 49 49 49 49 49 72 0 24 24 0 0 0 7,3071994 0 0 98 98 98 98 98 82 0 49 49 0 0 0 7,3701995 0 0 147 147 147 147 147 96 0 73 73 0 0 0 6,9241996 0 0 195 195 195 195 195 107 0 98 98 0 0 0 5,5311997 0 0 244 244 244 244 244 116 0 122 122 0 0 0 7,6021998 0 0 293 293 293 293 293 126 0 147 147 0 0 0 7,6081999 0 0 357 357 357 357 357 138 0 178 178 0 0 0 7,4752000 0 0 420 420 420 420 420 151 0 210 210 0 0 0 4,5872001 0 423 484 484 484 484 484 164 0 242 242 0 0 31 3,1762002 0 486 548 548 548 548 548 161 0 274 274 0 0 89 5,2372003 0 511 574 574 574 574 574 214 0 287 287 0 0 25 3,0842004 0 555 471 471 471 471 471 98 0 235 235 0 0 39 4,3872005 0 518 368 368 368 368 368 82 0 184 184 0 0 102 4,1472006 0 641 264 264 264 264 264 67 0 132 132 0 0 77 3,3732007 0 660 131 131 131 131 131 29 0 65 65 0 0 96 2,9172008 0 366 191 191 191 191 191 61 0 95 95 0 360 148 2,4122009 0 556 183 183 183 183 183 172 0 91 91 0 367 111 3,9162010 0 657 219 219 219 219 219 123 0 110 110 0 287 69 3,58030: Rhinobatidae; 31: Epigonus spp.; 32: Parastromateus niger; 33: Platycephalidae; 34: Portunus pelagicus; 35: Soleidae; 36: Tetraodontidae; 37: Brachyura; 38: Priacanthidae; 39: Mullidae; 40: Stomatopoda; 41: Carangoides malabaricus; 42: Atule mate; 43: Scaridae; 44: Others

Yemen - Tesfamichael et al. 135appendix b: reConstruCtion of yemen’s CatChes in the gulf of aden,

1950–20101

Dawit Tesfamichael1,2, Peter Rossing1, Hesham Saeed3

1 Sea Around Us, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, BC., V6T 1Z4, Canada

2 Department of Marine Sciences, University of Asmara, Eritrea.3 Marine Research and Resource Center, Hodeidah, Yemen

d.tesfamichael @fisheries.ubc.ca; p.rossing @fisheries.ubc.ca; alsaeed_co @yahoo.com

introduCtion

In addition to the Red Sea, Yemen has access to the Gulf of Aden and Arabian Sea, which is characterized by high productivity due to the upwelling caused by southwestern monsoons. The southern coast of Yemen used to be under the People’s Democratic Republic of Yemen (commonly known as South Yemen) until the unification of Yemen in 1990. The most productive part of that coast is east of Al Mukalla and the main port is Aden (Sanders and Morgan 1989) (Figure B1).

Most of the fishing is performed by artisanal fishers who are organized in cooperatives, from which fishery statistical data are collected; however, a lot of the fish, especially sardines are sold outside the cooperatives system, making it harder to keep records. The artisanal fishery targets mainly pelagic fishes (Bonfiglioli and Hariri 2004), using cast nets for small pelagic species and seines for larger pelagic species. The main small pelagic species caught is Indian oil sardine (Sardinella longiceps), caught in the near shore east of Al Mukhalla by cast net. It is mainly processed for fish meal. The industrial fishery in the Gulf of Aden has been operated mainly by foreign fleets, although Yemen is also developing its own industrial fishery. The target is mainly cuttlefish (Sepiidae), taken by trawlers up to 120 m deep, but mainly less than 50 m (Sanders and Morgan 1989).

CatCh reConstruCtion method

Total catch

In order to reconstruct the catches of the Gulf of Aden of Yemen, first the total catch of Yemen in the Gulf of Aden is calculated from the FAO data. The annual catch data for Yemen in the FAO database are for the whole country, i.e., both the Red Sea and the Gulf of Aden. The procedure of dividing the FAO data into the Red Sea and the Gulf of Aden is described in the main text (see Table 1 and Figure 2). Once the Gulf of Aden catch was calculated, it was further divided into artisanal and industrial fisheries using ratios available for some years and interpolating for the years it was missing (Table B1). From 1950 to 1966, all the catch was artisanal. The earliest indication of industrial catch was for 1967 (Edwards et al. 1985) for which a ratio of 0.025 of the total catch was assumed to be the share of the industrial fishery. From 1985 to 1994, catches of major groups were available (PERSGA 2001). The groups were divided into artisanal and industrial based on the ecology of the taxa. Pelagic fishes are caught by artisanal vessels and demersal taxa by industrial (Sanders and Morgan 1989; MoFW 2004). Taxa caught by both sectors were divided using the average of 2002 and 2003, which was already split by sector (MoFW 2004). Data by sector were also available for 1998 (FAO 2002) and 2006–2008 (MoFW 2008, 2012). For the years with missing data, they were interpolated, except for 2009 and 2010, for which the 2008 value was used.1 Cite as: Tesfamichael, D., Rossing, P. and Saeed, H. (2012) Reconstruction of Yemen’s catches in the Gulf of Aden, 1950-2010. pp. 135-152. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosysytem by countries (1950-2010). Fisheries Centre Research Reports 20(1). Fisheries Centre, University of British Columbia [ISSN 1198-6727].

Figure B1: The Gulf of Aden and Arabian Sea coast of Yemen with its shelf area and Exclusive Economic Zone (EEZ).

136

For each sector, the reconstructed catch was calculated using the ratio of reconstructed catch to FAO data for the Red Sea. For the artisanal fishery, the reconstructed total catch was 1.54 times the FAO data, and 1.31 times for the industrial fishery. Since the operation of the fisheries and their data recording systems are under the same administrative jurisdiction (MoFW 2004; Morgan 2006), this assumption is reasonable. In order to calculate the ratios for the Red Sea, the FAO Red Sea data were first divided into artisanal and industrial sectors using the ratios between the two sectors in the reconstructed catch; the totals of the sectors were then used to obtain the multiplication factor to calculate the Gulf of Aden catch based on the FAO data.

Table B1: Ratios and sources used for dividing the Gulf of Aden catch into artisanal and industrial fishery sector. Year Artisanal Industrial Source/Remark1950-66 1.00 0.00 Edward et al. (1986)1967 0.98 0.03 Edward et al. (1986), Start of industrial fishery and

assumed to be only 2.5% of total catch1968 0.95 0.05 Interpolation 1969 0.92 0.08 Interpolation 1970 0.89 0.11 Interpolation 1971 0.87 0.13 Interpolation 1972 0.84 0.16 Interpolation 1973 0.81 0.19 Interpolation 1974 0.79 0.21 Interpolation 1975 0.76 0.24 Interpolation 1976 0.73 0.27 Interpolation 1977 0.70 0.30 Interpolation 1978 0.68 0.32 Interpolation 1979 0.65 0.35 Interpolation 1980 0.62 0.38 Interpolation 1981 0.60 0.40 Interpolation 1982 0.57 0.43 Interpolation 1983 0.54 0.46 Interpolation 1984 0.51 0.49 Interpolation 1985 0.49 0.51 PERSGA (2001) Used ecology of taxa for categorization1986 0.43 0.57 PERSGA (2001) Used ecology of taxa for categorization1987 0.50 0.50 PERSGA (2001) Used ecology of taxa for categorization1988 0.57 0.43 PERSGA (2001) Used ecology of taxa for categorization1989 0.59 0.41 PERSGA (2001) Used ecology of taxa for categorization1990 0.87 0.13 PERSGA (2001) Used ecology of taxa for categorization1991 0.85 0.15 PERSGA (2001) Used ecology of taxa for categorization1992 0.95 0.05 PERSGA (2001) Used ecology of taxa for categorization1993 0.90 0.10 PERSGA (2001) Used ecology of taxa for categorization1994 0.96 0.04 PERSGA (2001) Used ecology of taxa for categorization1995 0.93 0.07 Interpolation 1996 0.89 0.11 Interpolation 1997 0.86 0.14 Interpolation 1998 0.82 0.18 FAO (2002)1999 0.84 0.16 Interpolation 2000 0.85 0.15 Interpolation 2001 0.87 0.13 Interpolation 2002 0.89 0.11 MoFW (2004)2003 0.95 0.05 MoFW (2004)2004 0.96 0.04 Interpolation 2005 0.98 0.02 Interpolation 2006 0.99 0.01 MoFW (2012)2007 0.98 0.02 MoFW (2012)2008 1.00 0.00 MoFW (2012)2009 1.00 0.00 2008 value2010 1.00 0.00 2008 value

Yemen - Tesfamichael et al. 137

Catch composition

Artisanal fishery

The earliest catch composition data available for Yemeni catch in the Gulf of Aden were for 1985 – 1994 (PERSGA 2001) where the catches of major groups were given separately, i.e., not a catch composition matrix. Thus here, the catches were first allocated to either artisanal or industrial sector; the pelagic and demersal taxa were assigned to the artisanal and industrial sectors, respectively. The artisanal fishers of Yemen in the Gulf of Aden have traditionally targeted pelagic fishes, while the industrial fishery, mainly trawlers, target demersal fishes (Sanders and Morgan 1989; MoFW 2004). Total catches of cuttlefish and spiny (rock) lobster, which are caught by both sectors, were assigned to these two sectors using the average of ratios from 2002 and 2003, when they were reported by sector (MoFW 2004). The same procedure was followed to the catch composition data for 2006 and 2007 (MoFW 2012). From 1995 to 2001, 2004, and 2005, the catches of the pelagic species were interpolated.

For 2002, 2003, 2006 and 2007, taxa with minor catch (e.g., sea cucumber) were put under ‘others’. The pelagic group of the artisanal catch, which has the biggest share (up to 99% for some years) was divided further to its components using detailed data from 1986 to 1989 (Saeed 1995). Detailed composition data were also available for 2006 and 2007 (MoFW 2012); however, there were some missing taxa, which were calculated as the average value of 1986–1989 and the ratios deducted from the group ‘others’ (Table B2) . For the years composition of pelagic fishes was not given, 1990–2005, it was interpolated, and for 1985 the averages of 1986–1989 were used.

Once the pelagic fishes were broken down to their components, the overall composition of artisanal fishery was calculated together with the invertebrate (cuttlefish, rock lobster and octopus) catch. The octopus catch reported was for 2003 (MoFW 2004), thus the same value was used from 2001 to 2010 because, according to the FAO database, that is the period octopus catch was reported. This procedure took care of the catch composition of the artisanal fishery from 1985 to 2007. From 1950 to 1984, the catch composition of 1985 was used and from 2008 to 2010 averages of 2006 and 2007 were used (Table B3).

Subsistence fishery

Similar to the Red Sea, the catch and composition of the subsistence fishery in the Gulf of Aden was calculated as a proportion of the artisanal fishery. In the Red Sea calculation, besides the percentage of the artisanal catch, this included the total catch of the small pelagic beach seine fishery which was solely a subsistence fishery. However, in the Gulf of Aden this was not the case because catching small pelagic fish is a major part of the artisanal fishery. The subsistence was calculated to be 30% of the artisanal from 1950 to 1974. This is a reasonably conservative estimate given that fishers in the region claim to give more than 50% of their catch to family, friends and people who need support before the artisanal fishery became commercialized with the advent of motorization (which for Yemen started to have an impact in 1975). Thus, the percentage was lowered to 20% for 1975. Even if the fish given freely is getting less and less, it is still part of the tradition. Hence it was assumed to be 10% of the artisanal catch in 2010, and interpolated between 1975 and 2010.

Table B2: Sources used to calculate the catch composition (%) of the pelagic fisheries catches in Yemen’s Gulf of Aden EEZ.Taxa 1986 1987 1988 1989 2006 2007Anchovy 2.60 37.68 30.11 18.15 39.09 39.57Shark 16.07 16.84 15.78 10.78 8.14 7.82Sardinella logiceps 8.85 7.58 9.46 0.00 6.47 6.47Euthynnus affinis 3.63 2.79 3.77 3.25 2.82 3.77Thunnus albacares 3.30 1.49 4.52 2.19 25.16 23.22Scomber commerson 3.40 1.52 1.00 1.48 2.56 1.84Rastrelliger kanagurta 3.66 1.52 0.55 0.99 3.72 3.66Istiophorus platypterus 0.13 0.15 0.68 0.63 0.40 0.40Thunnus tonggol 0.38 0.29 0.50 0.49 2.88 2.87Auxis thazard 0.17 0.29 0.21 0.07 0.19 0.19Katswonus pelamis 0.12 0.10 0.06 0.09 0.09 0.09Psettodes erumei 0.02 0.01 0.01 0.00 0.01 0.01Others 57.67 29.74 33.34 61.88 8.47 10.08Source Saeed (1995) Saeed (1995) Saeed (1995) Saeed (1995) MoFW (2012) MoFW (2012)* Italic values are averages of 1986-1989

138

Industrial fishery

The industrial fishery in the Gulf of Aden of Yemen was operated mainly by USSR vessels until 1990. After the re-unification of Yemen, it is done almost exclusively by Yemeni vessels (Koehn and Aklilu 1999). As far as the catch composition of industrial fishery is concerned, data were available for the following years: 1985 – 1994 (PERSGA 2001); 1998 (PERSGA 2002); 2002 and 2003 (MoFW 2004), and 2006 and 2007 (MoFW 2012). All of these sources reported ‘demersal fishes’ as a whole. Invertebrates (cuttlefish, squid, shrimp, rock lobster, deep sea lobster, crabs and octopus) were divided to artisanal and industrial sector using ratios from 2002 and 2003 (MoFW 2004; see text in the above for details). The demersal fishes, which accounted for up to 95% in some years, were further disaggregated using data from Edward et al., (1986) into catfish (25.6%), jacks (15.6%), grunts (13.3%), seabream (13.3%) and ‘others’ (32.2%). For years in which data were missing, they were interpolated, except for 1950 – 1984, where data from 1985 were used and for 2008 – 2010, where the mean 2006 and 2007 was used (Table B4).

The industrial (trawl) fishery discards portion of its catch, which is usually large and needs to be accounted explicitly. The total discard amount for Yemen in the Gulf of Aden was calculated using the retained catch, multiplied by the ratio of discard to retained industrial catch of Yemen in the Red Sea (where discards were twice the amount retained). This is a reasonable extrapolation, because the trawl operation and regulations in both areas are very similar. The catch composition of the discarded catch was also calculated using the overall (1950–2010) average of Red Sea industrial discard composition (Table 11).

The catch composition of each sector was compared with the taxonomic composition of the data Yemen reported to FAO (www .fao.org/fishery/statistics/software/fishstat/en), and some subsequent adjustments performed. The few taxa explicitly accounted for in the FAO database were included to the reconstruction catch using their proportions from the total catch, and their catches subtracted from the group ‘others’. In addition, for sectors where the final value of the ‘others’ was more than 10% of the total for the respective sector, it was reduced to 10% and the extra catch distributed to the already identified taxa in proportion to their contribution to the total of the sector.

Table B3: Catch composition (%) of the artisanal fishery of Yemen in the Gulf of Aden.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Remarks

1950-84

20.97 14.09 6.13 3.18 2.72 1.75 1.59 0.38 0.39 0.18 0.09 0.01 4.29 0.96 0.00 43.26 1985 value

1985 20.97 14.09 6.13 3.18 2.72 1.75 1.59 0.38 0.39 0.18 0.09 0.01 4.29 0.96 0.00 43.26 PERSGA (2001)1986 2.44 15.10 8.32 3.41 3.10 3.19 3.44 0.12 0.35 0.16 0.11 0.02 4.90 1.18 0.00 54.16 PERSGA (2001)1987 36.51 16.32 7.35 2.70 1.44 1.48 1.48 0.14 0.28 0.28 0.10 0.01 1.84 1.26 0.00 28.82 PERSGA (2001)1988 29.28 15.34 9.20 3.66 4.39 0.98 0.53 0.67 0.48 0.21 0.06 0.01 1.80 0.96 0.00 32.42 PERSGA (2001)1989 17.51 10.40 0.00 3.13 2.11 1.43 0.95 0.61 0.48 0.07 0.09 0.00 2.79 0.78 0.00 59.67 PERSGA (2001)1990 18.91 10.37 0.37 3.14 3.45 1.50 1.12 0.60 0.62 0.07 0.09 0.00 1.67 0.79 0.00 57.29 PERSGA (2001)1991 20.30 10.31 0.75 3.15 4.82 1.58 1.29 0.60 0.76 0.08 0.09 0.00 0.79 0.75 0.00 54.74 Interpolation1992 21.49 10.15 1.12 3.12 6.14 1.64 1.44 0.58 0.90 0.09 0.09 0.00 0.64 1.01 0.00 51.59 Interpolation1993 22.64 9.97 1.49 3.09 7.45 1.70 1.60 0.57 1.04 0.09 0.09 0.00 0.93 0.96 0.00 48.38 Interpolation1994 24.14 9.93 1.89 3.10 8.88 1.78 1.78 0.56 1.19 0.10 0.09 0.00 0.05 0.67 0.00 45.84 Interpolation1995 25.33 9.77 2.26 3.07 10.21 1.84 1.94 0.55 1.33 0.11 0.09 0.00 0.20 0.60 0.00 42.69 Interpolation1996 26.53 9.61 2.64 3.04 11.53 1.91 2.09 0.53 1.46 0.12 0.09 0.00 0.35 0.52 0.00 39.54 Interpolation1997 27.72 9.45 3.01 3.02 12.86 1.97 2.25 0.52 1.60 0.12 0.09 0.01 0.51 0.45 0.00 36.39 Interpolation1998 28.92 9.29 3.39 2.99 14.18 2.03 2.41 0.50 1.74 0.13 0.09 0.01 0.66 0.38 0.00 33.25 Interpolation1999 30.11 9.13 3.76 2.96 15.51 2.09 2.56 0.49 1.87 0.14 0.09 0.01 0.81 0.31 0.00 30.12 Interpolation2000 31.31 8.97 4.14 2.93 16.84 2.15 2.72 0.48 2.01 0.14 0.09 0.01 0.97 0.23 0.00 26.99 Interpolation2001 32.50 8.80 4.51 2.91 18.16 2.21 2.88 0.46 2.15 0.15 0.09 0.01 1.12 0.16 0.02 23.85 Interpolation2002 33.70 8.64 4.88 2.88 19.49 2.27 3.04 0.45 2.29 0.16 0.09 0.01 1.27 0.09 0.02 20.73 MoFW (2004)2003 34.50 8.39 5.20 2.82 20.57 2.31 3.16 0.43 2.40 0.16 0.09 0.01 2.37 0.13 0.02 17.42 MoFW (2004)2004 35.57 8.21 5.55 2.79 21.81 2.36 3.30 0.41 2.52 0.17 0.09 0.01 2.73 0.11 0.02 14.31 Interpolation2005 36.63 8.03 5.90 2.75 23.04 2.42 3.44 0.40 2.65 0.17 0.09 0.01 3.09 0.09 0.02 11.21 Interpolation2006 37.68 7.85 6.24 2.72 24.26 2.47 3.59 0.38 2.78 0.18 0.09 0.01 3.44 0.07 0.02 8.23 MoFW (2012)2007 38.40 7.59 6.28 3.66 22.53 1.79 3.55 0.39 2.79 0.18 0.09 0.01 2.78 0.04 0.02 9.89 MoFW (2012)2008-10

38.04 7.72 6.26 3.19 23.40 2.13 3.57 0.39 2.78 0.18 0.09 0.01 3.11 0.05 0.02 9.06 Average of 2006 & 2007

1: Anchovy; 2: Shark; 3: Sardinella logiceps; 4: Euthynnus affinis; 5: Thunnus albacares; 6: Scomber commerson; 7: Rastrelliger kanagurta; 8: Istiophorus platypterus; 9: Thunnus tonggol; 10: Auxis thazard; 11: Katswonus pelamis; 12: Psettodes erumei; 13: Cuttlefish; 14: Rock lobster; 15: Octopus; 16: Others

Yemen - Tesfamichael et al. 139

results and disCussion

Historically, Yemen’s catches in its Gulf of Aden EEZ has, except for a brief period in the early 1990s, represented the bulk of the catch in Yemen’s waters (Figure 2). The total catch was low until it started to increase at the beginning of the 1970s with the introduction of trawlers, while the largest increase was at the beginning of the 1990s, which corresponds with the unification of Yemen and stability of the country; finally, the total catch declined after its peak in 2004 (Figure B2, Table B5). Overall, the Gulf of Aden represented 77% of the total 9.8 million t reconstructed catch for all of Yemen from 1950 to 2010, which represented a little more than double the catch reported to FAO.

The artisanal fishery was the largest contributor to the total catch; jointly with the subsistence fishery, it is the only continuous fishery, in contrast to the industrial fishery, which appeared only in the mid-1960s. The industrial catch (both retained and discarded) was high from the mid-1970s to the end of 1980s (Figure B2). Industrial discards are high relative to the retained catch (i.e., 67% of the industrial catch), because the fishery’s main target is shrimp, which usually accounts for only a small fraction of the total catch. Overall, from 1950 to 2010, the artisanal fishery accounted for 63% of total catch, discards (18%), the industrial fishery retained catch (9%) and the subsistence fishery (10%). Recall that here, ‘subsistence’ refers to fish that is consumed by crew or freely given to family and friends by the artisanal fishery, and which is not recorded at all in fisheries statistics. This definition is in line with the delineation by the fishery administration of Yemen.

The reported catch (the part of the reconstructed catch accounted in the FAO data) represented only 32% of the total catch (Figure B3, Table B6). The unreported catch and discards accounted for 50% and 18%, respectively. Both the unreported catch and discards are not accounted in the FAO database, the main difference between the two is that unreported catches are landed while discards are thrown back to the sea, i.e., not landed.

The dominant sector, artisanal, had a stable and low total catch level until the mid-1990s when it started to show an increasing trend. The highest increase, however, started in 2000. The artisanal fishery exploits a large number of taxa. Foremost are Clupeidae (37% of the artisanal catch), caught in the productive waters in the eastern part of the Yemeni Gulf of Aden waters. The distant second is yellowfin tuna (Thunnus albacares; 16%) and sharks (14%). The top 9 taxa made up 88% of the total catch (Figure B4).

Table B4: Catch composition (%) of the retained industrial fishery catch of Yemen in the Gulf of Aden.Year Catfish Jacks Grunts Seabream Cuttlefish Squid Shrimp Rock lobster Deep sea lobster Crabs Octopus Others Remarks1950-84

23.65 14.41 12.29 12.29 6.59 0.00 0.00 1.04 0.00 0.00 0.00 29.75 1985 value

1985 23.65 14.41 12.29 12.29 6.59 0.00 0.00 1.04 0.00 0.00 0.00 29.75 PERSGA (2001)1986 23.81 14.51 12.37 12.37 6.00 0.00 0.00 1.01 0.00 0.00 0.00 29.94 PERSGA (2001)1987 24.49 14.92 12.72 12.72 2.94 0.00 0.00 1.41 0.00 0.00 0.00 30.80 PERSGA (2001)1988 24.27 14.79 12.61 12.61 3.78 0.00 0.00 1.42 0.00 0.00 0.00 30.53 PERSGA (2001)1989 23.60 14.38 12.26 12.26 6.54 0.00 0.00 1.28 0.00 0.00 0.00 29.68 PERSGA (2001)1990 19.39 11.81 10.07 10.07 18.21 0.00 0.00 6.06 0.00 0.00 0.00 24.39 PERSGA (2001)1991 22.57 13.75 11.73 11.73 7.14 0.00 0.00 4.71 0.00 0.00 0.00 28.39 PERSGA (2001)1992 15.18 9.25 7.89 7.89 19.30 0.00 0.00 21.39 0.00 0.00 0.00 19.10 PERSGA (2001)1993 19.86 12.10 10.32 10.32 13.05 0.00 0.00 9.37 0.00 0.00 0.00 24.98 PERSGA (2001)1994 20.49 12.49 10.65 10.65 1.84 0.00 0.00 18.10 0.00 0.00 0.00 25.78 PERSGA (2001)1995 19.91 12.13 10.34 10.34 6.95 1.64 0.05 13.58 0.02 0.00 0.00 25.04 Interpolation1996 19.32 11.77 10.04 10.04 12.05 3.28 0.11 9.05 0.05 0.00 0.00 24.30 Interpolation1997 18.73 11.42 9.73 9.73 17.15 4.91 0.16 4.53 0.07 0.00 0.00 23.56 Interpolation1998 18.15 11.06 9.43 9.43 22.26 6.55 0.21 0.00 0.10 0.00 0.00 22.82 PERSGA (2002)1999 18.47 11.26 9.60 9.60 22.50 4.37 0.46 0.44 0.07 0.00 0.00 23.24 Interpolation2000 18.80 11.46 9.77 9.77 22.74 2.18 0.71 0.88 0.03 0.00 0.01 23.65 Interpolation2001 19.13 11.66 9.94 9.94 22.98 0.00 0.96 1.33 0.00 0.00 0.01 24.06 Interpolation2002 19.13 11.66 9.94 9.94 22.98 0.00 0.96 1.33 0.00 0.00 0.01 24.06 MoFW (2004)2003 10.46 6.37 5.43 5.43 56.54 0.00 0.69 1.80 0.00 0.01 0.10 13.16 MoFW (2004)2004 12.47 7.60 6.48 6.48 49.37 0.00 0.46 1.35 0.00 0.01 0.07 15.71 Interpolation2005 14.49 8.83 7.53 7.53 42.20 0.00 0.23 0.91 0.00 0.00 0.03 18.25 Interpolation2006 16.50 10.06 8.57 8.57 35.03 0.00 0.00 0.46 0.00 0.00 0.00 20.80 MoFW (2012)2007 19.45 11.85 10.10 10.10 23.75 0.00 0.00 0.23 0.00 0.00 0.00 24.52 MoFW (2012)2008-10

17.97 10.95 9.34 9.34 29.39 0.00 0.00 0.35 0.00 0.00 0.00 22.66 Average of 2006-07

Figure B2: Reconstructed total catch of Yemen in its Gulf of Aden EEZ from 1950 to 2010 by sector compared to the total supplied to FAO.

140

The subsistence fishery follows a similar trend to the artisanal fishery, simply because it was calculated a ratio of the artisanal fishery (Figure B5). For more detailed catch composition of the artisanal and subsistence fisheries, see Tables (B7 and B8), respectively.

The industrial fishery, which was mainly trawling for shrimp, started in 1967 and the catch increased to a peak in 1986 (Figure B6, Table B9). Then, it declined drastically towards the end of the 1980s as the cold war was ending and most of the trawlers operating in the Gulf of Aden, which originated from the Soviet Union, stopped their operation. Although, the industrial fishery in the Gulf of Aden is almost non-existent since 2008, its contribution to the total catch from 1950 to 2010 (27%) was higher than that of its analog in the Red Sea (18%), reflecting the different ecology of the two seas. The Red Sea has extensive coral reefs, which makes it less convenient for trawling, while the Gulf of Aden has more suitable ground for trawling. Sea catfishes (Ariidae) dominate the industrial fishery catch, with 28% of the retained catch. The discarded industrial catch follows a similar pattern to the retained catch, with ponyfishes (Leiognathidae) dominating with 61% (Figure B7, Table B10).

For the whole Gulf of Aden, Clupeidae is the dominant taxon (27%), followed by yellowfin tuna (Thunnus albacores) at 11%, both of which are the dominant taxa in the artisanal fishery. The third most important taxon is ponyfishes (11%), the most important discarded group of the industrial fishery (Figure B8; see Table B11 for detailed composition). Twelve taxa make up more than 80% of the total catch of Yemen in the Gulf of Aden. Catches are increasingly dominated by pelagic fishes, which contributed 65% of the total catch from 1950 to 2010.

Least important in terms of bulk catch, but very valuable in monetary terms are shrimp, octopus, crabs, lobster and sea cucumber, which were only reported for the most recent years, but contributed less than 1% of the reconstructed total catch. Cuttlefish, however, accounted for 4% of the total catch, the highest contribution of any invertebrate. Demersal catches, in contrast to pelagic fishes, have declined since their peak in the mid-1980s to their lowest value at the beginning of 1990s and almost disappeared after 2008. The 1990s decline was a result of the departure of the Soviet fleet and collapse of the Yemeni trawl fleet following the reunification of Yemen in 1990.

Figure B5: Composition of the reconstructed catch of the subsistence fishery of Yemen in the Gulf of Aden from 1950 to 2010.

Figure B3: Reconstructed total catch for Yemen in its Gulf of Aden EEZ from 1950 to 2010 by component. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.

Figure B4: Composition of the reconstructed catch of the artisanal fishery of Yemen in the Gulf of Aden from 1950 to 2010.

Figure B6: Composition of the retained industrial fishery catch of Yemen in its Gulf of Aden EEZ from 1950 to 2010.

Yemen - Tesfamichael et al. 141

This reconstruction of the catch of Yemeni fisheries in the Gulf of Aden, even if brief and preliminary, improves the understanding of Yemen’s fishery, in these waters both in terms of sectorial resolution and taxonomic breakdown over a long period of time. There were many data gaps, hence the need for the catch reconstruction effort, where we filled them with transparent assumptions with the best knowledge available. These are open for constructive criticism, as this work is by no means final or conclusive. We view it only as a first iteration towards improving our understanding of Yemen’s fisheries in the Gulf of Aden.

Figure B7: Composition of the discarded industrial fishery catch of Yemen in its Gulf of Aden EEZ from 1950 to 2010.

Figure B8: The composition of the total catch of Yemen in its Gulf of Aden EEZ from 1950 to 2010.

142

referenCes

Bonfiglioli A and Hariri KI (2004) Small-scale fisheies in Yemen: Social assessment and development prospects. FAO, The World Bank. 11 p.

Edwards RRC, Bakhader A and Shaher S (1985) Growth, mortality, age composition and fisheries yields of fish from the Gulf of Aden. Journal of Fish Biology 27(1): 13-21.

FAO (2002) Information on Fisheries Management in the Republic of Yemen, February 2002. www.fao.orgKoehn D and Aklilu P (1999) Republic of Yemen–Fisheries Sector Strategy Note World Bank. 1-23 p.MoFW (2004) Fisheries Statistics Book. Ministry of Fish Wealth, General Department for Planning and Statistic. 224

p.MoFW (2008) Catch Statistics Yemen 1990-2007. Ministry of Fish Wealth, General Department for Planning and

Statistic.MoFW (2012) Catch Statistics Yemen 2008-2010. Ministry of Fish Wealth, General Department for Planning and

Statistic.Morgan G (2006) Country Review: Yemen. p. 458 In De Young C (ed.), Review of the state of world marine capture

fisheries management: Indian Ocean. FAO Fisheries Technical Paper. No. 488. FAO, Rome.PERSGA (2001) Strategic action programme for the Red Sea and Gulf of Aden. Regional Organization for the

Conservation of the Environment of the Red Sea and Gulf of Aden (PERSGA), Jeddah, Saudi Arabia. 149-180 p.PERSGA (2002) Status of the Living Marine Resources in the Red Sea and Gulf of Aden and Their Management.

Strategic action programme for the Red Sea and Gulf of Aden, Regional Organization for the Conservation of the Environment of the Red Sea and Gulf of Aden (PERSGA), Jeddah, Saudi Arabia. 134 p.

Saeed SS (1995) Biology and status of Tuna in Yemen. Marine Science Research Centre, Labour Island–Khormaksar, Aden, Yemen.

Sanders MJ and Morgan GR (1989) Review of the fisheries resources of the Red Sea and Gulf of Aden. FAO, Rome. 138 p.

Yemen - Tesfamichael et al. 143

Table B5: Reconstructed total catch (in tonnes) of Yemen in its Gulf of Aden EEZ from 1950 to 2010 by sector compared to the total supplied to FAO.

Year FAO landings Reconstructed total catch Artisanal Discards Subsistence Industrial1950 20,889 39,765 30,589 0 9,177 01951 20,865 39,765 30,589 0 9,177 01952 24,366 46,605 35,850 0 10,755 01953 25,047 47,719 36,707 0 11,012 01954 25,010 47,719 36,707 0 11,012 01955 28,900 55,354 42,580 0 12,774 01956 17,735 34,675 26,673 0 8,002 01957 18,581 35,948 27,652 0 8,296 01958 17,536 34,198 26,306 0 7,892 01959 20,101 38,811 29,855 0 8,956 01960 18,245 35,471 27,285 0 8,186 01961 17,980 34,994 26,918 0 8,075 01962 17,939 34,994 26,918 0 8,075 01963 17,899 34,994 26,918 0 8,075 01964 20,444 39,765 30,589 0 9,177 01965 20,945 39,765 30,589 0 9,177 01966 19,790 39,765 30,589 0 9,177 01967 22,217 44,006 32,210 1,429 9,663 7041968 22,079 45,155 31,314 2,979 9,394 1,4681969 20,709 46,304 30,418 4,529 9,125 2,2321970 21,670 48,156 29,959 6,169 8,988 3,0401971 20,147 47,522 27,990 7,459 8,397 3,6761972 24,992 58,227 32,454 10,742 9,736 5,2941973 36,051 81,440 42,934 17,166 12,880 8,4601974 42,777 98,785 49,228 23,304 14,768 11,4851975 40,729 95,434 47,142 26,033 9,428 12,8301976 54,083 124,899 58,148 37,035 11,463 18,2531977 54,209 128,203 56,198 40,919 10,919 20,1671978 53,414 120,815 49,811 41,176 9,535 20,2941979 51,978 133,137 51,563 48,129 9,723 23,7211980 62,614 173,806 63,147 66,271 11,727 32,6621981 54,439 158,921 54,080 63,604 9,889 31,3481982 37,458 126,848 40,361 53,068 7,265 26,1551983 40,882 130,560 38,766 56,889 6,867 28,0381984 43,168 150,562 41,627 68,111 7,255 33,5691985 56,316 173,439 44,533 81,235 7,634 40,0371986 55,893 178,125 38,868 88,893 6,552 43,8111987 46,248 170,509 45,087 79,010 7,472 38,9401988 45,140 154,527 49,065 65,292 7,991 32,1791989 44,125 147,063 49,975 59,679 7,996 29,4131990 47,653 103,426 67,177 17,210 10,556 8,4821991 45,516 106,070 65,522 20,389 10,109 10,0491992 38,653 80,609 62,489 5,800 9,463 2,8581993 34,329 82,912 57,279 11,470 8,510 5,6531994 33,561 69,834 55,692 4,037 8,115 1,9901995 55,907 103,346 76,476 10,681 10,925 5,2641996 66,296 111,993 76,889 16,304 10,764 8,0351997 72,526 136,762 87,084 25,277 11,943 12,4581998 86,000 166,364 98,199 36,827 13,187 18,1501999 86,438 171,785 105,376 35,207 13,849 17,3522000 91,288 166,922 106,417 31,364 13,682 15,4582001 119,765 216,754 143,630 36,887 18,056 18,1802002 146,817 285,544 196,692 43,331 24,165 21,3562003 195,830 359,749 283,699 28,138 34,044 13,8682004 214,976 396,818 324,889 22,688 38,058 11,1822005 197,393 362,161 307,936 12,749 35,193 6,2842006 185,326 342,406 302,458 4,184 33,702 2,0622007 143,131 263,108 224,202 9,756 24,342 4,8082008 92,622 165,860 148,730 943 15,723 4652009 118,017 221,980 199,565 1,265 20,527 6232010 146,108 266,110 239,855 1,520 23,985 749

144Table B6: Reconstructed total catch (in tonnes) for Yemen in its Gulf of Aden EEZ from 1950 to 2010 by component. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.Year Reported Unreported Discards1950 12,420 27,346 01951 12,417 27,348 01952 15,651 30,954 01953 16,265 31,453 01954 16,250 31,468 01955 18,584 36,769 01956 10,908 23,767 01957 10,843 25,105 01958 10,630 23,568 01959 12,222 26,589 01960 10,670 24,801 01961 10,744 24,250 01962 10,721 24,272 01963 10,700 24,294 01964 12,329 27,436 01965 13,598 26,168 01966 13,019 26,746 01967 13,939 28,638 1,4291968 14,012 28,165 2,9791969 14,192 27,583 4,5291970 14,097 27,890 6,1691971 13,917 26,146 7,4591972 16,416 31,069 10,7421973 21,293 42,982 17,1661974 21,755 53,726 23,3041975 25,237 44,164 26,0331976 32,025 55,839 37,0351977 30,689 56,595 40,9191978 31,854 47,785 41,1761979 31,607 53,400 48,1291980 43,108 64,428 66,2711981 34,500 60,817 63,6041982 28,502 45,279 53,0681983 34,035 39,637 56,8891984 26,241 56,210 68,1111985 34,192 58,012 81,2351986 40,538 48,694 88,8931987 25,690 65,809 79,0101988 25,723 63,512 65,2921989 29,758 57,626 59,6791990 27,515 58,701 17,2101991 30,466 55,214 20,3891992 26,667 48,143 5,8001993 25,432 46,010 11,4701994 23,502 42,295 4,0371995 34,744 57,921 10,6811996 42,445 53,243 16,3041997 46,842 64,644 25,2771998 59,358 70,178 36,8271999 61,365 75,213 35,2072000 62,111 73,447 31,3642001 87,467 92,400 36,8872002 117,679 124,534 43,3312003 158,366 173,244 28,1382004 168,912 205,217 22,6882005 149,833 199,579 12,7492006 135,485 202,737 4,1842007 104,004 149,349 9,7562008 68,901 96,016 9432009 86,237 134,478 1,2652010 85,928 178,662 1,520

Yemen - Tesfamichael et al. 145Table B7: Composition of the reconstructed catch (in tonnes) of the artisanal fishery of Yemen in the Gulf of Aden from 1950 to 2010.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 181950 10,175 1,321 6,835 2,976 1,544 2,082 772 851 190 467 183 0 85 43 0 4 0 3,0591951 10,175 1,321 6,835 2,976 1,544 2,082 772 851 190 467 183 0 85 43 0 4 0 3,0591952 11,925 1,549 8,010 3,488 1,809 2,441 905 997 223 547 215 0 100 51 0 5 0 3,5851953 12,210 1,586 8,202 3,571 1,852 2,499 927 1,021 228 561 220 0 102 52 0 5 0 3,6711954 12,210 1,586 8,202 3,571 1,852 2,499 927 1,021 228 561 220 0 102 52 0 5 0 3,6711955 14,164 1,839 9,514 4,143 2,149 2,899 1,075 1,185 265 650 255 0 119 60 0 6 0 4,2581956 8,873 1,152 5,960 2,595 1,346 1,816 673 742 166 407 160 0 74 38 0 4 0 2,6671957 9,198 1,195 6,179 2,690 1,395 1,883 698 769 172 422 166 0 77 39 0 4 0 2,7651958 8,751 1,136 5,878 2,559 1,327 1,791 664 732 164 402 158 0 73 37 0 4 0 2,6311959 9,931 1,290 6,671 2,905 1,507 2,032 754 831 186 456 179 0 83 42 0 4 0 2,9851960 9,076 1,179 6,097 2,655 1,377 1,858 689 759 170 417 163 0 76 39 0 4 0 2,7291961 8,954 1,163 6,015 2,619 1,358 1,833 679 749 167 411 161 0 75 38 0 4 0 2,6921962 8,954 1,163 6,015 2,619 1,358 1,833 679 749 167 411 161 0 75 38 0 4 0 2,6921963 8,954 1,163 6,015 2,619 1,358 1,833 679 749 167 411 161 0 75 38 0 4 0 2,6921964 10,175 1,321 6,835 2,976 1,544 2,082 772 851 190 467 183 0 85 43 0 4 0 3,0591965 10,175 1,321 6,835 2,976 1,544 2,082 772 851 190 467 183 0 85 43 0 4 0 3,0591966 10,175 1,321 6,835 2,976 1,544 2,082 772 851 190 467 183 0 85 43 0 4 0 3,0591967 10,714 1,392 7,197 3,134 1,625 2,193 813 896 200 492 193 0 90 46 0 5 0 3,2211968 10,416 1,353 6,997 3,047 1,580 2,132 790 871 195 478 188 0 87 44 0 4 0 3,1311969 10,118 1,314 6,797 2,959 1,535 2,071 768 846 189 465 182 0 85 43 0 4 0 3,0421970 9,966 1,294 6,694 2,915 1,512 2,040 756 834 186 458 179 0 83 42 0 4 0 2,9961971 9,311 1,209 6,254 2,723 1,412 1,905 707 779 174 427 168 0 78 40 0 4 0 2,7991972 10,796 1,402 7,252 3,158 1,638 2,209 819 903 202 496 194 0 90 46 0 5 0 3,2451973 14,282 1,855 9,593 4,177 2,167 2,923 1,084 1,195 267 656 257 0 120 61 0 6 0 4,2931974 16,375 2,127 10,999 4,789 2,484 3,351 1,243 1,370 306 752 295 0 137 70 0 7 0 4,9231975 15,681 2,037 10,533 4,587 2,379 3,209 1,190 1,312 293 720 282 0 131 67 0 7 0 4,7141976 19,342 2,512 12,993 5,657 2,934 3,959 1,468 1,618 361 888 348 0 162 82 0 8 0 5,8151977 18,694 2,428 12,557 5,468 2,836 3,826 1,419 1,564 349 858 337 0 156 79 0 8 0 5,6201978 16,569 2,152 11,130 4,846 2,514 3,391 1,257 1,386 310 761 298 0 139 70 0 7 0 4,9811979 17,152 2,228 11,521 5,017 2,602 3,510 1,302 1,435 321 787 309 0 144 73 0 7 0 5,1561980 20,999 2,727 14,105 6,142 3,186 4,298 1,594 1,756 392 964 378 0 176 89 0 9 17 6,3151981 17,962 2,333 12,065 5,253 2,725 3,676 1,363 1,502 336 825 323 0 150 76 0 8 75 5,4081982 13,403 1,741 9,003 3,920 2,033 2,743 1,017 1,121 250 615 241 0 112 57 0 6 60 4,0361983 12,871 1,672 8,646 3,765 1,953 2,634 977 1,077 241 591 232 0 108 55 0 6 65 3,8771984 13,842 1,798 9,298 4,049 2,100 2,833 1,050 1,158 259 636 249 0 116 59 0 6 12 4,1631985 14,799 1,922 9,941 4,329 2,245 3,029 1,123 1,238 277 679 267 0 124 63 0 6 38 4,4531986 1,857 2,363 11,494 6,332 2,596 3,734 2,616 2,432 269 895 92 0 122 86 0 16 77 3,8871987 20,813 821 9,302 4,187 1,541 1,047 842 842 158 720 82 0 159 58 0 4 0 4,5091988 19,115 2,868 10,017 6,007 2,390 1,173 349 637 316 628 435 45 136 39 0 4 0 4,9061989 18,848 2,273 11,195 0 3,370 3,002 1,025 1,534 514 836 656 1,558 72 93 0 2 0 4,9981990 26,148 4,775 14,334 514 4,344 2,304 1,548 2,079 857 1,094 834 1,403 102 121 0 3 0 6,7181991 25,783 6,117 13,095 953 3,997 1,007 1,636 2,007 970 948 756 1,481 103 112 0 3 0 6,5521992 24,350 6,958 11,497 1,273 3,534 725 1,637 1,860 1,021 1,147 659 1,375 100 100 0 3 0 6,2491993 21,978 7,232 9,676 1,451 2,995 906 1,552 1,650 1,006 929 550 1,447 92 86 0 3 0 5,7281994 21,743 8,000 8,948 1,703 2,791 43 1,602 1,606 1,070 603 504 1,333 92 81 0 4 0 5,5691995 29,970 12,076 11,561 2,679 3,633 238 2,289 2,182 1,568 705 645 1,040 129 107 0 5 0 7,6481996 30,046 13,062 10,885 2,989 3,447 401 2,370 2,159 1,657 593 602 751 131 102 0 5 0 7,6891997 33,841 15,696 11,535 3,678 3,682 619 2,746 2,401 1,953 550 632 776 149 111 0 6 0 8,7081998 38,005 18,641 12,207 4,451 3,929 868 3,163 2,666 2,284 497 662 711 170 119 0 8 0 9,8201999 40,594 20,907 12,303 5,070 3,993 1,097 3,456 2,817 2,528 411 660 689 183 123 0 8 0 10,5382000 40,827 21,953 11,691 5,393 3,827 1,261 3,548 2,805 2,624 303 620 610 186 119 0 9 0 10,6422001 54,950 30,702 14,883 7,623 4,916 1,894 4,865 3,741 3,634 270 780 555 252 155 36 12 0 14,3632002 75,029 43,385 19,242 10,873 6,413 2,835 6,757 5,063 5,092 193 996 528 347 204 47 17 0 19,6692003 106,491 63,501 25,893 16,041 8,710 7,325 9,741 7,127 7,398 413 1,323 500 496 280 65 24 0 28,3702004 121,242 74,339 27,974 18,910 9,501 9,306 11,250 8,053 8,605 378 1,410 456 568 309 72 28 0 32,4892005 114,239 71,844 25,032 18,387 8,585 9,628 10,740 7,533 8,267 275 1,244 455 538 283 66 27 0 30,7942006 113,981 73,363 23,735 18,878 8,223 10,417 10,847 7,465 8,398 197 1,162 226 540 274 64 28 0 24,6612007 86,107 50,528 17,017 14,088 8,204 6,234 7,964 4,004 6,245 87 867 222 403 205 47 21 0 21,9572008 56,585 34,797 11,480 9,314 4,743 4,629 5,309 3,163 4,136 77 573 125 267 135 31 14 0 13,3512009 75,925 46,691 15,404 12,498 6,364 6,211 7,123 4,245 5,550 104 769 136 358 182 42 18 0 17,9452010 91,254 56,117 18,514 15,021 7,649 7,465 8,561 5,102 6,670 125 925 142 430 218 51 22 0 21,589

1: Clupeidae; 2: Thunnus albacares; 3: Carcharhinidae; 4: Sardinella logiceps; 5: Euthynnus affinis; 6: Sepiidae; 7: Rastrelliger kanagurta; 8: Scomberomorus commerson; 9: Thunnus tonggol; 10: Panulirus homarus; 11: Istiophorus platypterus; 12: Scomberomorus guttatus; 13: Auxis thazard thazard; 14: Katswonus pelamis; 15: Octopus spp.; 16: Psettodes erumei; 17: Xiphias gladius; 18: Others

146

Table B8: Composition of the reconstructed catch (in tonnes) of the subsistence fishery of Yemen in the Gulf of Aden from 1950 to 2010. Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 181950 3,053 2,050 396 893 625 463 232 255 57 140 55 0 26 13 1 0 0 9181951 3,053 2,050 396 893 625 463 232 255 57 140 55 0 26 13 1 0 0 9181952 3,578 2,403 465 1,046 732 543 271 299 67 164 64 0 30 15 2 0 0 1,0761953 3,663 2,461 476 1,071 750 556 278 306 68 168 66 0 31 16 2 0 0 1,1011954 3,663 2,461 476 1,071 750 556 278 306 68 168 66 0 31 16 2 0 0 1,1011955 4,249 2,854 552 1,243 870 645 322 355 79 195 77 0 36 18 2 0 0 1,2771956 2,662 1,788 346 779 545 404 202 223 50 122 48 0 22 11 1 0 0 8001957 2,759 1,854 358 807 565 419 209 231 52 127 50 0 23 12 1 0 0 8301958 2,625 1,763 341 768 537 398 199 220 49 121 47 0 22 11 1 0 0 7891959 2,979 2,001 387 871 610 452 226 249 56 137 54 0 25 13 1 0 0 8961960 2,723 1,829 354 796 557 413 207 228 51 125 49 0 23 12 1 0 0 8191961 2,686 1,804 349 786 550 408 204 225 50 123 48 0 22 11 1 0 0 8081962 2,686 1,804 349 786 550 408 204 225 50 123 48 0 22 11 1 0 0 8081963 2,686 1,804 349 786 550 408 204 225 50 123 48 0 22 11 1 0 0 8081964 3,053 2,050 396 893 625 463 232 255 57 140 55 0 26 13 1 0 0 9181965 3,053 2,050 396 893 625 463 232 255 57 140 55 0 26 13 1 0 0 9181966 3,053 2,050 396 893 625 463 232 255 57 140 55 0 26 13 1 0 0 9181967 3,214 2,159 417 940 658 488 244 269 60 148 58 0 27 14 1 0 0 9661968 3,125 2,099 406 914 640 474 237 261 58 143 56 0 26 13 1 0 0 9391969 3,035 2,039 394 888 621 460 230 254 57 139 55 0 25 13 1 0 0 9131970 2,990 2,008 388 874 612 454 227 250 56 137 54 0 25 13 1 0 0 8991971 2,793 1,876 363 817 572 424 212 234 52 128 50 0 23 12 1 0 0 8401972 3,239 2,175 421 947 663 491 246 271 61 149 58 0 27 14 1 0 0 9741973 4,284 2,878 556 1,253 877 650 325 358 80 197 77 0 36 18 2 0 0 1,2881974 4,913 3,300 638 1,437 1,005 745 373 411 92 226 88 0 41 21 2 0 0 1,4771975 3,136 2,107 407 917 642 476 238 262 59 144 56 0 26 13 1 0 0 9431976 3,813 2,561 495 1,115 780 578 289 319 71 175 69 0 32 16 2 0 0 1,1461977 3,632 2,440 472 1,062 743 551 276 304 68 167 65 0 30 15 2 0 0 1,0921978 3,172 2,131 412 928 649 481 241 265 59 146 57 0 27 13 1 0 0 9541979 3,234 2,173 420 946 662 491 245 271 60 148 58 0 27 14 1 0 0 9721980 3,900 2,620 506 1,141 798 592 296 326 73 179 70 0 33 17 2 3 0 1,1731981 3,284 2,206 427 961 672 498 249 275 61 151 59 0 27 14 1 14 0 9891982 2,413 1,621 313 706 494 366 183 202 45 111 43 0 20 10 1 11 0 7261983 2,280 1,532 296 667 467 346 173 191 43 105 41 0 19 10 1 11 0 6871984 2,413 1,621 313 706 494 366 183 202 45 111 43 0 20 10 1 2 0 7251985 2,537 1,704 329 742 519 385 193 212 47 116 46 0 21 11 1 6 0 7631986 313 1,938 398 1,067 629 438 441 410 45 151 16 0 21 15 3 13 0 6551987 3,449 1,542 136 694 174 255 140 139 26 119 14 0 26 10 1 0 0 7471988 3,113 1,631 467 978 191 389 57 104 51 102 71 7 22 6 1 0 0 7991989 3,016 1,791 364 0 480 539 164 246 82 134 105 249 11 15 0 0 0 8001990 4,109 2,253 750 81 362 683 243 327 135 172 131 220 16 19 0 0 0 1,0561991 3,978 2,020 944 147 155 617 252 310 150 146 117 229 16 17 0 0 0 1,0111992 3,687 1,741 1,054 193 110 535 248 282 155 174 100 208 15 15 1 0 0 9461993 3,265 1,438 1,074 216 135 445 231 245 149 138 82 215 14 13 0 0 0 8511994 3,168 1,304 1,166 248 6 407 233 234 156 88 73 194 13 12 1 0 0 8121995 4,281 1,652 1,725 383 34 519 327 312 224 101 92 149 18 15 1 0 0 1,0931996 4,206 1,524 1,829 418 56 483 332 302 232 83 84 105 18 14 1 0 0 1,0761997 4,641 1,582 2,153 504 85 505 377 329 268 75 87 106 20 15 1 0 0 1,1941998 5,104 1,639 2,503 598 117 528 425 358 307 67 89 96 23 16 1 0 0 1,3191999 5,335 1,617 2,748 666 144 525 454 370 332 54 87 91 24 16 1 0 0 1,3852000 5,249 1,503 2,823 693 162 492 456 361 337 39 80 78 24 15 1 0 0 1,3682001 6,908 1,871 3,860 958 238 618 612 470 457 34 98 70 32 19 2 0 4 1,8062002 9,218 2,364 5,330 1,336 348 788 830 622 626 24 122 65 43 25 2 0 6 2,4172003 12,779 3,107 7,620 1,925 879 1,045 1,169 855 888 50 159 60 59 34 3 0 8 3,4042004 14,203 3,277 8,708 2,215 1,090 1,113 1,318 943 1,008 44 165 53 67 36 3 0 8 3,8062005 13,056 2,861 8,211 2,101 1,100 981 1,227 861 945 31 142 52 62 32 3 0 8 3,5192006 12,701 2,645 8,175 2,104 1,161 916 1,209 832 936 22 130 25 60 31 3 0 7 2,7482007 9,349 1,848 5,486 1,530 677 891 865 435 678 9 94 24 44 22 2 0 5 2,3842008 5,982 1,214 3,679 985 489 501 561 334 437 8 61 13 28 14 1 0 3 1,4112009 7,809 1,584 4,802 1,286 639 655 733 437 571 11 79 14 37 19 2 0 4 1,8462010 9,125 1,851 5,612 1,502 747 765 856 510 667 12 92 14 43 22 2 0 5 2,159

1: Clupeidae; 2: Carcharhinidae; 3: Thunnus albacares; 4: Sardinella logiceps; 5: Sepiidae; 6: Euthynnus affinis; 7: Rastrelliger kanagurta; 8: Scomberomorus commerson; 9: Thunnus tonggol; 10: Panulirus homarus; 11: Istiophorus platypterus; 12: Scomberomorus guttatus; 13: Auxis thazard thazard; 14: Katswonus pelamis; 15: Psettodes erumei; 16: Xiphias gladius; 17: Octopus spp.; 18: Others

Yemen - Tesfamichael et al. 147Table B9: Composition of the retained industrial fishery catch (in tonnes) of Yemen in its Gulf of Aden EEZ from 1950 to 2010.Year 1 2 3 4 5 6 7 8 9 10 11 12 131950 0 0 0 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 0 0 0 01967 213 111 111 59 92 38 9 0 0 0 0 0 701968 445 231 231 124 192 79 19 0 0 0 0 0 1471969 676 351 351 188 292 120 30 0 0 0 0 0 2231970 921 479 479 257 398 163 40 0 0 0 0 0 3041971 1,114 579 579 310 481 198 49 0 0 0 0 0 3681972 1,604 833 833 447 693 284 70 0 0 0 0 0 5291973 2,563 1,332 1,332 714 1,107 455 112 0 0 0 0 0 8461974 3,479 1,808 1,808 969 1,503 617 152 0 0 0 0 0 1,1491975 3,887 2,019 2,019 1,083 1,679 689 170 0 0 0 0 0 1,2831976 5,530 2,873 2,873 1,540 2,389 981 242 0 0 0 0 0 1,8251977 6,110 3,174 3,174 1,702 2,639 1,084 268 0 0 0 0 0 2,0171978 6,148 3,194 3,194 1,713 2,656 1,090 269 0 0 0 0 0 2,0291979 7,186 3,733 3,733 2,002 3,105 1,274 315 0 0 0 0 0 2,3721980 9,895 5,141 5,141 2,757 4,275 1,755 433 0 0 0 0 0 3,2661981 9,497 4,934 4,934 2,646 4,103 1,684 416 0 0 0 0 0 3,1351982 7,923 4,117 4,117 2,207 3,423 1,405 347 0 0 0 0 0 2,6151983 8,494 4,413 4,413 2,366 3,670 1,506 372 0 0 0 0 0 2,8041984 10,170 5,283 5,283 2,833 4,393 1,804 445 0 0 0 0 0 3,3571985 12,129 6,301 6,301 3,379 5,240 2,151 531 0 0 0 0 0 4,0041986 13,398 6,961 6,961 3,379 5,788 2,376 567 0 0 0 0 0 4,3811987 12,401 6,443 6,443 1,487 5,357 2,199 717 0 0 0 0 0 3,8941988 10,117 5,256 5,256 1,576 4,371 1,794 591 0 0 0 0 0 3,2181989 8,885 4,616 4,616 2,461 3,838 1,576 480 0 0 0 0 0 2,9411990 1,957 1,017 1,017 1,838 846 347 611 0 0 0 0 0 8481991 2,850 1,481 1,481 901 1,231 505 594 0 0 0 0 0 1,0051992 483 251 251 614 209 86 680 0 0 0 0 0 2861993 1,347 700 700 885 582 239 636 0 0 0 0 0 5651994 494 257 257 44 214 88 437 0 0 0 0 0 1991995 1,258 654 654 439 544 223 858 103 3 2 0 0 5261996 1,846 959 959 1,151 797 327 865 313 10 5 0 0 8041997 2,748 1,428 1,428 2,516 1,187 487 664 721 24 11 0 0 1,2461998 3,841 1,995 1,995 4,711 1,659 681 0 1,386 45 21 0 0 1,8151999 3,758 1,952 1,952 4,577 1,624 666 90 888 94 13 1 0 1,7352000 3,425 1,780 1,780 4,143 1,480 608 161 398 130 6 1 0 1,5462001 4,121 2,141 2,141 4,952 1,780 731 286 0 208 0 3 0 1,8182002 4,841 2,515 2,515 5,817 2,091 859 336 0 244 0 3 0 2,1362003 1,503 781 781 8,126 649 267 258 0 99 0 15 1 1,3872004 1,489 774 774 5,894 643 264 162 0 55 0 8 1 1,1182005 1,002 521 521 2,919 433 178 63 0 16 0 2 0 6282006 387 201 201 821 167 69 11 0 0 0 0 0 2062007 1,115 579 579 1,362 482 198 13 0 0 0 0 0 4812008 97 50 50 159 42 17 2 0 0 0 0 0 462009 130 68 68 213 56 23 3 0 0 0 0 0 622010 157 81 81 256 68 28 3 0 0 0 0 0 751: Ariidae; 2: Haemulidae; 3: Chrysoblephus spp.; 4: Sepiidae; 5: Trachurus spp.; 6: Carangidae; 7: Panulirus homarus; 8: Teuthida; 9: Penaeidae; 10: Palinuridae; 11: Octopus spp.; 12: Brachyura; 13: Others

148Table B10: Composition of the discarded industrial fishery catch (in tonnes) of Yemen in its Gulf of Aden EEZ from 1950 to 2010.

Year 1 2 3 4 5 6 7 8 9 101950 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 01967 867 98 56 56 28 28 14 14 14 91968 1,807 204 117 117 58 58 29 29 29 191969 2,748 310 177 177 89 89 44 44 44 291970 3,743 423 241 241 121 121 60 60 60 401971 4,525 511 292 292 146 146 73 73 73 481972 6,517 736 420 420 210 210 105 105 105 691973 10,415 1,176 672 672 336 336 168 168 168 1101974 14,139 1,596 912 912 456 456 228 228 228 1501975 15,794 1,783 1,019 1,019 509 509 255 255 255 1671976 22,469 2,537 1,450 1,450 725 725 362 362 362 2381977 24,826 2,803 1,602 1,602 801 801 400 400 400 2631978 24,982 2,821 1,612 1,612 806 806 403 403 403 2651979 29,200 3,297 1,884 1,884 942 942 471 471 471 3101980 40,207 4,539 2,594 2,594 1,297 1,297 648 648 648 4261981 38,589 4,357 2,490 2,490 1,245 1,245 622 622 622 4091982 32,197 3,635 2,077 2,077 1,039 1,039 519 519 519 3411983 34,515 3,897 2,227 2,227 1,113 1,113 557 557 557 3661984 41,323 4,666 2,666 2,666 1,333 1,333 667 667 667 4381985 49,286 5,565 3,180 3,180 1,590 1,590 795 795 795 5231986 53,932 6,089 3,479 3,479 1,740 1,740 870 870 870 5721987 47,936 5,412 3,093 3,093 1,546 1,546 773 773 773 5081988 39,613 4,472 2,556 2,556 1,278 1,278 639 639 639 4201989 36,208 4,088 2,336 2,336 1,168 1,168 584 584 584 3841990 10,442 1,179 674 674 337 337 168 168 168 1111991 12,370 1,397 798 798 399 399 200 200 200 1311992 3,519 397 227 227 114 114 57 57 57 371993 6,959 786 449 449 224 224 112 112 112 741994 2,449 277 158 158 79 79 40 40 40 261995 6,480 732 418 418 209 209 105 105 105 691996 9,892 1,117 638 638 319 319 160 160 160 1051997 15,336 1,731 989 989 495 495 247 247 247 1631998 22,343 2,523 1,442 1,442 721 721 360 360 360 2371999 21,360 2,412 1,378 1,378 689 689 345 345 345 2262000 19,029 2,148 1,228 1,228 614 614 307 307 307 2022001 22,380 2,527 1,444 1,444 722 722 361 361 361 2372002 26,289 2,968 1,696 1,696 848 848 424 424 424 2792003 17,071 1,927 1,101 1,101 551 551 275 275 275 1812004 13,765 1,554 888 888 444 444 222 222 222 1462005 7,735 873 499 499 250 250 125 125 125 822006 2,538 287 164 164 82 82 41 41 41 272007 5,919 668 382 382 191 191 95 95 95 632008 572 65 37 37 18 18 9 9 9 62009 768 87 50 50 25 25 12 12 12 82010 922 104 60 60 30 30 15 15 15 10

1: Leiognathidae; 2: Terapon spp.; 3: Gerreidae; 4: Trichiuridae; 5: Parastromateus niger; 6: Platycephalidae; 7: Clupeidae; 8: Mullidae; 9: Stomatopoda; 10: Carangoides malabaricus

Yemen - Tesfamichael et al. 149B10 continued

Year 11 12 13 14 15 16 17 18 19 20 211950 0 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 0 01967 9 7 3 1 1 1 0 28 28 28 1401968 18 15 6 3 1 1 1 58 58 58 2911969 27 23 9 4 2 2 1 89 89 89 4431970 37 32 12 5 3 3 1 121 121 121 6041971 45 38 14 6 3 3 2 146 146 146 7301972 64 55 21 9 5 5 2 210 210 210 1,0511973 103 88 33 15 7 7 4 336 336 336 1,6801974 140 120 45 20 10 10 5 456 456 456 2,2801975 156 134 50 22 11 11 6 509 509 509 2,5471976 222 191 71 32 16 16 8 725 725 725 3,6241977 246 211 79 35 18 18 9 801 801 801 4,0041978 247 212 79 35 18 18 9 806 806 806 4,0291979 289 248 93 41 21 21 10 942 942 942 4,7101980 398 341 128 57 28 28 14 1,297 1,297 1,297 6,4851981 382 327 123 55 27 27 14 1,245 1,245 1,245 6,2241982 319 273 102 46 23 23 11 1,039 1,039 1,039 5,1931983 342 293 110 49 24 24 12 1,113 1,113 1,113 5,5671984 409 351 131 58 29 29 15 1,333 1,333 1,333 6,6651985 488 418 157 70 35 35 17 1,590 1,590 1,590 7,9491986 534 457 172 76 38 38 19 1,740 1,740 1,740 8,6991987 474 407 152 68 34 34 17 1,546 1,546 1,546 7,7321988 392 336 126 56 28 28 14 1,278 1,278 1,278 6,3891989 358 307 115 51 26 26 13 1,168 1,168 1,168 5,8401990 103 89 33 15 7 7 4 337 337 337 1,6841991 122 105 39 17 9 9 4 399 399 399 1,9951992 35 30 11 5 2 2 1 114 114 114 5681993 69 59 22 10 5 5 2 224 224 224 1,1221994 24 21 8 3 2 2 1 79 79 79 3951995 64 55 21 9 5 5 2 209 209 209 1,0451996 98 84 31 14 7 7 3 319 319 319 1,5951997 152 130 49 22 11 11 5 495 495 495 2,4741998 221 190 71 32 16 16 8 721 721 721 3,6041999 211 181 68 30 15 15 8 689 689 689 3,4452000 188 161 61 27 13 13 7 614 614 614 3,0692001 221 190 71 32 16 16 8 722 722 722 3,6102002 260 223 84 37 19 19 9 848 848 848 4,2402003 169 145 54 24 12 12 6 551 551 551 2,7532004 136 117 44 19 10 10 5 444 444 444 2,2202005 77 66 25 11 5 5 3 250 250 250 1,2482006 25 22 8 4 2 2 1 82 82 82 4092007 59 50 19 8 4 4 2 191 191 191 9552008 6 5 2 1 0 0 0 18 18 18 922009 8 7 2 1 1 1 0 25 25 25 1242010 9 8 3 1 1 1 0 30 30 30 149

11: Synodontidae; 12: Nemipterus spp., 13: Haemulidae; 14: Ariidae; 15: Carangidae; 16: Sphyraenidae; 17: Sepiidae; 18: Portunus pelagicus; 19: Soleidae; 20: Tetraodontidae; 21: Others

150Table B11: The composition of the total catch of Yemen in its Gulf of Aden EEZ from 1950 to 2010.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 141950 13,228 1,718 0 8,885 3,869 2,707 2,007 0 1,004 1,106 247 0 0 01951 13,228 1,718 0 8,885 3,869 2,707 2,007 0 1,004 1,106 247 0 0 01952 15,503 2,013 0 10,413 4,534 3,173 2,352 0 1,176 1,297 290 0 0 01953 15,873 2,061 0 10,662 4,643 3,249 2,408 0 1,205 1,328 297 0 0 01954 15,873 2,061 0 10,662 4,643 3,249 2,408 0 1,205 1,328 297 0 0 01955 18,413 2,391 0 12,368 5,385 3,768 2,793 0 1,397 1,540 344 0 0 01956 11,535 1,498 0 7,748 3,374 2,361 1,750 0 875 965 216 0 0 01957 11,958 1,553 0 8,032 3,497 2,447 1,814 0 907 1,000 223 0 0 01958 11,376 1,477 0 7,641 3,327 2,328 1,726 0 863 951 213 0 0 01959 12,910 1,677 0 8,672 3,776 2,642 1,959 0 980 1,080 241 0 0 01960 11,799 1,532 0 7,926 3,451 2,415 1,790 0 895 987 220 0 0 01961 11,640 1,512 0 7,819 3,405 2,382 1,766 0 883 974 218 0 0 01962 11,640 1,512 0 7,819 3,405 2,382 1,766 0 883 974 218 0 0 01963 11,640 1,512 0 7,819 3,405 2,382 1,766 0 883 974 218 0 0 01964 13,228 1,718 0 8,885 3,869 2,707 2,007 0 1,004 1,106 247 0 0 01965 13,228 1,718 0 8,885 3,869 2,707 2,007 0 1,004 1,106 247 0 0 01966 13,228 1,718 0 8,885 3,869 2,707 2,007 0 1,004 1,106 247 0 0 01967 13,943 1,809 867 9,356 4,074 2,910 2,113 215 1,057 1,165 260 114 111 981968 13,570 1,759 1,807 9,096 3,961 2,896 2,054 447 1,028 1,133 253 237 231 2041969 13,198 1,708 2,748 8,836 3,847 2,881 1,995 680 998 1,100 246 360 351 3101970 13,016 1,683 3,743 8,702 3,789 2,909 1,965 926 983 1,084 242 490 479 4231971 12,177 1,572 4,525 8,130 3,540 2,789 1,836 1,120 919 1,012 226 593 579 5111972 14,139 1,823 6,517 9,427 4,105 3,321 2,129 1,613 1,065 1,174 262 854 833 7361973 18,734 2,411 10,415 12,471 5,430 4,517 2,817 2,578 1,409 1,553 347 1,365 1,332 1,1761974 21,516 2,765 14,139 14,299 6,226 5,331 3,229 3,499 1,615 1,781 398 1,853 1,808 1,5961975 19,073 2,444 15,794 12,640 5,504 4,940 2,855 3,909 1,428 1,574 352 2,070 2,019 1,7831976 23,518 3,007 22,469 15,554 6,773 6,287 3,513 5,561 1,757 1,937 433 2,944 2,873 2,5371977 22,726 2,900 24,826 14,997 6,530 6,280 3,387 6,145 1,694 1,867 417 3,253 3,174 2,8031978 20,144 2,564 24,982 13,260 5,774 5,762 2,995 6,183 1,498 1,651 369 3,274 3,194 2,8211979 20,857 2,648 29,200 13,694 5,963 6,185 3,093 7,227 1,547 1,705 381 3,826 3,733 3,2971980 25,547 3,234 40,207 16,725 7,282 7,866 3,777 9,952 1,889 2,083 465 5,269 5,141 4,5391981 21,868 2,759 38,589 14,271 6,214 7,007 3,223 9,551 1,612 1,777 397 5,057 4,934 4,3571982 16,335 2,054 32,197 10,624 4,626 5,456 2,399 7,969 1,200 1,323 296 4,219 4,117 3,6351983 15,708 1,968 34,515 10,177 4,432 5,479 2,299 8,543 1,150 1,267 283 4,523 4,413 3,8971984 16,921 2,111 41,323 10,919 4,754 6,174 2,466 10,228 1,234 1,360 304 5,415 5,283 4,6661985 18,131 2,252 49,286 11,645 5,071 6,944 2,630 12,199 1,316 1,450 324 6,458 6,301 5,5651986 3,040 2,762 53,932 13,432 7,399 7,761 3,034 13,474 3,057 2,842 314 7,132 6,961 6,0891987 25,036 957 47,936 10,844 4,881 2,724 1,797 12,469 982 981 185 6,595 6,443 5,4121988 22,867 3,335 39,613 11,648 6,985 2,955 2,780 10,173 406 740 367 5,382 5,256 4,4721989 22,448 2,637 36,208 12,986 0 5,957 3,909 8,936 1,189 1,780 596 4,731 4,616 4,0881990 30,425 5,526 10,442 16,587 594 4,508 5,027 1,972 1,791 2,406 991 1,050 1,017 1,1791991 29,961 7,061 12,370 15,116 1,100 2,068 4,613 2,868 1,889 2,317 1,120 1,520 1,481 1,3971992 28,094 8,011 3,519 13,238 1,466 1,450 4,069 488 1,885 2,142 1,175 262 251 3971993 25,356 8,306 6,959 11,113 1,666 1,927 3,441 1,357 1,783 1,895 1,155 722 700 7861994 24,951 9,166 2,449 10,252 1,951 95 3,198 498 1,835 1,840 1,226 265 257 2771995 34,356 13,801 6,480 13,213 3,062 713 4,152 1,267 2,616 2,494 1,792 674 654 7321996 34,412 14,891 9,892 12,409 3,407 1,612 3,930 1,860 2,701 2,461 1,889 990 959 1,1171997 38,730 17,849 15,336 13,117 4,182 3,226 4,187 2,769 3,122 2,731 2,221 1,476 1,428 1,7311998 43,469 21,144 22,343 13,846 5,049 5,703 4,456 3,872 3,587 3,024 2,590 2,066 1,995 2,5231999 46,274 23,655 21,360 13,920 5,737 5,826 4,518 3,788 3,910 3,188 2,860 2,020 1,952 2,4122000 46,383 24,776 19,029 13,194 6,086 5,573 4,319 3,452 4,004 3,166 2,962 1,840 1,780 2,1482001 62,218 34,562 22,380 16,754 8,582 7,091 5,534 4,153 5,477 4,211 4,091 2,212 2,141 2,5272002 84,671 48,716 26,289 21,606 12,209 9,009 7,201 4,878 7,588 5,685 5,718 2,599 2,515 2,9682003 119,545 71,121 17,071 29,000 17,966 16,336 9,756 1,527 10,910 7,983 8,286 835 781 1,9272004 135,667 83,047 13,765 31,251 21,125 16,295 10,613 1,509 12,567 8,996 9,612 817 774 1,5542005 127,420 80,054 7,735 27,892 20,488 13,650 9,566 1,013 11,968 8,394 9,212 545 521 8732006 126,722 81,538 2,538 26,380 20,981 12,400 9,139 390 12,056 8,296 9,333 209 201 2872007 95,552 56,014 5,919 18,864 15,618 8,274 9,094 1,123 8,829 4,439 6,923 598 579 6682008 62,576 38,476 572 12,694 10,299 5,277 5,244 98 5,870 3,498 4,573 52 50 652009 83,747 51,493 768 16,988 13,783 7,064 7,018 131 7,856 4,681 6,121 70 68 872010 100,394 61,729 922 20,365 16,523 8,468 8,413 158 9,417 5,612 7,337 84 81 1041: Clupeidae; 2: Thunnus albacares; 3: Leiognathidae; 4: Carcharhinidae; 5: Sardinella logiceps; 6: Sepiidae; 7: Euthynnus affinis; 8: Ariidae; 9: Rastrelliger kanagurta; 10: Scomberomorus commerson; 11: Thunnus tonggol; 12: Haemulidae; 13: Chrysoblephus spp.; 14: Terapon spp.

Yemen - Tesfamichael et al. 151B11 continuedYear 15 16 17 18 19 20 21 22 23 24 25 26 27 281950 0 607 0 0 0 238 0 0 0 0 0 0 0 01951 0 607 0 0 0 238 0 0 0 0 0 0 0 01952 0 712 0 0 0 279 0 0 0 0 0 0 0 01953 0 729 0 0 0 286 0 0 0 0 0 0 0 01954 0 729 0 0 0 286 0 0 0 0 0 0 0 01955 0 845 0 0 0 332 0 0 0 0 0 0 0 01956 0 530 0 0 0 208 0 0 0 0 0 0 0 01957 0 549 0 0 0 215 0 0 0 0 0 0 0 01958 0 522 0 0 0 205 0 0 0 0 0 0 0 01959 0 593 0 0 0 232 0 0 0 0 0 0 0 01960 0 542 0 0 0 212 0 0 0 0 0 0 0 01961 0 534 0 0 0 210 0 0 0 0 0 0 0 01962 0 534 0 0 0 210 0 0 0 0 0 0 0 01963 0 534 0 0 0 210 0 0 0 0 0 0 0 01964 0 607 0 0 0 238 0 0 0 0 0 0 0 01965 0 607 0 0 0 238 0 0 0 0 0 0 0 01966 0 607 0 0 0 238 0 0 0 0 0 0 0 01967 92 649 56 56 38 251 28 28 28 28 28 0 14 141968 192 641 117 117 80 244 58 58 58 58 58 0 29 291969 292 633 177 177 122 237 89 89 89 89 89 0 44 441970 398 635 241 241 166 233 121 121 121 121 121 0 60 601971 481 604 292 292 201 218 146 146 146 146 146 0 73 731972 693 715 420 420 289 253 210 210 210 210 210 0 105 1051973 1,107 965 672 672 462 334 336 336 336 336 336 0 168 1681974 1,503 1,130 912 912 627 383 456 456 456 456 456 0 228 2281975 1,679 1,034 1,019 1,019 701 339 509 509 509 509 509 0 255 2551976 2,389 1,305 1,450 1,450 997 417 725 725 725 725 725 0 362 3621977 2,639 1,292 1,602 1,602 1,101 402 801 801 801 801 801 0 400 4001978 2,656 1,175 1,612 1,612 1,108 355 806 806 806 806 806 0 403 4031979 3,105 1,251 1,884 1,884 1,295 367 942 942 942 942 942 0 471 4711980 4,275 1,576 2,594 2,594 1,783 448 1,297 1,297 1,297 1,297 1,297 0 648 6481981 4,103 1,391 2,490 2,490 1,712 383 1,245 1,245 1,245 1,245 1,245 0 622 6221982 3,423 1,073 2,077 2,077 1,428 285 1,039 1,039 1,039 1,039 1,039 0 519 5191983 3,670 1,068 2,227 2,227 1,531 273 1,113 1,113 1,113 1,113 1,113 0 557 5571984 4,393 1,192 2,666 2,666 1,833 293 1,333 1,333 1,333 1,333 1,333 0 667 6671985 5,240 1,327 3,180 3,180 2,186 312 1,590 1,590 1,590 1,590 1,590 0 795 7951986 5,788 1,613 3,479 3,479 2,414 108 1,740 1,740 1,740 1,740 1,740 0 870 8701987 5,357 1,556 3,093 3,093 2,233 96 1,546 1,546 1,546 1,546 1,546 0 773 7731988 4,371 1,321 2,556 2,556 1,822 506 1,278 1,278 1,278 1,278 1,278 52 639 6391989 3,838 1,450 2,336 2,336 1,601 761 1,168 1,168 1,168 1,168 1,168 1,807 584 5841990 846 1,877 674 674 355 965 337 337 337 337 337 1,623 168 1681991 1,231 1,689 798 798 514 873 399 399 399 399 399 1,710 200 2001992 209 2,001 227 227 88 758 114 114 114 114 114 1,584 57 571993 582 1,702 449 449 244 631 224 224 224 224 224 1,662 112 1121994 214 1,127 158 158 89 577 79 79 79 79 79 1,528 40 401995 544 1,664 418 418 228 737 209 209 209 209 209 1,188 105 1051996 797 1,540 638 638 334 686 319 319 319 319 319 856 160 1601997 1,187 1,289 989 989 498 718 495 495 495 495 495 882 247 2471998 1,659 563 1,442 1,442 697 750 721 721 721 721 721 807 360 3601999 1,624 555 1,378 1,378 682 746 689 689 689 689 689 779 345 3452000 1,480 503 1,228 1,228 621 700 614 614 614 614 614 688 307 3072001 1,780 590 1,444 1,444 747 878 722 722 722 722 722 625 361 3612002 2,091 553 1,696 1,696 877 1,118 848 848 848 848 848 593 424 4242003 649 721 1,101 1,101 279 1,482 551 551 551 551 551 560 275 2752004 643 584 888 888 274 1,576 444 444 444 444 444 509 222 2222005 433 369 499 499 183 1,386 250 250 250 250 250 507 125 1252006 167 230 164 164 70 1,292 82 82 82 82 82 252 41 412007 482 110 382 382 202 962 191 191 191 191 191 246 95 952008 42 88 37 37 18 634 18 18 18 18 18 138 9 92009 56 117 50 50 24 849 25 25 25 25 25 150 12 122010 68 141 60 60 28 1,017 30 30 30 30 30 156 15 15

15: Trachurus spp.; 16: Panulirus homarus; 17: Gerreidae; 18: Trichiuridae; 19: Carangidae; 20: Istiophorus platypterus; 21: Parastromateus niger; 22: Platycephalidae; 23: Portunus pelagicus; 24: Soleidae; 25: Tetraodontidae; 26: Scomberomorus guttatus; 27: Mullidae; 28: Stomatopoda

152B11 continuedYear 29 30 31 32 33 34 35 36 37 38 39 40 41 421950 111 0 0 0 56 0 0 0 6 0 0 0 0 3,9771951 111 0 0 0 56 0 0 0 6 0 0 0 0 3,9771952 130 0 0 0 66 0 0 0 7 0 0 0 0 4,6611953 133 0 0 0 67 0 0 0 7 0 0 0 0 4,7721954 133 0 0 0 67 0 0 0 7 0 0 0 0 4,7721955 154 0 0 0 78 0 0 0 8 0 0 0 0 5,5351956 97 0 0 0 49 0 0 0 5 0 0 0 0 3,4681957 100 0 0 0 51 0 0 0 5 0 0 0 0 3,5951958 95 0 0 0 48 0 0 0 5 0 0 0 0 3,4201959 108 0 0 0 55 0 0 0 6 0 0 0 0 3,8811960 99 0 0 0 50 0 0 0 5 0 0 0 0 3,5471961 97 0 0 0 49 0 0 0 5 0 0 0 0 3,4991962 97 0 0 0 49 0 0 0 5 0 0 0 0 3,4991963 97 0 0 0 49 0 0 0 5 0 0 0 0 3,4991964 111 0 0 0 56 0 0 0 6 0 0 0 0 3,9771965 111 0 0 0 56 0 0 0 6 0 0 0 0 3,9771966 111 0 0 0 56 0 0 0 6 0 0 0 0 3,9771967 117 9 9 7 59 0 0 0 6 1 0 0 0 4,3981968 113 19 18 15 58 0 0 0 6 1 0 0 0 4,5091969 110 29 27 23 56 0 0 0 6 2 0 0 0 4,6211970 108 40 37 32 55 0 0 0 6 3 0 0 0 4,8021971 101 48 45 38 51 0 0 0 5 3 0 0 0 4,7361972 117 69 64 55 60 0 0 0 6 5 0 0 0 5,8001973 155 110 103 88 79 0 0 0 8 7 0 0 0 8,1071974 178 150 140 120 90 0 0 0 9 10 0 0 0 9,8291975 157 167 156 134 80 0 0 0 8 11 0 0 0 9,4881976 194 238 222 191 98 0 0 0 10 16 0 0 0 12,4101977 187 263 246 211 95 0 0 0 10 18 0 0 0 12,7331978 165 265 247 212 84 0 0 0 8 18 0 0 0 11,9931979 171 310 289 248 87 0 0 0 9 21 0 0 0 13,2101980 208 426 398 341 106 0 0 0 11 28 20 0 0 17,2391981 178 409 382 327 90 0 0 0 9 27 89 0 0 15,7561982 132 341 319 273 67 0 0 0 7 23 71 0 0 12,5711983 127 366 342 293 64 0 0 0 7 24 76 0 0 12,9341984 136 438 409 351 69 0 0 0 7 29 14 0 0 14,9101985 145 523 488 418 74 0 0 0 7 35 44 0 0 17,1701986 142 572 534 457 101 0 0 0 19 38 91 0 0 17,6221987 186 508 474 407 67 0 0 0 5 34 0 0 0 16,8811988 158 420 392 336 46 0 0 0 5 28 0 0 0 15,3131989 83 384 358 307 107 0 0 0 2 26 0 0 0 14,5781990 118 111 103 89 140 0 0 0 3 7 0 0 0 10,3061991 119 131 122 105 129 0 0 0 4 9 0 0 0 10,5631992 115 37 35 30 115 0 0 0 4 2 0 0 0 8,0491993 105 74 69 59 99 0 0 0 4 5 0 0 0 8,2671994 106 26 24 21 93 0 0 0 4 2 0 0 0 6,9751995 147 69 64 55 122 103 3 0 6 5 0 2 0 10,3121996 149 105 98 84 117 313 10 0 6 7 0 5 0 11,1641997 170 163 152 130 126 721 24 0 7 11 0 11 0 13,6221998 192 237 221 190 135 1,386 45 0 9 16 0 21 0 16,5571999 207 226 211 181 139 888 94 1 9 15 0 13 0 17,1032000 210 202 188 161 134 398 130 1 10 13 0 6 0 16,6252001 284 237 221 190 174 0 208 43 14 16 0 0 0 21,5962002 389 279 260 223 229 0 244 56 19 19 0 0 0 28,4612003 555 181 169 145 314 0 99 88 27 12 0 0 1 35,9152004 634 146 136 117 346 0 55 89 32 10 0 0 1 39,6332005 600 82 77 66 315 0 16 76 30 5 0 0 0 36,1892006 600 27 25 22 305 0 0 71 31 2 0 0 0 28,0242007 447 63 59 50 227 0 0 53 23 4 0 0 0 25,7762008 295 6 6 5 150 0 0 35 15 0 0 0 0 14,9012009 394 8 8 7 200 0 0 47 20 1 0 0 0 19,9772010 473 10 9 8 240 0 0 56 24 1 0 0 0 23,972

29: Auxis thazard thazard; 30: Carangoides malabaricus; 31: Synodontidae; 32: Nemipterus spp.; 33: Katswonus pelamis; 34: Teuthida; 35: Penaeidae; 36: Octopus spp.; 37: Psettodes erumei; 38: Sphyraenidae; 39: Xiphias gladius; 40: Palinuridae; 41: Brachyura; 42: Others

Saudi Arabia - Tesfamichael and Rossing 153

reConstruCting red sea fisheries CatChes of saudi arabia: national wealth and fisheries transformation1

Dawit Tesfamichaela,b and Peter Rossinga

a Sea Around Us, Fisheries Centre, University of British Columbia 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada

b Department of Marine Sciences, University of Asmara, Asmara, Eritread.tesfamichael @fisheries.ubc.ca; p.rossing @fisheries.ubc.ca

abstraCt

Saudi Arabia is the largest country in the Arabian Peninsula with access to both the Persian Gulf and the Red Sea, of which it represents most of the east coast. Despite the Saudi Arabian coastline in the Red Sea being three times longer than its Gulf coast, Saudi catches from both coasts are very comparable. The catch of Saudi Arabian fisheries in the Red Sea was reconstructed from 1950 to 2010. Catch reports were searched to be used as base information for the reconstruction and for the years information was missing, they were used as anchors for estimation. The reconstruction was conducted separately for each fishery sector: artisanal, subsistence, industrial and recreational. The total catch of each sector was further divided into its taxonomic composition. The catch was low at the beginning of 1950s (7,000 t·year-1). The major change in total Saudi Arabian catch occurred at the beginning of the 1980s, with the massive motorization of artisanal boats and the beginning of industrial fisheries. The peak of the total catch happened in the mid-1990s (about 50,000 t) and after which it decreased slightly to about 40,000 t at the end of 2000s. Artisanal fishery had the highest contribution to the total catch (64%), followed by industrial (23%), subsistence (10%) and recreational fisheries (3%). Although a large number of taxa were identified in the catch, few groups were dominant. The reconstructed catches were compared with the data Saudi Arabia reported to the Food and Agriculture Organization of the United Nations (FAO). The reconstructed catch was 1.5 times the Saudi catch in the FAO data from 1950 to 2010. The major differences appear following the mid-1980s, because of the industrial fishery, which then became very active and whose substantial discards remain unreported. The procedures and assumptions used here are clearly stated, because they may be useful for further research on specific aspects of the fishery, and to improve the catch time series presented herein.

introduCtion

Saudi Arabia occupies 80% of the Arabian Peninsula, and has coastlines on both the Red Sea (in the southwest) and the Persian Gulf (also known as Arabian Gulf in the northeast), with the former more than three times as long as the latter. Consequently, people in the coastal areas of the lands now comprising Saudi Arabia have been fishing in both seas since ancient times. In fact, in the past, almost all coastal communities derived their entire livelihood from fishing (Neve and Al-Aiidy 1973). However, the development of fishing was uneven, with the Red Sea providing only about half of the Saudi Arabian catch despite being about three times longer.

The aquaculture sector, both freshwater and marine, has grown from 2,696 t in 1995 to 14,376 t in 2005; during that period the growth was higher for mariculture from 158 t to 11,259 t (MAW 1996, 2006).2 The freshwater sector emphasizes on tilapia farming, while the mariculture is mainly for shrimp. The total aquaculture output is still growing and the amount for 2009 was about 26,000 t (Tim Huntington, pers. comm.). The rapid increase in aquaculture is in line with a government policy to supply the rapidly growing population with fish, given the stagnating yields of the capture fisheries (FAO 2003; see also below).

Saudi Arabia has the largest shelf in the Red Sea, about 70,000 km2. This shelf is narrow in the north, about 40 km, but broadens in the south (Figure 1). In the 1 Cite as: Tesfamichael, D. and Rossing, P. (2012) Reconstructing Red Sea fisheries catches of Saudi Arabia: National wealth and fisheries transformation. pp. 153-178. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosystem by countries (1950-2010). Fisheries Centre Research Reports 20(1). Fisheries Centre, University of British Columbia [ISSN 1198-6727].2 The fishery statistics publications by the Saudi government do not have the year of publication. We have assigned them the next year of the latest data presented in the reports, e.g., data for 2005 would be published in 2006.

Figure 1. Map of the coast of Saudi Arabia in the Red Sea, shelf area and Exclusive Economic Zone (EEZ).

154

past, most of the landings came from the productive southern grounds, particularly those adjacent to the Farasan Banks (Barrania et al. 1980; Sanders and Morgan 1989). Recently, about half of the catch comes from the southern part and the rest from the central and northern part (MAW 2006). Because the Saudi Arabian coast in the Red Sea has a narrow shelf and deep water is close to shore, nutrients are rapidly lost and hence pelagic fish landings are low. The Farasan Islands (not Farasan Banks) are probably the most productive grounds in the Saudi Arabian Red Sea because of the considerable run-off. In addition, the southern part (South of Jeddah) has well developed mangroves that serve as nursery areas for many reef-associated fish (Price et al. 1987).

The inner shelf is characterized by shallow fringing reefs, which run for few meters to more than half a kilometer. The reefs are interrupted at the mouths of valleys or wadi beds, which created natural deep water harbors (Neve and Al-Aiidy 1973). The reefs are more developed in the north, while in the south the water is more turbid due to run offs from the mountainous areas and influx of nutrient rich water from the Indian Ocean through the narrow strait of Bab-al-Mandeb. There are well-developed off-shore reef systems around Al Wajh, Yanbu and Farasan Islands (Bruckner et al. 2011). Beyond the narrow shelf, depth increases abruptly. The coastal area is hot and dry, with air temperatures reaching more than 45oC in the hot season. There are as many as 88 settlements along the coast where fish are landed, of which some of the largest are Yanbu, Jeddah and Gizan in the northern, central and southern part of the coast, respectively. In the past, most of the supplies for fishing such as ice-making machines, engines, spare parts, gears, services, workshops were found only in the major settlements (Neve and Al-Aiidy 1973). The fishery in the Red Sea was overwhelmingly artisanal and it used mainly small boats, which started to be motorized at the end of the 1950s. By the beginning of 1990s, all the boats were motorized. The industrial fishery, experimental at first, took off at the beginning of the 1980s (Ferrer 1958; Sanders and Morgan 1989). However, due to narrow shelf area and reefs, there are no large trawlable areas to support a large number of trawlers.

The population density on the Red Sea coast of Saudi Arabia has traditionally been low, due to the dry and hot climate. The economy was based on agriculture, fishing (including pearling), nomadic herding, commerce, and since the ascent of Islam, catering to pilgrims to and from Mecca. The discovery (in 1949) and the exploitation of petroleum in Saudi Arabia profoundly modified the economy, with oil accounting for over 85% of government’s revenue in the early 1970s (Neve and Al-Aiidy 1973), reducing the traditional sectors to insignificance; thus, in 1998, fisheries accounted for only 0.3% of GDP (Sakurai 1998). Easy access to air conditioners allowed major population centers to grow along the hot coast. The oil wealth also changed the demography of fisheries in that foreign fish workers, both on boats and in processing, mostly from India and Bangladesh, increased significantly starting in the mid-1980s and account for more than 60% of the fishers (Sakurai 1998). Most of the local people prefer the meat of land animals (goat, mutton, beef, chicken and camel) over seafood. On the other hand, the rather large expatriate community has a high seafood consumption, and thus Saudi Arabia imported 58,300 t, half of its seafood supply, in 1996 (Sakurai 1998) and 112,683 t, about two third of total supply, in 2003 (FAO 2003). Saudi Arabia exported a small amount of seafood, about 2,000 t in the 1990s and early 2000s, of which shrimp accounts for about 20%.

The administration of fisheries was placed under the Animal Husbandry Department of the Ministry of Agriculture and Water up to 1990. In 1991, recognizing the importance of fishery in national food security policy, the government created a Deputy Minister for Fisheries Affairs under the Ministry of Agriculture and Water, tasked to manage the fishery resources of the country. The deputy minister, in 1993, created three departments each with specific responsibilities: Marine Fisheries Department, Aquaculture Department and Marine Protection Department (Sakurai 1998; FAO 2003).

In this contribution, the Saudi Arabian fishery catches in its Red Sea exclusive economic zone (EEZ) are reconstructed from 1950 to 2010, i.e., an attempt is made to account for all catches of all fisheries (including recreational fisheries, the discards of industrial trawlers and other catches usually ignored in official fisheries statistics (see e.g., Zeller et al. 2011). The fisheries are reviewed and the catch standardized by the major fishery sectors in order to establish a long time series data. The fishery is divided into four sectors: artisanal, subsistence, industrial and recreational. The catches are further disaggregated into taxonomic groups. For each sector, general introduction is given, followed by a detailed description of the catch reconstruction methodology, and results and conclusions at the end.

Artisanal fishery

The artisanal fishery, sometimes referred to as ‘traditional’ fishery in Saudi Arabia as elsewhere, is conducted from small boats, ranging from 5 to 20 m, and simple gears with no sophisticated technologies such as winch, fish finder, electronic navigation or communication equipment (MAW 2000). Most of the boats are small 6 – 9 m, and only about 10% are bigger than 9 m. In the past, traditional boats were exclusively made of wood (locally called sambuks and houris), and used to have sails (El-Saby and Farina 1954). The fishery was not highly developed, but the economy of coastal communities depended heavily on fishing (Tesfamichael and Pitcher 2006). Part of their catch was for local consumption, and part was dried or salted to be sold or bartered in exchange for other necessities (El-Saby and Farina 1954). Dried and salted fish were the only fish product to be available inland (Neve and Al-Aiidy 1973). Fishers were part time, and often would work from September to January in the agriculture sector (Gilberg 1966). Fishing was done only during the day, because it was difficult to navigate the coral reefs at night. Small boats performed day trips, but larger boats performed trips of up to 7 days (Kedidi et al. 1984); in some exceptional cases, even trips of up to 14 days occurred (Neve and Al-Aiidy 1973). Except for a few large boats, ice was not carried onboard, and fish were sold fresh bundled in strings (Barrania et al. 1980). Crew size ranged 1 to 4 per boat (Kedidi et al. 1984). The artisanal fishery changed with the advent of oil wealth: in 1983, fiberglass boats were introduced (Sanders and Morgan 1989) and by the mid-1990s, they accounted for about 80%, with the majority having outboard engines (Sakurai 1998). Motorization of boats started at the end of 1950s (Ferrer 1958) and was

Saudi Arabia - Tesfamichael and Rossing 155

completed by the beginning of 1990s (Sakurai 1998). The number of boats also increased in the artisanal fishery of Saudi Arabia. The dominant fishing gears are gillnet, and hook and line, which account for more than 90% of the artisanal catch, while trolling and trap are rarely used (MAW 2000). Handlining is dominant in the northern coast, targeting coral reef fishes, while gillnets are used in the southern coast, targeting pelagic fishes. Fishing licenses for the traditional fishery are issued by representatives of the Fisheries Out-Stations at the district level (MAW 2000). According to the fishery administration, traditional fishers are Saudi citizens who work on board one of their own traditional fishing boat; however, a traditional fisher can own up to 4 fishing boats (MAW 2000). Since the 1980s, most Saudi fishers are not directly involved in fishing, sometimes referred as ‘investor fishers’. They own the boats, but the fishing is done by foreign workers through an arrangement where the owner gets half of the profit and the crew shares the other half. To limit effort (because catches are not increasing anymore), the issuing of new licenses has stopped in the mid-1990s (Sakurai 1998).

Subsistence fishery

The majority of the subsistence catch includes what the fishers consume and give to their families and friends to sustain their communities. These catches are not reported at all because the catch is given away before the official recording, if it exists. In the coastal areas, community members, mainly children, are also involved in catching fish for consumption by the family. For cultural and religious reasons, women are not involved in fishing in Saudi Arabia. The subsistence fishery catch can be significant. Based on interview with fishers in the Red Sea, it can amount up to half of the total catch. The catch amounts given freely have changed over time: in the past where the fishery was less commercialized, they were relatively high, but they diminished later.

Industrial fishery

The history of Saudi Arabian industrial fishery in Red Sea is tied to the history of the Saudi Fishing Company. Experimental fishing by chartered boats, mainly trawling for shrimps, started in 1952 (Ferrer 1958). The Saudi Fishing Company did not have its own boats until 1954, and it became inactive in 1961, due to engine failures, lack of maintenance and lack of profits (Gilberg 1966). The company re-established itself again in 1981, when shrimp trawling started with Thai vessels operating under contract (Sanders and Morgan 1989). Eventually, the Saudi Fishing Company grew, and owned and operated its own vessels. Currently, the company leased its operations to other companies. Its main base in the Red Sea is Gizan, in the south, close to the border with Yemen, and its main fishing grounds are located off the Farasan Islands, and near Al-Qunfotha and Al-Khoriebah. Some industrial fishing vessels operate outside the Saudi territorial waters in the neighboring countries or international waters (Sakurai 1998). Although the industrial fishery is mainly trawling (hence sometimes referred as trawl fishery), the vessels are also involved in purse seining, as well (MAW 2000). The issuance of fishing license for industrial fishing is a sole prerogative of the Minister of Agriculture and Water or the Deputy Minister for Fisheries Affairs in the same ministry (MAW 2000).

Recreational fishery

Recreational fishing was not commonly practiced in Saudi Arabia. However, once the country acquired oil wealth, and saw numerous expatriates practice the sport, recreational fishery or ‘pleasure fishing’, as it is called locally, took off. In the mid to late 1990s, there were 2,126 to 2,445 boats registered as ‘recreational’ (Sakurai 1998; MAW 2000). Most of the fishing happens on the weekend (Thursday and Friday), using handline. There are rare reports of trolling and longline fishing (MAW 2000). Recreational fishing with net is prohibited (Sakurai 1998).

methods

Artisanal fishery

The earliest catch estimate for Saudi Arabia’s artisanal fisheries in the Red Sea was from a partial survey of the fishers from which the average catch was calculated and multiplied by the total number of fishers in order to estimate the total catch for 1953, which was 3,000 to 5,000 t (El-Saby and Farina 1954). The mid-range value 4,000 t was taken. The same amount was assumed from 1950 to 1952. After 1952, the next estimate was for 1963, from a survey which led to a total catch estimate of 5,000 t (Gilberg 1966). From 1965 to

Table 1. Sources used to adjust Saudi Arabian Red Sea catches (tonnes) reported by Sanders and Morgan (1989).

Year

Reported catch Adjusted catchSanders and Morgan (1989) Others Source

1976 11,500 10,200 Peacock (1978) -1977 11,700 10,200 Peacock (1978) -1978 13,300 12,900 Barrania et al. (1980) -1979 13,100 - - 11,3281980 13,200 10,350 Barrania et al. (1980) -1981 13,200 - - 11,4151982 13,200 - - 11,4151983 13,200 10,742 Chakraborty (1984) -1984 13,200 - - 11,4151985 21,800 - - 18,8511986 22,700 - - 19,630

156

1971, total catches were available for the whole of Saudi Arabia, i.e., both the Red Sea and Persian Gulf together, where it is stated that ‘about half’ of the catch came from the Red Sea (Neve and Al-Aiidy 1973). Another report gave a more precise estimate, 53%, (Barrania et al. 1980), which was used to calculate the Red Sea catch. From 1976 to 1986, catches from the Red Sea were estimated by halving the total Saudi Arabian reported catch (Sanders and Morgan 1989). Estimates for the Red Sea only were available for 1976 and 1977 (Peacock 1978), 1978 and 1980 (Barrania et al. 1980) and 1983 (Chakraborty 1984). The data from Sanders and Morgan (1989) were used for years for which there were no other estimates, after adjusting it using weighted mean for the years where there were estimates for the Red Sea only (Table 1). This resulted in that the Red Sea catch was only 86% of that reported by Sanders and Morgan (1989).

Starting 1987, data availability improved, and the following sources were used: 1987-1994 (Sakurai 1998), 1995-1998 (MAW 2000), 2004 to 2007 (MAW 2008) and 2009 (FSDP 2011) . Also, the number of fishers data were available from 1991 to 2007 (MAW 2008), which was used to calculate the catch per fisher from 1991 to 2007. A linear regression was fitted to the data (Figure 2). Using this function, the catch per fisher was calculated for 1999 to 2003, which was multiplied by the number of fishers to estimate the total catch. Interpolation of the total catch was used to fill in the data gaps in 1954 to 1962, 1964, 1972 to 1975, 2008 and 2010 (Table 2).3

Part of the artisanal fishery catch is not reported at all. The major contributions to unreported catch in artisanal fisheries are fish landed outside the major landing sites where data recording occurs, if any. The second contributions to unreported catch occurs when boats land their catch at the major landing sites, but before their catch is recorded, part of the fish is sold in the non-formal market before recording. These catches are different from catch that is allocated for subsistence, which is treated separately below. It was difficult to estimate the unreported catch of artisanal fishery, as we were unable to locate pertinent studies for Saudi Arabia. We used some qualitative information that the first author collected during a field trip to the neighboring Red Sea countries of Sudan, Eritrea and Yemen (Tesfamichael et al. in press). The market and data recording infrastructure improved with the motorization of artisanal boats starting the beginning of 1960s facilitated by the government. This knowledge, jointly with the general pattern of the fishery, was used to estimate the unreported catch. The reconstructed time series reported Saudi artisanal catch can be divided into three phases (Figure 3): low catch level until 1963, a slight increase until 1984, and rapid increase after that, followed by decline. Thus, we assumed conservative unreported catch to be 30 % of the total catch from 1950 to 1963, 20 % from 1964 to 1984 and 10 % from 3 When this report was being published Saudi Arabia published fishery statistics up to 2010. Our estimates are very similar to the official published values.

Table 2. Sources and methods for estimating reported artisanal fishery catch of Saudi Arabia in the Red Sea.Year Source Remarks1950-52 - Assumed the same as 19531953 El-Saby and Farina (1954) Average of reported range1954-62 Interpolation Linear change in total catch1963 Gilberg (1966) -1964 Interpolation Linear change in total catch1965-71 Neve and Al-Aiidy (1973) -1972-75 Interpolation Linear change in total catch1976-77 Peacock ( 1978) -1978 Barrania et al.(1980) -1979 Sanders and Morgan (1989) Adjusted (see Table 1)1980 Barrania et al.(1980) -1981-82 Sanders and Morgan (1989) Adjusted (see Table 1)1983 Chakraborty (1984) -1984-86 Sanders and Morgan (1989) Adjusted (see Table 1)1987-94 Sakurai (1998) -1995-98 MAW (2000) -1999-2003 Interpolation Based on linear function of

catch per fisher (Fig. 2) and total number of fishers

2004-07 MAW (2008) -2008 Interpolation Linear change in total catch2009 FSDP (2011) -2010 Interpolation Linear change in total catch

Figure 3. Reconstructed Saudi Arabian artisanal Red Sea fishery catches. (Note that apparent constancy of ‘unreported catch’ is a reflection of the improvement of data recording system).

Figure 2. A linear function fitted to the catch per fisher in Saudi Arabia’s Red Sea artisanal fishery.

Saudi Arabia - Tesfamichael and Rossing 157

1985 to 2010. In addition, fishers from Jordan fished in Saudi waters from 1950 to 1984 (Tesfamichael et al. 2012). The catches were very small (maximum of 100 t) compared to the Saudi catch (minimum of 5,700 t); nevertheless they were included with the unreported catch.

Catch composition data for Saudi Arabia’s artisanal fishery were available for some years, the earliest being 1980. Data points were often only available for the major target species, reflecting the over-aggregated nature of the reported data. From 1950 to 1998, where the catch composition was highly aggregated, we created a comprehensive catch composition list consisting of 20 major taxa and the category ‘others’ for the species not identified. To fill the species composition matrix for all the years, some aggregated taxonomic groups were disaggregated using data from other years. Indian mackerel and Spanish mackerel (‘kingfish’) were reported as ‘Mackerel’ for the 1980 and 1983 (Barrania et al. 1980; Chakraborty 1984). This category was split based on disaggregated ratio reported for 1985, i.e., kingfish 91% and Indian mackerel 9% (MAW 1986). The same source was used to split parrotfish and surgeonfish, with contribution 98% and 2%, respectively. Tunas were reported separately for most of the years, but not for all years. For 1985, their catch was calculated by splitting the reported ‘others’ using the proportion of tuna relative to ‘others’ for 1983. The catch ratio of tunas for 1995 (MAW 1996) was assumed to be similar to 1996 (MAW 1998; Sakurai 1998). Catch rates for cobia, wrasses, sea breams, rabbitfish, goatfish and cutlassfishes were not available for 1980 and 1983. We estimated their proportions from ‘others’ using ratios reported for 1985 (MAW 1986). The final result is a standardized catch composition (Table 3).

The most detailed (disaggregated) catch composition available was from 2004 to 2007 (MAW 2008). The catch was divided into 40 taxonomic groups and ‘others’ (Table 4). The 40 groups included all the 20 groups from 1950 to 1998 and 20 new ones. The ‘others’ from 1950 to 1998 were further divided to the 20 new groups in 2004-2007 using their average ratios. For the years catch composition was missing altogether, it was estimated by interpolating between the closest years for which catch composition was available. From 1950 to 1979, the catch composition was estimated using the earliest available ratio (1980). From 1986 to 1994, the phase of the Saudi artisanal fishery characterized by high catches (Figure 3), the only catch composition available was for 1985, and it was used for the whole period. Species composition data were also missing for the period 1999 to 2003, the mean of 1996 to 1998 and 2004 to 2007 (i.e., similar phase of the fishery; Figure 3), was used. From 2008 to 2010, the catch composition of 2007 was used. The final catch composition of the artisanal fishery consisted of many taxa but for clarity of presentation of the result only the major taxa are included and the minor taxa are lumped together in the group ‘others’ (Figure 4). The detailed composition is presented in the Appendix Table (A1).

Table 3. Source for catch composition (%) of Saudi Arabian Red Sea artisanal fishery.Year 1950-80 1981-82 1983 1984 1985-94 1995 1996 1997 1998 1999-03 2004 2005 2006 2007-10Spanish Mackerel

21.84 24.70 27.57 28.98 30.40 16.20 16.93 18.49 23.91 15.97 15.93 14.08 11.03 12.43

Jacks 15.00 15.36 15.73 13.86 12.00 10.70 13.52 12.01 11.81 13.30 16.03 15.88 14.02 13.48Groupers 9.00 8.90 8.80 10.90 13.00 10.60 17.91 14.04 15.30 16.02 16.45 17.94 19.71 17.47Emperors 8.00 6.89 5.77 9.84 13.90 12.40 17.49 14.66 12.78 14.88 14.44 15.84 16.75 15.87Snappers 12.00 8.44 4.87 6.44 8.00 4.90 4.91 5.62 5.53 5.27 6.83 4.93 4.89 4.93Barracudas 4.00 5.20 6.41 6.70 7.00 3.90 4.01 4.01 3.99 5.14 5.23 6.73 6.92 6.74Tunas 7.00 6.28 5.55 3.74 1.94 2.46 2.46 2.46 2.45 3.60 4.71 4.58 4.70 5.28Mullets 8.00 6.21 4.42 3.21 2.00 1.90 1.90 1.90 1.89 1.49 1.21 1.11 0.95 1.19Sharks 6.00 6.84 7.67 4.84 2.00 1.80 1.80 1.80 1.79 2.24 2.18 2.69 2.69 3.38Indian Mackerel 2.16 2.44 2.73 2.86 3.00 15.10 2.91 2.91 2.89 4.07 1.01 1.58 3.00 3.47Parrot fishes 4.90 4.12 3.34 2.17 1.00 3.00 2.33 2.33 2.32 2.21 1.89 1.72 2.24 2.05Cutlass fish 1.15 2.63 4.10 3.55 3.00 2.10 2.10 2.10 2.09 1.04 0.00 0.00 0.00 0.00Rabbit fish 0.01 0.02 0.03 0.02 0.02 4.00 3.50 4.53 2.65 2.50 1.51 1.35 1.41 1.25Sea breams 0.01 0.01 0.00 0.02 0.03 1.20 1.20 1.20 1.19 1.08 0.83 0.79 0.98 1.29Surgeon fish 0.10 0.08 0.07 0.04 0.02 0.60 0.60 0.60 0.60 0.91 1.26 1.29 1.28 1.12Grunts 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.54 1.09 0.91 0.97 0.95 1.57Wrasses 0.00 0.01 0.01 0.06 0.10 0.80 0.80 0.80 0.80 0.63 0.59 0.44 0.44 0.41Queenfish 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.98 1.74 0.86 0.44 0.92Cobia 0.00 0.01 0.01 0.06 0.10 0.10 0.10 0.10 0.10 0.26 0.45 0.41 0.31 0.57Goat fish 0.00 0.01 0.01 0.01 0.01 0.20 0.20 0.20 0.20 0.14 0.07 0.11 0.09 0.03Others 0.82 1.86 2.90 2.69 2.48 8.04 5.33 10.23 7.17 7.18 6.75 6.71 7.20 6.56Sources/remarks

Barrania et al. (1980)

a Chakraborty (1984)

b MAW (1986)

MAW (1996)

MAW (1998)

MAW (2000)

MAW (2000)

c MAW (2008)

MAW (2008)

MAW (2008)

MAW (2008)

a Average of 1980 & 1983, b Average of 1983 & 1985, c Average of 1996-1998 & 2004-2007

Figure 4. Catch composition of Saudi Arabia’s artisanal fishery in the Red Sea.

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Subsistence fishery

The amount of the subsistence catch was estimated based on information obtained through interviews with fishers in the Red Sea areas of Yemen, Eritrea and Sudan (Tesfamichael et al. in press). The amounts of fish allocated for subsistence changed over time; in the past: when fishing was mainly for subsistence, catch rates were high, and there was lack of extensive marketing, fishers reported to give about half of their catch. But later, as their catch became more valuable and their catch rates started to decrease; fishers gave less of their catch away. In order to capture the different phases of the fishery, we used the trend of the total reported catch of the artisanal fishery (Figure 3). The Saudi reconstructed reported artisanal catch can be divided into three phases: low catch level until 1963, which is the pre-motorization phase; a slight increase until 1984, and rapid increase after that, followed by decline. We assumed the subsistence fishery to be 30% of the artisanal catch until 1963. This is a conservative estimate, because fishers told us in the years before motorization gained momentum, they used to give up to 50% of their catch away. For 1964, the subsistence percentage was reduced to 20%, and for 2010 only 10%. From 1965 to 2009, the percentages were interpolated. Before these percentages were applied, some taxa not usually given away were eliminated. The taxa included the ones usually targeted for the export market, i.e., shark fished for their fin and many invertebrates such as shrimp, crab and lobster. Traditionally most of these taxa were not consumed locally and their consumption

Table 4. Sources for the expanded catch composition (%) of Saudi Arabian Red Sea artisanal fishery (2004-2010)Taxa 2004 2005 2006 2007 2008-2010Spanish Mackerel 16 14 11 12 12Jacks 16 16 14 13 13Groupers 16 18 20 17 17Emperors 14 16 17 16 16Snappers 7 5 5 5 5Barracudas 5 7 7 7 7Tunas 5 5 5 5 5Mullets 1 1 1 1 1Sharks 2 3 3 3 3Indian Mackerel 1 2 3 3 3Parrot fishes 2 2 2 2 2Cutlass fish 0* 0 0 0 0Rabbit fish 2 1 1 1 1Sea breams 1 1 1 1 1Surgeon fish 1 1 1 1 1Grunts 1 1 1 2 2Wrasses 1 0 0 0 0Queenfish 2 1 0 1 1Cobia 0 0 0 1 1Goat fish 0 0 0 0 0Squirrel fish 1 1 1 0 0Sea catfish 1 1 0 1 1Needle fish 1 1 1 1 1Mojarras 1 1 1 1 1Milkfish 0 0 1 0 0Snubnose chub 0 0 0 0 0Angle fishes 0 0 0 0 0Rainbow runner 0 0 0 0 0Triggerfishes 0 0 0 0 0White pomfret 0 0 0 0 0Marine crabs 0 0 0 0 0Sail fish, marlin 0 0 0 0 0Sardins 1 1 1 1 1Batfish 0 0 0 0 0Fuslier fish 0 0 0 0 0Rays 0 0 0 0 0Flatfishes 0 0 0 0 0Goggle eye 0 0 0 0 0Lizardfishes 0 0 0 0 0Squids and cuttle fishes 0 0 0 0 0Others 3 2 3 2 2Sources MAW (2008) MAW (2008) MAW (2008) MAW (2008) 2007 values* Values presented as zero in tables are higher than zero and used in calculation. But they are very small, hence presented as zero because of rounding off

Saudi Arabia - Tesfamichael and Rossing 159

was introduced by foreigner (mainly European) visitors to the region. Nowadays, they are consumed by the communities mainly in the affluent bigger urban centers, yet still not given freely to family and friends. The local names of most of these taxa are based on European names, rather than Arabic as is the case for most of the fish (Tesfamichael and Awadh 2012). The remaining taxa of the artisanal fishery constitute the composition of the subsistence fishery (Figure 5, Table A2). Thus, to clarify: our definition of subsistence fishery considers only the portion of the catch that is not sold by the artisanal fishers. We ignore classifications, wherein the entire artisanal fishery, especially before motorization was considered a ‘subsistence fishery’.

Industrial fishery

An exploratory trawl fishing conducted for the Saudi Fishing Company in 1952 initiated industrial fishing in the Saudi Arabian waters of the Red Sea (El-Saby and Farina 1954; Ferrer 1958). The company became inactive and closed in 1961 (Gilberg 1966), but re-established itself in 1980 and carried out trial trawling until it started commercial operation in 1982 in the southern part of the Saudi Red Sea coast around Gizan (Sanders and Morgan 1989). The sporadic experimental trawling in the early 1950s, which yielded negligible catches, are not included in this reconstruction. Rather, it starts in 1982, with a first substantial catch, of which 466 t of shrimp and 703 t of fish were retained. The dataset is not continuous after 1982, but catch data were available for some years: 1987 to 1996 (Sakurai 1998), 1997 to 1998 (MAW 2000), 2004 to 2007 (MAW 2008), and 2009 (FSDP 2011) which were used as total reported catch for the respective years (Table 5). For the periods where catch was not reported 1983 to 1986, 1999 to 2003, 2008 and 2010, interpolation was used to fill in the gaps. The interpolation for the earlier period reflects the rapid expansion of the industrial fishery in Saudi Arabian Red Sea (Sanders and Morgan 1989), while the latter period depicts a somewhat stable high catch.

For the years data were available, the sources reported total (both fish and shrimp) catch or usually the commercially lucrative shrimp only. To reconstruct the catch composition, first a continuous shrimp catch was established from 1982 to 2010. Shrimp data were available for 1982 (Sanders and Morgan 1989) and 1987 to 2007 (MAW 2008). The missing data from 1983 to 1986 were interpolated between the 1982 and 1987 data and for 2008 to 2010 the ratio of shrimp to the total catch for 2007 (11%) was applied (see Table A3) for the total reconstructed shrimp data). Then, the shrimp catches were subtracted from the total reconstructed to determine the total catch of fishes, i.e., non-shrimp retained catch. This procedure was used to get the best possible species distribution as available shrimp catches went back to the early 1980s, whereas the retained fish was available only for 1997 and 1998 (MAW 2000) and 2004 to 2007 (MAW 2008). The catch compositions of 1997 and 1998 were highly aggregated in 5 major groups and more than 30% in the category ‘others’. However, the data from 2004 to 2007 were more detailed with 31 groups and ‘others’. The category ‘others’ for 1997 and 1998 was further disaggregated using the average of 2004 to 2007. From 1982 to 1996, the catch composition of 1997 was used, from 1999 to 2003, the average of 1998 and 2004 was used, and for 2008 to 2010 the composition of 2007 was used (Table 6). The shrimp catch was added to the non-shrimp catch to establish the composition of the industrial total catch of Saudi Arabia in the Red Sea (Figure 6, Table A4). Of the shrimp catch, Penaeus semisulcatus accounts for more than 90% (Sakurai 1998).

Unlike the artisanal fishery, where the main source of unreported catch is the catch landed without being recorded, the main source of unreported catch for the industrial fishery of Saudi Arabia is discarding. Data of retained catch were collected using logbook (MAW 2000). Fish thrown overboard (i.e., non-target species or the young of target species) usually have a low market value and are not recorded in the logbook at all. In the Saudi fishery recording system, the catches of industrial fisheries are not separated by gear, i.e., only the total is given, and usually, the same vessels use both trawling and purse seining gears (MAW 2000). Estimating the unreported catch from the total industrial catch would be misleading, because the source of discard is trawling and the proportion of trawl and purse seine catch is not constant. Using the percentage of shrimp and Indian mackerel, the main catch of trawl and purse seine, respectively, from the total catch for the years data were available for both; we found that they have inverse relationship, i.e., when the share of one increases that of the other decreases indicating the relative

Table 5. Sources and methods for estimating the industrial fishery reported catch of Saudi Arabia in the Red Sea.

Year Source Remarks1950-1981 Sanders and Morgan (1989) Catch was negligible1982 Sanders and Morgan (1989)1983-1986 Interpolation Linear change in total catch1987-1998 MAW (2000)1999-2003 Interpolation Linear change in total catch2004-2007 MAW (2008)2008 Interpolation Linear change in total catch2009 FSDP (2011)2010 Interpolation Linear change in total catch

Figure 5. Catch composition of Saudi Arabia’s subsistence fishery catch in the Red Sea.

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share of each gear (Figure 7). Because of its high value shrimp is the main target of trawling, the main factor in discarding fish, and because a wider coverage of shrimp catch data were available; the reconstructed shrimp data were used as a base to estimate the amount of unreported catch. Estimates of retained and discarded catches were available from experimental fishing in 1952/53, where it was found that for 750 kg of retained catch, 1.5 to 2.0 t were discarded (Ferrer 1958). Taking the mid-range, discards were 2.3 times the retained catch or 70% of the total catch. However, these values cannot be used directly as the retained catch (despite the main target being shrimp) contains other species and our base of estimating unreported catch is shrimp. The earliest, which is also the highest, percentage of shrimp in the retained catch was 40% for 1982 (Sanders and Morgan 1989), and is used to calculate the amount of shrimp in the retained catch of the experimental fishing. Using these ratios, the discard was calculated to be 5.8 times the shrimp catch. This is a conservative estimate because shrimp accounting 40% of retained catch is high and for other countries in the Red Sea discard can be more than 6 times the amount of shrimp catch (Tesfamichael and Mohamud 2012).

Table 6. The catch composition (%) of Saudi Arabian Red Sea industrial fishery excluding shrimp.Taxa 1982-97 1998 1999-03 2004 2005 2006 2007 2008-10Indian Mackerel 24 31 38 45 42 41 43 43Scads, Jacks, trevallies 18 13 9 4 6 7 8 8Emperors 9 8 6 4 7 7 6 6cuttlefishes, squids 8 9 10 11 12 9 9 9Barracudas 5 5 4 3 5 4 4 4Catfish 3 3 2 2 2 3 4 4Crabs 4 4 3 3 5 4 3 3Threadfin bream 3 3 2 0 3 5 3 3Lizardfishes 3 3 3 3 2 2 3 3Kingfishes 3 3 3 3 3 2 2 2Queenfishs 2 2 2 1 2 3 2 2Grunts, sweetlips 2 2 2 2 2 3 2 2Mojarras 2 2 3 1 2 3 1 1Snappers 1 1 1 0 1 0 1 1Flatfishes 1 1 1 1 1 1 1 1Ribbonfish 0 0 0 0 0 0 1 0Tunas 1 1 1 2 1 1 1 1Bony fish 0 0 0 0 0 0 1 0Goatfish 1 1 1 0 0 1 1 0Groupers 1 1 1 0 1 0 1 1Shark 1 1 1 0 0 1 1 0Fuslier fish 1 1 1 1 0 1 0 0Cobia 0 0 0 0 0 0 0 0Rabbit fish 0 0 0 0 0 0 0 0Sardins 0 0 0 0 0 0 0 0Rays 0 0 0 0 0 0 0 0Parrotfishes nei 0 0 0 0 0 0 0 0Seabreams 1 1 1 3 1 1 0 1Needle fish 0 0 0 0 0 0 0 0Milkfish 0 0 0 0 0 0 0 0Triggerfishes 0 0 0 0 1 0 0 0Others 4 4 4 10 1 2 2 2Source MAW (2000) MAW (2000) a MAW (2008) MAW (2008) MAW (2008) MAW (2008) baAverage of 1998 and 2004; b based on 2007 values

Figure 6. Composition of the retained industrial fishery catch of Saudi Arabia in the Red Sea.

Saudi Arabia - Tesfamichael and Rossing 161

The species composition of discarded catch is different from that of the retained catch. There was no any data for the composition of discards from the Saudi Arabian Red Sea trawl fishery. However, such data were available from the Yemeni part of the Red Sea (Walczak 1977), which was used for Saudi Arabia with some modification. Jacks, lizard fish, breams, grunters, catfish and barracuda were reported as discards in Walczak (1977). They were removed from the discard list of Saudi Arabian industrial fishery, as these species were believed to have been retained (Sanders and Morgan 1989). The remaining taxonomic groups of the discard were scaled to make the total 100% (Table 7). The final catch composition is presented in Figure (8) and the actual values in Table (A5).

Recreational fishery

Very little data were available for Saudi Arabia’s recreational fishery catches. They have not traditionally been accounted for in the reported fisheries statistics, possibly because their catch is very small compared with artisanal or industrial fisheries. The only catch estimate available was 1,500 t for 1998 (MAW 2000). This tonnage was used as anchor point. We assumed, in lack of other data, that recreational catches had been ongoing since the beginning of 1970s. This is the time the oil wealth started to have effect in the fishing sector. Many Saudi citizens started to buy fiberglass boats and hired foreigners to do the fishing (Sanders and Morgan 1989; Sakurai 1998) while they would go fishing for pleasure usually in the weekend. Thus, the catch was assumed to be zero until 1969 and interpolated between 1969 and the anchor in 1998. The population size of Saudi Arabia was used as a proxy to calculate the recreational fishery catch from 1998 to 2010 using the 1998 catch as anchor.

Recreational catches were reported to consist mostly of emperors, then sea breams followed by groupers (MAW 2000). We transformed this qualitative information (using 10% steps between the ranked groups) into percent contributions, which yielded: emperors (Lethrinidae) = 40%; sea breams (Sparidae) = 30%; groupers (Serranidae) = 20% and ‘others’ = 10% (Figure 9, Table A6).

Comparing reconstructed catch with the FAO data

The reconstructed catch was compared to the catch reported in the United Nations Food and Agriculture Organization (FAO) database on behalf of Saudi Arabia (www .fao.org/fishery/statistics/software/fishstat/en). FAO uses broad statistical areas to geographically subdivide catches, and in the case of Saudi Arabia, both coasts fall in the same statistical area (‘Western Indian Ocean’). Thus, the Saudi Arabian catch reported to FAO needed to be divided into the two coasts. This was done using reports that allocated ratios to the Red Sea and the Persian Gulf (Table 8).

The earliest available Red Sea-to-Gulf ratio was for 1979 (Barrania et al. 1980), 1987 to 1998 (Sakurai 1998; MAW 2000) and 2000 (FAO 2003). For 2002, the Regional Commission for Fisheries (RECOFI 2009), which is active in the Gulf, reported the Gulf catch of Saudi Arabia, which in turn was used to calculate the percentage for the Red Sea. In more recent years, Saudi Arabia published annual fishery statistical reports, separate for each coast, which we relied on for 2004 to 2007 (MAW 2008). The latest year with data disaggregated between the two coasts was for 2009, and statistical data were presented separately for the artisanal and industrial sectors in the Red Sea and the artisanal sector in the Gulf (FSDP 2011). The industrial catch in the Gulf was calculated using the ratio for the two sectors in 2007, where industrial catch was 0.38% of the artisanal catch.

Table 7. Catch composition (%) of Saudi Arabia’s discarded industrial catch in the Red Sea.

Species %

Pony fish 63.3Grunters 7.1Mojarra 4.1Cutlass fish 4.1Flatheads 2.0Puffers 2.0Soles 2.0Black pomfret 2.0Blue Swimming crab 2.0Sardines, anchovies 1.0Goatfish 1.0Mantis shrimp 1.0Others 8.2

Figure 8. Composition of the discarded industrial fishery catch of Saudi Arabia in the Red Sea.

Figure 7. The contribution of shrimp and Indian mackerel to the total industrial catch of Saudi Arabia in the Red Sea for the years data were available.

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For years where data were not available, they were estimated using different methods. For 1950 to 1960 and 1975 to 1978, the earliest available data (for 1979) were used. Using the 1979 Red Sea-Gulf ratio for 1961 to 1974 resulted in unreasonably very high Red Sea catches, thus a different approach was used for this period. The closest period with data that separates the Red Sea and Gulf catches was for 1987 to 1994. Thus, an average ratio was calculated for the total reconstructed Red Sea catch without the industrial discard to the FAO catch of Red Sea from 1987 to 1994. (Note that discarded catches are not reported to FAO at all). The result, that FAO Red Sea data were on average 92% of the reconstructed catch, was used to calculate the FAO Red Sea catch for 1961 to 1974. Then the FAO Gulf catch was obtained by subtracting the Red Sea amount from the total Saudi catch in the FAO database. The same ratio was also used for the period 1980 to 1986. Although there were ratios available for 1995 to 1996, they resulted in the FAO Red Sea catch being slightly higher than the reconstructed catch, which is unrealistic given the pattern for the other years. Thus, the reconstructed catch (without industrial discard) is assumed to be equal to the FAO Red Sea catch. For 1999, 2001, 2003, 2008 and 2010, the ratios were interpolated from the neighbouring years (Table 8). 4

Once the FAO data for Saudi Arabia in the Red Sea were separated, they were compared with our reconstructed catch. The FAO data have more taxa (127) than the reconstructed catch, which is strange given that we used the Saudi official national and technical reports for our catch reconstruction. The large number of taxa started in 2000 when the country introduced an extensive data recording and reporting system. Most of the taxa that were included starting in 2000 have very low catch amounts and they were aggregated as ‘miscellaneous’ in the national reports we used. To make full use of the additional information on catch composition in the FAO data, it was used to further disaggregate the reconstructed catch composition. First the distribution of the taxa were verified using FishBase (Froese and Pauly 2012) to check if each taxon was to be included in both the Red Sea and the Gulf or only in one of these bodies of water. Then, for the taxa included in the FAO data, but not in the reconstruction, the ratios of the taxa in the FAO data were used to disaggregate the catch composition of the reconstructed data. For example, in the reconstructed catch, there was only one taxon item for groupers (Serranidae), but in the FAO data there were 18 taxon items for groupers, mainly species, but also including Serranidae. Overall, the “Serranidae” of the reconstructed Gulf catch was disaggregated into 17 groups using their ratios in the FAO data.

After the reconstructed and the corresponding FAO catch by taxa were tabulated, comparison was done at taxonomic level. The part of the reconstructed catch that is accounted in the FAO data is referred as ‘reported catch’ in our result. If the value of a taxon in reconstructed catch was higher than its value in the FAO data, then the difference was labeled as ‘unreported catch’. If the FAO value for a taxon was higher than the reconstructed catch, the difference is over-reported catch in the EEZ of Saudi Arabia in the Red Sea. Since, the comparison of the reconstructed catch with the FAO data has modified the catch composition of the reconstructed catch, the final ratios are not exactly what are reported in the methodological tables given in the above.

results and disCussion

The Saudi fishery in its Red Sea EEZ had, for a long time, catches less than 10,000 t·year-1. The fishery was dominated by traditional fishers who used small sailing boats and simple gears for decades (El-Saby and Farina 1954; Neve and Al-Aiidy 1973; Tesfamichael and Pitcher 2006). The catches were largely for subsistence and very localized markets, and the fishery lacked modern technology. The rapid change started at the beginning of 1980s, when the catch increased drastically to attain its maximum in the mid-1990s. After the mid-1990s, the total catch was declining, but remained higher than in the earlier years. The maximum catch attained was around 50,000 t in 1994. The rapid increase in the total catch starting the 1980s is due to the motorization and the introduction of fast fibreglass boats in the artisanal fisheries (Sanders and Morgan 1989; Sakurai 1998), which resulted in higher catches (Figure 10, Appendix Table A7). The artisanal and subsistence fisheries were the only ones operating in the Red Sea until the 1980s, when the industrial and recreational fisheries started, and contributed to a drastic increase of the total catch (Sanders and Morgan 1989). The catch of the artisanal fishery decreased dramatically in 1995, but this was compensated for by an increase of the industrial catch. The contribution of the recreational fishery was very low. The slight decrease from the peak is taken as a sign of resource depletion by the fisheries administration and precautionary approaches are being considered, for example new licenses are not issued (MAW 2000). Overall, artisanal fishery contributed to the highest to the total catch from 1950 to 2010 (64%), followed by industrial fishery (12%), discards (11%), subsistence catch (10%) and recreational fishery (3%).

4 After the completion of the report, we came to realize that data only for the gulf were available at FAO/RECOFI. Our sources gave us similar results. In addition we used the FAO data only as a way of comparison and did not have any impact in our reconstruction.

Figure 9. Catch composition of Saudi Arabia’s recreational fishery in the Red Sea.

Saudi Arabia - Tesfamichael and Rossing 163

The reported catch (the reconstructed catch accounted in the FAO data) had the highest contribution to the total catch (54%). The discarded catch (11%), originating from the trawl fishery, appeared only since 1982 when the Saudi industrial fishery started operating in the Red Sea. The unreported landed catch accounted for 35%. The reconstructed catch and the catch reported by FAO on behalf of Saudi Arabia assigned to the Red Sea were close to each other from the 1960s to mid-1980s. The major differences are in the 1950s and from the mid-1980s on (Figure 11, Table A8). In the 1950s, there was not any catch recording system. The fishery was traditional and there was no regulatory body, hence its catches were not properly reported. The main difference after the mid-1980s is the discarded catch of the industrial fishery, which is included in the reconstructed catch, but missing in the data supplied to FAO. As in many other sub-tropical fisheries, the Saudi Red Sea fishery catch consisted a very large number of taxonomic groups. However, only 5 taxa made up 50% of the total catch from 1950 to 2010: Spanish mackerel (17%), emperors (9%), jacks (9%), groupers (8%) and pony fish (7%). These dominant taxa are caught by artisanal fisheries. The

Table 8. Ratios used to calculate the Red Sea catch from Saudi Arabia’s catch reported to FAO.

Year Red Sea Source/Remarks1950-60 52.74 1979 values1961 39.01 FAO Red Sea catch assumed to be 92% of reconstructed catch1962 35.25 FAO Red Sea catch assumed to be 92% of reconstructed catch1963 33.59 FAO Red Sea catch assumed to be 92% of reconstructed catch1964 35.80 FAO Red Sea catch assumed to be 92% of reconstructed catch1965 39.39 FAO Red Sea catch assumed to be 92% of reconstructed catch1966 38.69 FAO Red Sea catch assumed to be 92% of reconstructed catch1967 38.13 FAO Red Sea catch assumed to be 92% of reconstructed catch1968 43.70 FAO Red Sea catch assumed to be 92% of reconstructed catch1969 47.18 FAO Red Sea catch assumed to be 92% of reconstructed catch1970 47.83 FAO Red Sea catch assumed to be 92% of reconstructed catch1971 46.55 FAO Red Sea catch assumed to be 92% of reconstructed catch1972 44.76 FAO Red Sea catch assumed to be 92% of reconstructed catch1973 41.39 FAO Red Sea catch assumed to be 92% of reconstructed catch1974 47.47 FAO Red Sea catch assumed to be 92% of reconstructed catch1975-78 52.74 1979 values1979 52.74 Barrania et al. (1980)1980 48.13 FAO Red Sea catch assumed to be 92% of reconstructed catch1981 46.03 FAO Red Sea catch assumed to be 92% of reconstructed catch1982 44.71 FAO Red Sea catch assumed to be 92% of reconstructed catch1983 40.09 FAO Red Sea catch assumed to be 92% of reconstructed catch1984 40.59 FAO Red Sea catch assumed to be 92% of reconstructed catch1985 51.44 FAO Red Sea catch assumed to be 92% of reconstructed catch1986 52.69 FAO Red Sea catch assumed to be 92% of reconstructed catch1987 66.07 Sakurai (1998), MAW (2000)1988 67.93 Sakurai (1998), MAW (2000)1989 68.49 Sakurai (1998), MAW (2000)1990 72.28 Sakurai (1998), MAW (2000)1991 74.57 Sakurai (1998), MAW (2000)1992 68.13 Sakurai (1998), MAW (2000)1993 69.17 Sakurai (1998), MAW (2000)1994 62.53 Sakurai (1998), MAW (2000)1995 53.75 Sakurai (1998), MAW (2000)1996 50.76 Sakurai (1998), MAW (2000)1997 53.10 Sakurai (1998), MAW (2000)1998 48.91 Sakurai (1998), MAW (2000)1999 47.41 Interpolated2000 45.73 FAO (2003)2001 43.61 Interpolated2002 41.93 RECOFI (2009)2003 39.43 Interpolated2004 36.85 MAW (2008)2005 38.59 MAW (2008)2006 35.79 MAW (2008)2007 40.01 MAW (2008)2008 40.11 Interpolated2009 40.21 FSDP (2011)2010 40.31 Interpolated

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highest contribution of the industrial fishery were pony fishes (Family Leignathidae, which are systematically discarded) and which, with 7%, ranked fifth in the total catch (Figure 12, Table A9).

This long time series of reconstructed Saudi Arabian catches in the Red Sea, the first of its kind, is very informative, and should be useful in the assessment and management of the fisheries (Tesfamichael 2012). Unreported catches are estimated for the different sectors given explicit assumptions, on the basis of the best information available. Some of the procedures and assumptions used here will certainly require correcting when new information is available. In the meantime, this is provided in the hope that it will be found useful.

aCknowledgments

We thank Tim Huntington of Poseidon Aquatic Resource Management Ltd for his collaboration in providing us with the data of Saudi Arabian fisheries and also for his constructive comments on our first draft. Our gratitude goes to Julia Spät and Andrew Bruckner for their help with reports of Saudi Arabian fisheries and the latter for reviewing the draft. We also thank Daniel Pauly for his encouragement and copious comments on the draft. This research was supported by Sea Around Us, a scientific collaboration between the University of British Columbia and The Pew Charitable Trusts.

Figure 10. Reconstructed catch of Saudi Arabia in the Red Sea by sectors and its comparison to the data reported by FAO on behalf of Saudi Arabia.

Figure 12. Composition of the total catch of Saudi Arabia’s fisheries in the Red Sea.

Figure 11. Reconstructed catch of Saudi Arabia in the Red Sea by components. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.

Saudi Arabia - Tesfamichael and Rossing 165

referenCes

Barrania A, Bringi MR and Saleh M (1980) Socio-economic aspects of the Saudi Arabian fisheries in the Red Sea. FAO/UNDP Proj. for Development of Fisheries in Areas of the Red Sea and Gulf of Aden, Suez, Egypt.

Bruckner A, Rowlands G, Riegl B, Purkis S, Williams A and Renaud P (2011) Khaled bin Sultan Living Oceans Foundation Atlas of Saudi Arabian Red Sea Marine Habitats. Panoramic Press, Phoenix.

Chakraborty D (1984) Fish landings on the Red Sea and Gulf of Aden coast of the member countries: A preliminary estimate. Development of Fisheries in Areas of the Red Sea and Gulf of Aden, United Nations Development Programme (UNDP) and Food and Agriculture Organization (FAO) of the United Nations, Suez, Egypt. 29 p.

El-Saby MK and Farina L (1954) Report to the government of Saudi Arabia on possibility for development of marine fisheries. FAO, Rome.

FAO (2003) Kingdom of Saudi Arabia fishery country profile. FAO, Rome.Ferrer GG (1958) Report to the government of Saudi Arabia on exploration and commercial fishing operations in the

Red Sea. FAO, Rome.Froese R and Pauly D (2012) FishBase. Available at: www .fishbase.org [Accessed: May 24, 2012].FSDP (2011) Fisheries Sector Development Plans (Phase 2): Establishing entities to undertake marketing, processing

and services for the aquaculture and fishery industries in the Kingdom of Saudi Arabia. KPMG and Poseidon, aquatic resource management Ltd. .

Gilberg YC (1966) Report to the government of the Kingdom of Saudi Arabia on a survey of marien fisheries development possibilities. FAO, Rome.

Kedidi SM, Abushusha T and Allam K (1984) Description of the artisanal fishery at Tuwwal, Saudi Arabia: catches, efforts and catches per unit effort survey conducted during 1981–1982. FAO, Rome.

MAW (1986) Fisheries of Saudi Arabia, 1985. Ministry of Agriculture and water, Department of Marine Fisheries. Kingdom of Saudi Arabia.

MAW (1996) Fisheries of Saudi Arabia, 1995. Ministry of Agriculture and water, Department of Marine Fisheries. Kingdom of Saudi Arabia.

MAW (1998) Fisheries of Saudi Arabia, 1997. Ministry of Agriculture and water, Department of Marine Fisheries. Kingdom of Saudi Arabia.

MAW (2000) Fisheries of Saudi Arabia, 1998. Ministry of Agriculture and water, Department of Marine Fisheries. Kingdom of Saudi Arabia.

MAW (2006) Fisheries of Saudi Arabia, 2005. Ministry of Agriculture and water, Department of Marine Fisheries. Kingdom of Saudi Arabia.

MAW (2008) Statistical indications about fisheries in the Kingdom of Saudi Arabia 2007. Ministry of Agriculture and water, Department of Marine Fisheries. Kingdom of Saudi Arabia.

Neve P and Al-Aiidy H (1973) The Red Sea Fisheries of Saudi Arabia. Bull.Mar.Res.Cent.Saudi Arabia 3: 32.Peacock NA (1978) Final report. The fishery resource survey of the Saudi Arabian Red Sea, February 1977–October

1979 Field rep. Fish. Dev. Proj. Kingdom of Saudi Arabia, 40 : 28p.Price ARG, Medley PAH, McDowall RJ, Dawson-Shepherd AR, Hogarth PJ and Ormond RFG (1987) Aspects of mangal

ecology along the Red Sea coast of Saudi Arabia. Journal of Natural History 21(2): 449-464.RECOFI (2009) Review of capture fishery statistics in the RECOFI area. Regional commission for fisheries (RECOFI),

Dubai, UAE. 9 p.Sakurai T (1998) Fisheries of Saudi Arabia. Ministry of Agriculture and water, Department of Marine Fisheries and

Japan International Cooperation Agency.Sanders MJ and Morgan GR (1989) Review of the fisheries resources of the Red Sea and Gulf of Aden. FAO, Rome.

138 p.Tesfamichael D (2012) Assessment of the Red Sea ecosystem with emphasis on fisheries. PhD, University of British

Columbia, Resource Management and Environmental Studies, Vancouver. 241 p.Tesfamichael D and Awadh H (2012) Common names of exploited fish and invertebrates of the Red Sea. In Tesfamichael

D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20(1), Vancouver.

Tesfamichael D, Govender R and Pauly D (2012) Preliminary reconstruction of fisheries catches of Jordan and Israel in the inner Gulf of Aqaba, Red Sea, 1950-2010. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D and Mohamud S (2012) Reconstructing Red Sea fisheries of Eritrea: A case study of the relationship between political stability and fisheries development. In Tesfamichael D and Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D and Pitcher TJ (2006) Multidisciplinary evaluation of the sustainability of Red Sea fisheries using Rapfish. Fisheries Research 78(2-3): 227-235.

Tesfamichael D, Pitcher TJ and Pauly D (in press) Assessing changes in fisheries using fishers’ knowledge to generate long time series of catch rates: a case study from the Red Sea. Ecology and society.

Walczak P (1977) The Yemen Arab Republic. A study of the marine resources of the Yemen ArabRepublic. A report prepared for the Fisheries Development Project. FAO, Rome. 67 p.

Zeller D, Rossing P, Harper S, Persson L, Booth S and Pauly D (2011) The Baltic Sea: Estimates of total fisheries removals 1950–2007. Fisheries Research 108(2-3): 356-363.

166 Appendix Table A1. Catch composition (in tonnes) of Saudi Arabia’s artisanal fishery in the Red Sea by major taxa.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 161950 1,248 857 457 514 686 229 457 343 400 123 0 280 0 0 0 01951 1,248 857 457 514 686 229 457 343 400 123 0 280 0 0 0 01952 1,248 857 457 514 686 229 457 343 400 123 0 280 0 0 0 01953 1,248 857 457 514 686 229 457 343 400 123 0 280 0 0 0 01954 1,279 879 469 527 703 234 469 351 410 127 0 287 0 0 0 01955 1,310 900 480 540 720 240 480 360 420 130 0 294 0 0 0 01956 1,342 921 491 553 737 246 491 369 430 133 0 301 0 0 0 01957 1,373 943 503 566 754 251 503 377 440 136 0 308 0 0 0 01958 1,404 964 514 579 771 257 514 386 450 139 0 315 0 0 0 01959 1,435 986 526 591 789 263 526 394 460 142 0 322 1 0 0 01960 1,466 1,007 537 604 806 269 537 403 470 145 0 329 1 0 0 01961 1,498 1,029 549 617 823 274 549 411 480 148 0 336 1 0 0 01962 1,529 1,050 560 630 840 280 560 420 490 151 0 343 1 0 0 01963 1,560 1,071 571 643 857 286 571 429 500 154 0 350 1 0 0 01964 1,502 1,031 550 619 825 275 550 413 481 149 0 337 1 0 0 01965 1,736 1,193 636 716 954 318 636 477 557 172 0 390 1 0 0 01966 1,852 1,272 678 763 1,018 339 678 509 594 183 0 416 1 0 0 01967 1,997 1,371 731 823 1,097 366 731 549 640 197 0 448 1 0 0 01968 2,185 1,501 800 900 1,200 400 800 600 700 216 0 490 1 0 0 01969 2,460 1,689 901 1,014 1,352 451 901 676 788 243 0 552 1 0 0 01970 2,460 1,689 901 1,014 1,352 451 901 676 788 243 0 552 1 0 0 01971 2,460 1,689 901 1,014 1,352 451 901 676 788 243 0 552 1 0 0 01972 2,525 1,734 925 1,040 1,387 462 925 694 809 250 0 566 1 0 0 01973 2,590 1,779 949 1,067 1,423 474 949 711 830 256 0 581 1 0 0 01974 2,655 1,823 972 1,094 1,459 486 972 729 851 263 0 596 1 0 0 01975 2,720 1,868 996 1,121 1,494 498 996 747 872 269 0 610 1 0 0 01976 2,785 1,913 1,020 1,148 1,530 510 1,020 765 893 275 0 625 1 0 0 01977 2,785 1,913 1,020 1,148 1,530 510 1,020 765 893 275 0 625 1 0 0 01978 3,522 2,419 1,290 1,451 1,935 645 1,290 968 1,129 348 0 790 1 0 0 01979 3,093 2,124 1,133 1,274 1,699 566 1,133 850 991 306 0 694 1 0 0 01980 2,826 1,941 1,035 1,164 1,553 518 1,035 776 906 279 0 634 1 0 0 01981 3,525 2,192 983 1,270 1,204 742 886 976 895 349 0 588 2 0 0 01982 3,525 2,192 983 1,270 1,204 742 886 976 895 349 0 588 2 0 0 01983 3,702 2,112 775 1,182 654 860 594 1,030 745 366 0 449 4 0 0 01984 4,136 1,978 1,404 1,555 918 956 458 690 534 409 0 310 3 0 0 01985 6,368 2,514 2,911 2,723 1,676 1,466 419 419 406 628 0 209 4 0 0 01986 6,630 2,617 3,032 2,835 1,745 1,527 436 436 423 654 0 218 4 0 0 01987 8,444 3,333 3,861 3,611 2,222 1,944 556 556 538 833 0 278 6 0 0 01988 9,120 3,600 4,170 3,900 2,400 2,100 600 600 582 900 0 300 6 0 0 01989 9,120 3,600 4,170 3,900 2,400 2,100 600 600 582 900 0 300 6 0 0 01990 8,444 3,333 3,861 3,611 2,222 1,944 556 556 538 833 0 278 6 0 0 01991 8,444 3,333 3,861 3,611 2,222 1,944 556 556 538 833 0 278 6 0 0 01992 8,444 3,333 3,861 3,611 2,222 1,944 556 556 538 833 0 278 6 0 0 01993 9,120 3,600 4,170 3,900 2,400 2,100 600 600 582 900 0 300 6 0 0 01994 9,120 3,600 4,170 3,900 2,400 2,100 600 600 582 900 0 300 6 0 0 01995 2,787 1,841 2,133 1,824 843 671 327 310 290 2,598 0 516 688 0 0 451996 2,899 2,315 2,994 3,066 841 687 325 308 314 498 0 399 599 0 0 631997 3,579 2,322 2,837 2,718 1,088 776 368 348 333 563 0 451 877 0 0 1071998 4,638 2,289 2,478 2,967 1,072 774 367 347 297 561 0 449 514 0 0 1151999 3,481 2,898 3,243 3,491 1,148 1,120 325 489 542 887 0 482 545 0 0 1582000 3,353 713 1,457 1,001 155 814 313 471 511 854 963 259 525 637 209 1622001 3,673 581 1,591 1,159 378 321 343 516 526 935 1,022 324 575 641 508 1712002 3,421 515 1,509 1,072 127 363 319 480 581 871 863 253 536 735 617 852003 3,258 915 1,525 800 168 702 304 457 59 830 904 246 510 1,297 255 4832004 2,343 635 1,154 1,007 148 260 178 320 46 149 579 130 222 409 429 4322005 2,467 770 1,428 993 235 406 194 471 42 277 794 184 237 543 695 6012006 1,939 582 1,372 1,040 140 314 167 473 30 528 881 252 248 493 819 6612007 2,454 796 1,598 1,260 174 400 234 667 57 684 952 193 247 441 782 7662008 2,470 628 1,575 957 126 420 236 671 69 689 880 278 248 542 750 8062009 2,486 598 1,503 1,039 173 336 237 675 54 693 1,024 235 250 519 866 8762010 2,502 605 1,576 949 167 393 239 680 53 698 918 248 251 640 826 886

1: Scomberomorus commerson; 2: Carangidae; 3: Lethrinidae; 4: Serranidae; 5: Lutjanidae; 6: Sphyraena spp.; 7: Valamugil seheli; 8: Elasmobranchii; 9: Scombridae; 10: Rastrelliger kanagurta; 11: Lethrinus lentjan; 12: Scaridae; 13: Siganus spp.; 14: Epinephelus tauvina; 15: Sphyraena barracuda; 16: Euthynnus affinis

Saudi Arabia - Tesfamichael and Rossing 167Table A1 continuedYear 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 321950 0 0 5 0 0 0 0 5 4 4 0 0 0 0 0 2081951 0 0 5 0 0 0 0 5 4 4 0 0 0 0 0 2081952 0 0 5 0 0 0 0 5 4 4 0 0 0 0 0 2081953 0 0 5 0 0 0 0 5 4 4 0 0 0 0 0 2081954 0 0 6 0 0 0 0 5 4 4 0 0 0 0 0 2111955 0 0 6 0 0 0 0 5 4 4 0 0 0 0 0 2131956 0 0 6 0 0 0 0 5 5 4 0 0 0 0 0 2161957 0 0 6 0 0 0 0 5 5 5 0 0 0 0 0 2181958 0 0 6 0 0 0 0 5 5 5 0 0 0 0 0 2211959 0 0 6 0 0 0 0 5 5 5 0 0 0 0 0 2231960 0 0 6 0 0 0 0 5 5 5 0 0 0 0 0 2261961 0 0 6 0 0 0 0 6 5 5 0 0 0 0 0 2291962 0 0 7 0 0 0 0 6 5 5 0 0 0 0 0 2311963 0 0 7 0 0 0 0 6 5 5 0 0 0 0 0 2341964 0 0 6 0 0 0 0 6 5 5 0 0 0 0 0 2291965 0 0 8 0 0 0 0 6 6 6 0 0 0 0 0 2481966 0 0 8 0 0 0 0 7 6 6 0 0 0 0 0 2571967 0 0 9 0 0 0 0 7 7 7 0 0 0 0 0 2631968 0 0 9 0 0 0 0 8 7 7 0 0 0 0 0 2721969 0 0 11 0 0 0 0 9 8 8 0 0 0 0 0 2891970 0 0 11 0 0 0 0 9 8 8 0 0 0 0 0 2831971 0 0 11 0 0 0 0 9 8 8 0 0 0 0 0 2771972 0 0 11 0 0 0 0 9 9 8 0 0 0 0 0 2761973 0 0 11 0 0 0 0 10 9 9 0 0 0 0 0 2561974 0 0 11 0 0 0 0 10 9 9 0 0 0 0 0 2661975 0 0 12 0 0 0 0 10 9 9 0 0 0 0 0 2661976 0 0 12 0 0 0 0 10 10 9 0 0 0 0 0 2501977 0 0 12 0 0 0 0 10 10 9 0 0 0 0 0 2411978 0 0 15 0 0 0 0 13 12 12 0 0 0 0 0 3011979 0 0 13 0 0 0 0 11 11 10 0 0 0 0 0 2731980 0 0 12 0 0 0 0 10 10 9 0 0 0 0 0 2581981 0 0 31 0 0 0 0 26 24 24 0 0 0 0 0 5881982 0 0 31 0 0 0 0 26 24 24 0 0 0 0 0 5951983 0 0 45 0 0 0 0 38 36 35 0 0 0 0 0 8501984 0 0 44 0 0 0 0 38 35 34 0 0 0 0 0 8521985 0 0 60 0 0 0 0 51 48 47 0 0 0 0 0 9971986 0 0 63 0 0 0 0 53 50 49 0 0 0 0 0 1,0381987 0 0 80 0 0 0 0 68 63 62 0 0 0 0 0 1,3221988 0 0 86 0 0 0 0 73 68 67 0 0 0 0 0 1,4281989 0 0 86 0 0 0 0 73 68 67 0 0 0 0 0 1,4281990 0 0 80 0 0 0 0 68 63 62 0 0 0 0 0 1,3221991 0 0 80 0 0 0 0 68 63 62 0 0 0 0 0 1,3221992 0 0 80 0 0 0 0 68 63 62 0 0 0 0 0 1,3221993 0 0 86 0 0 0 0 73 68 67 0 0 0 0 0 1,4281994 0 0 86 0 0 0 0 73 68 67 0 0 0 0 0 1,4281995 0 0 160 0 0 0 0 136 127 124 0 0 0 0 0 1,7841996 0 0 106 0 0 0 0 90 84 82 0 0 0 0 0 1,4521997 0 0 229 0 0 0 0 195 181 178 0 0 0 0 0 2,2031998 0 0 161 0 0 0 0 137 127 125 0 0 0 0 0 1,9751999 0 0 181 0 0 0 0 154 143 141 0 0 0 0 0 2,3632000 473 364 175 214 184 379 588 149 138 135 297 241 203 251 174 4,6262001 624 447 191 329 280 644 370 163 151 148 278 197 141 176 146 5,4402002 556 13 178 393 429 234 507 152 141 138 327 187 181 254 235 5,1402003 577 396 170 182 387 242 371 144 134 132 246 99 201 152 122 4,1232004 428 487 127 245 297 171 341 97 91 76 189 156 182 132 94 3,1582005 538 449 177 295 386 335 209 99 126 97 212 210 208 211 184 3,4522006 518 518 162 205 379 265 212 59 109 110 247 275 232 257 270 3,8172007 579 288 74 276 350 204 182 216 106 148 171 222 221 223 252 4,5282008 452 389 151 441 410 351 241 129 119 117 161 269 184 216 245 4,6532009 381 532 152 529 262 329 201 129 120 118 205 270 255 223 281 4,4472010 501 451 153 536 227 308 227 130 121 119 231 272 334 225 282 4,379

17: Decapterus russelli; 18: Atule mate; 19: Sargocentron spiniferum; 20: Carangoides bajad; 21: Gnathanodon speciosus; 22: Epinephelus multinotatus; 23: Lutjanus gibbus; 24: Netuma thalassina; 25: Tylosurus crocodilus crocodilus; 26: Clupeidae; 27: Lethrinus borbonicus; 28: Plectropomus areolatus; 29: Epinephelus areolatus; 30: Plectropomus pessuliferus; 31: Variola louti; 32: Others

168Appendix Table A2. Catch composition (in tonnes) of Saudi Arabia’s subsistence fishery catch in the Red Sea by major taxa.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 161950 374 257 137 154 206 69 137 120 84 37 0 0 0 0 0 01951 374 257 137 154 206 69 137 120 84 37 0 0 0 0 0 01952 374 257 137 154 206 69 137 120 84 37 0 0 0 0 0 01953 374 257 137 154 206 69 137 120 84 37 0 0 0 0 0 01954 384 264 141 158 211 70 141 123 86 38 0 0 0 0 0 01955 393 270 144 162 216 72 144 126 88 39 0 0 0 0 0 01956 402 276 147 166 221 74 147 129 90 40 0 0 0 0 0 01957 412 283 151 170 226 75 151 132 92 41 0 0 0 0 0 01958 421 289 154 174 231 77 154 135 95 42 0 0 0 0 0 01959 431 296 158 177 237 79 158 138 97 43 0 0 0 0 0 01960 440 302 161 181 242 81 161 141 99 44 0 0 0 0 0 01961 449 309 165 185 247 82 165 144 101 44 0 0 0 0 0 01962 459 315 168 189 252 84 168 147 103 45 0 0 0 0 0 01963 468 321 171 193 257 86 171 150 105 46 0 0 0 0 0 01964 300 206 110 124 165 55 110 96 67 30 0 0 0 0 0 01965 343 236 126 142 189 63 126 110 77 34 0 0 0 0 0 01966 362 249 133 149 199 66 133 116 81 36 0 0 0 0 0 01967 386 265 142 159 212 71 142 124 87 38 0 0 0 0 0 01968 418 287 153 172 230 77 153 134 94 41 0 0 0 0 0 01969 465 320 170 192 256 85 170 149 104 46 0 0 0 0 0 01970 460 316 168 190 253 84 168 147 103 45 0 0 0 0 0 01971 455 312 166 187 250 83 166 146 102 45 0 0 0 0 0 01972 461 317 169 190 253 84 169 148 103 46 0 0 0 0 0 01973 467 321 171 193 257 86 171 150 105 46 0 0 0 0 0 01974 473 325 173 195 260 87 173 152 106 47 0 0 0 0 0 01975 479 329 175 197 263 88 175 153 107 47 0 0 0 0 0 01976 484 333 177 200 266 89 177 155 109 48 0 0 0 0 0 01977 478 328 175 197 263 88 175 153 107 47 0 0 0 0 0 01978 597 410 219 246 328 109 219 191 134 59 0 0 0 0 0 01979 518 356 190 213 284 95 190 166 116 51 0 0 0 0 0 01980 467 321 171 192 257 86 171 150 105 46 0 0 0 0 0 01981 575 357 160 207 196 121 145 146 96 57 0 0 0 0 0 01982 567 353 158 204 194 119 143 144 95 56 0 0 0 0 0 01983 587 335 123 188 104 137 94 118 71 58 0 1 0 0 0 01984 647 310 220 243 144 150 72 84 48 64 0 1 0 0 0 01985 983 388 449 420 259 226 65 63 32 97 0 1 0 0 0 01986 1,009 398 461 431 266 232 66 64 33 100 0 1 0 0 0 01987 1,267 500 579 542 333 292 83 81 42 125 0 1 0 0 0 01988 1,348 532 616 577 355 310 89 86 44 133 0 1 0 0 0 01989 1,328 524 607 568 350 306 87 85 44 131 0 1 0 0 0 01990 1,212 478 554 518 319 279 80 77 40 120 0 1 0 0 0 01991 1,193 471 546 510 314 275 79 76 39 118 0 1 0 0 0 01992 1,175 464 537 502 309 271 77 75 39 116 0 1 0 0 0 01993 1,249 493 571 534 329 288 82 80 41 123 0 1 0 0 0 01994 1,229 485 562 526 323 283 81 78 40 121 0 1 0 0 0 01995 370 244 283 242 112 89 43 38 68 345 0 91 0 0 6 01996 378 302 391 400 110 90 42 41 52 65 0 78 0 0 8 01997 459 298 364 349 140 100 47 43 58 72 0 113 0 0 14 01998 585 289 312 374 135 98 46 37 57 71 0 65 0 0 14 01999 431 359 402 433 142 139 40 67 60 110 0 68 0 0 20 02000 408 87 177 122 19 99 38 62 32 104 117 64 78 25 20 582001 439 69 190 139 45 38 41 63 39 112 122 69 77 61 20 752002 402 60 177 126 15 43 37 68 30 102 101 63 86 72 10 652003 375 105 176 92 19 81 35 7 28 96 104 59 149 29 56 662004 265 72 130 114 17 29 20 5 15 17 65 25 46 48 49 482005 273 85 158 110 26 45 22 5 20 31 88 26 60 77 67 602006 211 63 149 113 15 34 18 3 27 57 96 27 54 89 72 562007 261 85 170 134 19 43 25 6 21 73 101 26 47 83 82 622008 258 66 164 100 13 44 25 7 29 72 92 26 57 78 84 472009 254 61 154 106 18 34 24 6 24 71 105 26 53 89 90 392010 250 61 158 95 17 39 24 5 25 70 92 25 64 83 89 50

1: Scomberomorus commerson; 2: Carangidae; 3: Lethrinidae; 4: Serranidae; 5: Lutjanidae; 6: Sphyraena spp.; 7: Valamugil seheli; 8: Scombridae; 9: Scaridae; 10: Rastrelliger kanagurta; 11: Lethrinus lentjan; 12: Siganus spp.; 13: Epinephelus tauvina; 14: Sphyraena barracuda; 15: Euthynnus affinis; 16: Decapterus russelli

Saudi Arabia - Tesfamichael and Rossing 169Table A2 continuedYear 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 321950 2 0 1 0 0 0 1 0 1 2 0 0 0 0 0 291951 2 0 1 0 0 0 1 0 1 2 0 0 0 0 0 291952 2 0 1 0 0 0 1 0 1 2 0 0 0 0 0 291953 2 0 1 0 0 0 1 0 1 2 0 0 0 0 0 291954 2 0 1 0 0 0 1 0 1 2 0 0 0 0 0 291955 2 0 1 0 0 0 1 0 1 2 0 0 0 0 0 301956 2 0 1 0 0 0 1 0 1 2 0 0 0 0 0 311957 2 0 2 0 0 0 1 0 1 2 0 0 0 0 0 311958 2 0 2 0 0 0 1 0 1 2 0 0 0 0 0 321959 2 0 2 0 0 0 1 0 1 2 0 0 0 0 0 331960 2 0 2 0 0 0 2 0 1 2 0 0 0 0 0 341961 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 341962 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 351963 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 361964 1 0 1 0 0 0 1 0 1 1 0 0 0 0 0 231965 1 0 1 0 0 0 1 0 1 1 0 0 0 0 0 261966 2 0 1 0 0 0 1 0 1 2 0 0 0 0 0 281967 2 0 1 0 0 0 1 0 1 2 0 0 0 0 0 291968 2 0 2 0 0 0 1 0 1 2 0 0 0 0 0 321969 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 361970 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 351971 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 351972 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 351973 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 361974 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 361975 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 371976 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 371977 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 371978 3 0 2 0 0 0 2 0 2 2 0 0 0 0 0 461979 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 401980 2 0 2 0 0 0 2 0 2 2 0 0 0 0 0 361981 5 0 4 0 0 0 4 0 4 5 0 0 0 0 0 841982 5 0 4 0 0 0 4 0 4 5 0 0 0 0 0 831983 7 0 6 0 0 0 6 0 6 7 0 0 0 0 0 1191984 7 0 6 0 0 0 5 0 5 7 0 0 1 0 0 1111985 9 0 8 0 0 0 7 0 7 9 0 0 3 0 0 1411986 10 0 8 0 0 0 8 0 7 9 0 0 3 0 0 1451987 12 0 10 0 0 0 9 0 9 12 0 0 4 0 0 1821988 13 0 11 0 0 0 10 0 10 12 0 0 4 0 0 1931989 13 0 11 0 0 0 10 0 10 12 0 0 4 0 0 1901990 11 0 10 0 0 0 9 0 9 11 0 0 4 0 0 1741991 11 0 10 0 0 0 9 0 9 11 0 0 4 0 0 1711992 11 0 9 0 0 0 9 0 9 11 0 0 4 0 0 1681993 12 0 10 0 0 0 9 0 9 11 0 0 4 0 0 1791994 12 0 10 0 0 0 9 0 9 11 0 0 4 0 0 1761995 21 0 18 0 0 0 17 0 16 20 0 0 18 0 0 1961996 14 0 12 0 0 0 11 0 11 13 0 0 18 0 0 1571997 29 0 25 0 0 0 23 0 23 28 0 0 20 0 0 2321998 20 0 17 0 0 0 16 0 16 20 0 0 19 0 0 2081999 22 0 19 0 0 0 18 0 17 22 0 0 17 0 0 2522000 21 44 18 26 22 72 17 46 16 3 36 29 16 25 31 5642001 23 53 19 39 34 44 18 77 18 0 33 23 17 17 21 6492002 21 2 18 46 50 60 17 27 16 8 38 22 16 21 30 6062003 20 46 17 21 45 43 15 28 15 2 28 11 15 23 18 4702004 14 55 11 28 34 39 10 19 9 0 21 18 10 21 15 3572005 20 50 11 33 43 23 14 37 11 0 23 23 9 23 23 3942006 18 56 6 22 41 23 12 29 12 0 27 30 8 25 28 4342007 8 31 23 29 37 19 11 22 16 1 18 24 9 24 24 4972008 16 41 13 46 43 25 12 37 12 1 17 28 8 19 23 5012009 16 54 13 54 27 21 12 34 12 1 21 28 8 26 23 4732010 15 45 13 54 23 23 12 31 12 1 23 27 8 33 22 456

17: Sargocentron spiniferum; 18: Atule mate; 19: Netuma thalassina; 20: Carangoides bajad; 21: Gnathanodon speciosus; 22: Lutjanus gibbus; 23: Tylosurus crocodilus crocodilus; 24: Epinephelus multinotatus; 25: Clupeidae; 26: Gerres spp.; 27: Lethrinus borbonicus; 28: Plectropomus areolatus; 29: Labridae; 30: Epinephelus areolatus; 31: Plectropomus pessuliferus; 32: Others

170

Appendix Table A3. Sources and methods for the reconstruction of shrimp (in tonnes) of the Saudi Arabian trawl fishery in the Red Sea.Year Total (t) Shrimp (t) % Source/Remark1982 1169 466 40 Sanders and Morgan (1989)1983 1927 455 24 Interpolation1984 2684 528 20 Interpolation1985 3442 516 15 Interpolation1986 4200 517 12 Interpolation1987 4957 412 8 MAW (2007)1988 4079 820 20 MAW (2007)1989 5274 468 9 MAW (2007)1990 4610 521 11 MAW (2007)1991 5591 1060 19 MAW (2007)1992 5995 547 9 MAW (2007)1993 5929 574 10 MAW (2007)1994 6824 1280 19 MAW (2007)1995 7356 2105 29 MAW (2007)1996 7098 1717 24 MAW (2007)1997 8411 1803 21 MAW (2007)1998 7417 1515 20 MAW (2007)1999 7382 1235 17 MAW (2007)2000 7348 878 12 MAW (2007)2001 7313 833 11 MAW (2007)2002 7278 979 13 MAW (2007)2003 7244 1060 15 MAW (2007)2004 7209 660 9 MAW (2007)2005 7535 961 13 MAW (2007)2006 7618 922 12 MAW (2007)2007 8942 949 11 MAW (2007)2008 8971 952 11 2007 % value2009 9000 955 11 2007 % value2010 9029 958 11 2007 % value

Saudi Arabia - Tesfamichael and Rossing 171Appendix Table A4. Composition (in tonnes) of the retained industrial fishery catch of Saudi Arabia in the Red Sea by major taxa.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 161950 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01967 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01968 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01969 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01970 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01971 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01972 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01973 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01974 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01975 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01976 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01977 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01978 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01979 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01980 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01981 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01982 172 466 130 47 63 0 30 33 21 21 20 23 8 17 15 161983 359 455 272 93 131 0 62 69 44 43 41 47 21 36 32 341984 526 528 398 139 193 0 91 101 64 64 60 69 28 53 47 501985 714 516 540 191 261 0 123 137 87 86 82 94 35 73 64 681986 899 517 680 285 329 0 155 173 110 109 103 118 0 91 81 851987 1,109 412 839 352 406 0 191 213 136 134 127 146 0 113 99 1051988 795 820 601 252 291 0 137 153 97 96 91 105 0 81 71 751989 1,173 468 887 372 429 0 202 226 144 142 135 154 0 119 105 1111990 998 521 755 316 365 0 172 192 122 121 115 131 0 101 90 941991 1,106 1,060 836 351 405 0 190 213 135 134 127 145 0 112 99 1051992 1,329 547 1,005 422 486 0 229 256 163 161 153 175 0 135 119 1261993 1,307 574 988 414 478 0 225 251 160 158 150 172 0 133 117 1241994 1,353 1,280 1,023 429 495 0 233 260 166 164 155 178 0 137 121 1281995 1,282 2,105 969 406 469 0 221 247 157 155 147 169 0 130 115 1211996 1,313 1,717 993 416 480 0 226 253 161 159 151 173 0 133 118 1241997 1,613 1,803 1,217 511 590 0 278 310 197 195 185 212 0 164 145 1531998 1,810 1,515 786 512 472 0 241 269 171 170 161 184 0 142 126 1321999 2,338 1,235 543 602 367 0 212 222 138 173 166 109 0 122 154 1112000 2,461 83 146 312 180 721 223 177 145 182 175 18 322 1 22 02001 2,465 103 109 345 180 636 223 64 145 183 175 68 290 47 0 02002 2,396 5 101 397 178 896 217 75 141 178 170 0 220 1 59 02003 2,352 39 185 476 185 801 213 150 138 174 167 0 130 6 20 02004 2,974 5 77 461 140 596 184 59 103 181 175 0 255 6 3 02005 2,754 11 101 583 246 855 305 109 108 213 126 86 225 14 0 02006 2,750 1 115 514 225 801 239 76 185 119 130 0 79 6 0 02007 3,465 5 199 555 247 847 260 95 306 182 228 0 175 6 3 02008 3,476 2 156 622 243 824 261 100 307 183 229 0 110 7 5 02009 3,487 44 148 615 231 860 262 80 308 183 229 0 120 7 6 02010 3,499 3 150 587 241 718 263 93 309 184 230 0 150 17 5 01: Rastrelliger kanagurta; 2: Penaeidae; 3: Carangidae; 4: Sepiidae; 5: Lethrinidae; 6: Penaeus semisulcatus; 7: Brachyura; 8: Sphyraena; 9: Netuma thalassina; 10: Scomberomorus commerson; 11: Synodontidae; 12: Nemipteridae; 13: Teuthida; 14: Haemulidae; 15: Gerres spp.; 16: Scomberoides spp.

172Table A4 continuedYear 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

1950 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01967 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01968 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01969 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01970 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01971 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01972 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01973 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01974 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01975 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01976 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01977 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01978 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01979 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01980 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01981 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 01982 0 0 7 0 0 0 0 8 5 0 7 0 4 4 0 541983 0 0 15 0 0 0 0 17 10 0 15 0 9 8 0 1131984 0 0 22 0 0 0 0 25 14 0 22 0 13 11 0 1651985 0 0 30 0 0 0 0 33 19 0 30 0 17 15 0 2251986 0 0 38 0 0 0 0 42 24 0 37 0 22 19 0 2831987 0 0 47 0 0 0 0 52 30 0 46 0 27 24 0 3491988 0 0 34 0 0 0 0 37 21 0 33 0 19 17 0 2501989 0 0 50 0 0 0 0 55 31 0 49 0 29 25 0 3691990 0 0 42 0 0 0 0 47 27 0 42 0 24 21 0 3141991 0 0 47 0 0 0 0 52 29 0 46 0 27 24 0 3481992 0 0 57 0 0 0 0 62 35 0 55 0 32 29 0 4181993 0 0 56 0 0 0 0 61 35 0 54 0 32 28 0 4111994 0 0 58 0 0 0 0 63 36 0 56 0 33 29 0 4251995 0 0 55 0 0 0 0 41 34 0 53 0 31 27 0 4221996 0 0 56 0 0 0 0 46 35 0 55 0 32 28 0 4291997 0 0 69 0 0 0 0 53 43 0 67 0 39 35 0 5321998 0 0 60 0 0 0 0 41 37 0 58 0 34 30 0 4651999 0 0 73 0 0 0 0 56 46 0 71 0 42 37 0 5652000 97 45 77 119 74 113 97 57 48 66 11 75 44 39 44 1,1752001 47 101 77 116 93 119 117 54 48 107 23 84 44 39 62 1,1502002 105 128 75 102 78 87 109 62 47 44 8 3 43 38 77 1,2402003 93 54 73 110 220 105 116 7 46 8 11 80 42 37 37 1,1662004 24 97 53 70 59 60 52 8 30 70 2 59 24 44 30 1,3072005 107 186 50 137 95 103 71 3 22 72 21 59 23 6 39 8042006 300 199 60 144 120 178 103 2 47 139 5 103 40 38 41 8592007 230 186 66 147 97 94 144 3 45 108 14 72 43 38 69 1,0122008 233 178 57 135 126 104 112 4 35 113 7 97 32 29 110 1,0742009 234 205 57 157 52 102 94 3 36 106 10 132 33 29 131 1,0422010 234 195 57 140 238 103 124 3 36 90 9 112 33 29 132 1,04617: Scolopsis taeniata; 18: Sphyraena barracuda; 19: Bothus pantherinus; 20: Lethrinus lentjan; 21: Metapenaeus monoceros; 22: Gerres oyena; 23: Decapterus russelli; 24: Scombridae; 25: Mulloidichthys flavolineatus; 26: Scomberoides commersonnianus; 27: Lutjanidae; 28: Atule mate; 29: Elasmobranchii; 30: Caesionidae; 31: Carangoides bajad; 32: Others

Saudi Arabia - Tesfamichael and Rossing 173

Appendix Table A5. Composition of the discarded industrial fishery catch (in tonnes) of Saudi Arabia in the Red Sea.Year 1 2 3 4 5 6 7 8 9 10 11 12 131950 0 0 0 0 0 0 0 0 0 0 0 0 01951 0 0 0 0 0 0 0 0 0 0 0 0 01952 0 0 0 0 0 0 0 0 0 0 0 0 01953 0 0 0 0 0 0 0 0 0 0 0 0 01954 0 0 0 0 0 0 0 0 0 0 0 0 01955 0 0 0 0 0 0 0 0 0 0 0 0 01956 0 0 0 0 0 0 0 0 0 0 0 0 01957 0 0 0 0 0 0 0 0 0 0 0 0 01958 0 0 0 0 0 0 0 0 0 0 0 0 01959 0 0 0 0 0 0 0 0 0 0 0 0 01960 0 0 0 0 0 0 0 0 0 0 0 0 01961 0 0 0 0 0 0 0 0 0 0 0 0 01962 0 0 0 0 0 0 0 0 0 0 0 0 01963 0 0 0 0 0 0 0 0 0 0 0 0 01964 0 0 0 0 0 0 0 0 0 0 0 0 01965 0 0 0 0 0 0 0 0 0 0 0 0 01966 0 0 0 0 0 0 0 0 0 0 0 0 01967 0 0 0 0 0 0 0 0 0 0 0 0 01968 0 0 0 0 0 0 0 0 0 0 0 0 01969 0 0 0 0 0 0 0 0 0 0 0 0 01970 0 0 0 0 0 0 0 0 0 0 0 0 01971 0 0 0 0 0 0 0 0 0 0 0 0 01972 0 0 0 0 0 0 0 0 0 0 0 0 01973 0 0 0 0 0 0 0 0 0 0 0 0 01974 0 0 0 0 0 0 0 0 0 0 0 0 01975 0 0 0 0 0 0 0 0 0 0 0 0 01976 0 0 0 0 0 0 0 0 0 0 0 0 01977 0 0 0 0 0 0 0 0 0 0 0 0 01978 0 0 0 0 0 0 0 0 0 0 0 0 01979 0 0 0 0 0 0 0 0 0 0 0 0 01980 0 0 0 0 0 0 0 0 0 0 0 0 01981 0 0 0 0 0 0 0 0 0 0 0 0 01982 1,710 193 110 110 55 55 55 55 55 28 28 28 2211983 1,670 189 108 108 54 54 54 54 54 27 27 27 2161984 1,938 219 125 125 63 63 63 63 63 31 31 31 2501985 1,894 214 122 122 61 61 61 61 61 31 31 31 2441986 1,897 214 122 122 61 61 61 61 61 31 31 31 2451987 1,512 171 98 98 49 49 49 49 49 24 24 24 1951988 3,009 340 194 194 97 97 97 97 97 49 49 49 3881989 1,717 194 111 111 55 55 55 55 55 28 28 28 2221990 1,912 216 123 123 62 62 62 62 62 31 31 31 2471991 3,890 439 251 251 125 125 125 125 125 63 63 63 5021992 2,007 227 129 129 65 65 65 65 65 32 32 32 2591993 2,106 238 136 136 68 68 68 68 68 34 34 34 2721994 4,697 530 303 303 152 152 152 152 152 76 76 76 6061995 7,724 872 498 498 249 249 249 249 249 125 125 125 9971996 6,300 711 406 406 203 203 203 203 203 102 102 102 8131997 6,616 747 427 427 213 213 213 213 213 107 107 107 8541998 5,559 628 359 359 179 179 179 179 179 90 90 90 7171999 4,532 512 292 292 146 146 146 146 146 73 73 73 5852000 3,222 364 208 208 104 104 104 104 104 52 52 52 4162001 3,057 345 197 197 99 99 99 99 99 49 49 49 3942002 3,592 406 232 232 116 116 116 116 116 58 58 58 4642003 3,890 439 251 251 125 125 125 125 125 63 63 63 5022004 2,422 273 156 156 78 78 78 78 78 39 39 39 3122005 3,526 398 228 228 114 114 114 114 114 57 57 57 4552006 3,383 382 218 218 109 109 109 109 109 55 55 55 4372007 3,482 393 225 225 112 112 112 112 112 56 56 56 4492008 3,494 394 225 225 113 113 113 113 113 56 56 56 4512009 3,505 396 226 226 113 113 113 113 113 57 57 57 4522010 3,516 397 227 227 113 113 113 113 113 57 57 57 4541: Leiognathidae; 2: Terapon spp.; 3: Gerres spp.; 4: Trichiuridae; 5: Platycephalidae; 6: Tetraodontidae; 7: Soleidae; 8: Bramidae; 9: Brachyura; 10: Clupeidae; 11: Mullidae; 12: Squillidae; 13: Others

174

Appendix Table A6: Catch composition (in tonnes) of Saudi Arabia’s recreational fishery in the Red Sea.

Year Lethrinidae Sparidae Serranidae Others1970 21 16 10 51971 41 31 21 101972 62 47 31 161973 83 62 41 211974 103 78 52 261975 124 93 62 311976 145 109 72 361977 166 124 83 411978 186 140 93 471979 207 155 103 521980 228 171 114 571981 248 186 124 621982 269 202 134 671983 290 217 145 721984 310 233 155 781985 331 248 166 831986 352 264 176 881987 372 279 186 931988 393 295 197 981989 414 310 207 1031990 434 326 217 1091991 455 341 228 1141992 476 357 238 1191993 497 372 248 1241994 517 388 259 1291995 538 403 269 1341996 559 419 279 1401997 579 434 290 1451998 600 450 300 1501999 610 458 305 1532000 625 468 312 1562001 644 483 322 1612002 669 502 334 1672003 696 522 348 1742004 723 542 362 1812005 749 562 375 1872006 773 580 386 1932007 795 596 397 1992008 815 611 408 2042009 835 626 418 2092010 855 641 428 214

Saudi Arabia - Tesfamichael and Rossing 175

Appendix Table A7: Reconstructed catch (in tonnes) of Saudi Arabia in the Red Sea by sectors and its comparison to the data reported by FAO on behalf of Saudi Arabia. Year FAO landings Reconstructed total catch Industrial Artisanal Subsistence Recreational Discards

1950 1,582 7,433 0 5,821 1,611 0 01951 1,582 7,433 0 5,821 1,611 0 01952 2,637 7,433 0 5,821 1,611 0 01953 2,110 7,433 0 5,821 1,611 0 01954 2,637 7,616 0 5,964 1,652 0 01955 2,637 7,799 0 6,107 1,692 0 01956 2,901 7,982 0 6,250 1,732 0 01957 4,219 8,165 0 6,393 1,772 0 01958 4,219 8,348 0 6,536 1,813 0 01959 5,274 8,532 0 6,679 1,853 0 01960 5,274 8,715 0 6,821 1,893 0 01961 6,320 8,898 0 6,964 1,934 0 01962 6,451 9,081 0 7,107 1,974 0 01963 6,583 9,264 0 7,250 2,014 0 01964 6,336 8,275 0 6,982 1,292 0 01965 7,327 9,535 0 8,057 1,478 0 01966 7,816 10,147 0 8,587 1,559 0 01967 8,426 10,906 0 9,244 1,663 0 01968 9,220 11,898 0 10,099 1,799 0 01969 10,380 13,354 0 11,352 2,002 0 01970 10,380 13,377 0 11,346 1,979 52 01971 10,380 13,399 0 11,340 1,956 103 01972 10,654 13,771 0 11,631 1,984 155 01973 10,928 14,122 0 11,904 2,011 207 01974 11,203 14,502 0 12,206 2,037 259 01975 12,130 14,869 0 12,498 2,061 310 01976 12,288 15,221 0 12,775 2,084 362 01977 12,025 15,237 0 12,765 2,058 414 01978 13,158 19,176 0 16,141 2,570 466 01979 12,900 16,928 0 14,182 2,228 517 01980 11,924 15,545 0 12,967 2,009 569 01981 13,150 17,092 0 14,304 2,167 621 01982 14,228 20,993 1,169 14,311 2,138 672 2,7031983 14,151 20,735 1,927 13,478 1,967 724 2,6401984 15,624 23,004 2,684 14,356 2,125 776 3,0631985 22,477 31,376 3,442 20,946 3,168 828 2,9941986 23,972 33,141 4,200 21,811 3,252 879 2,9991987 31,549 40,138 4,957 27,778 4,082 931 2,3901988 31,064 44,163 4,079 30,000 4,345 983 4,7561989 32,291 43,304 5,274 30,000 4,281 1,034 2,7141990 29,368 40,401 4,610 27,778 3,905 1,086 3,0221991 30,044 44,500 5,591 27,778 3,846 1,138 6,1481992 31,279 41,921 5,995 27,778 3,787 1,190 3,1731993 33,219 44,525 5,929 30,000 4,026 1,241 3,3291994 34,147 49,503 6,824 30,000 3,962 1,293 7,4241995 24,561 40,353 7,356 17,204 2,239 1,345 12,2091996 24,219 37,766 7,098 17,121 2,192 1,397 9,9591997 26,230 42,108 8,411 19,356 2,435 1,448 10,4571998 25,088 39,500 7,417 19,396 2,400 1,500 8,7871999 22,142 40,500 7,382 21,792 2,638 1,525 7,1632000 22,445 37,485 7,348 20,988 2,496 1,561 5,0922001 24,130 39,431 7,313 22,991 2,685 1,611 4,8312002 23,988 38,497 7,278 21,413 2,456 1,672 5,6782003 21,859 37,820 7,244 20,393 2,295 1,740 6,1482004 20,422 29,180 7,209 14,709 1,626 1,808 3,8282005 23,315 34,396 7,535 17,524 1,890 1,873 5,5742006 23,440 34,329 7,618 17,574 1,857 1,932 5,3482007 26,495 38,206 8,942 19,744 2,029 1,987 5,5042008 27,634 38,406 8,971 19,872 2,002 2,038 5,5222009 27,207 38,601 9,000 20,000 1,973 2,088 5,5402010 26,257 38,796 9,029 20,128 1,944 2,138 5,558

176

Appendix Table A8. Reconstructed catch (in tonnes) of Saudi Arabia in the Red Sea by components.Year Reported Unreported Discards

1950 1,056 6,377 01951 1,056 6,377 01952 1,861 5,572 01953 1,894 5,539 01954 1,891 5,725 01955 1,921 5,878 01956 2,056 5,926 01957 1,901 6,264 01958 1,932 6,417 01959 1,918 6,614 01960 1,949 6,766 01961 2,295 6,603 01962 2,343 6,738 01963 2,391 6,873 01964 2,301 5,973 01965 2,661 6,874 01966 2,838 7,308 01967 3,060 7,846 01968 3,348 8,549 01969 3,770 9,584 01970 3,770 9,607 01971 3,770 9,630 01972 3,869 9,901 01973 3,969 10,153 01974 4,069 10,433 01975 4,168 10,701 01976 4,268 10,953 01977 4,268 10,970 01978 5,397 13,779 01979 4,740 12,188 01980 4,330 11,214 01981 8,095 8,997 01982 9,042 9,248 2,7031983 9,438 8,657 2,6401984 10,545 9,396 3,0631985 19,588 8,795 2,9941986 23,212 6,929 2,9991987 27,974 9,775 2,3901988 28,460 10,947 4,7561989 29,958 10,632 2,7141990 26,899 10,480 3,0221991 27,758 10,594 6,1481992 28,313 10,435 3,1731993 30,522 10,673 3,3291994 31,803 10,275 7,4241995 21,839 6,305 12,2091996 21,959 5,848 9,9591997 23,819 7,831 10,4571998 23,249 7,464 8,7871999 24,015 9,322 7,1632000 22,631 9,761 5,0922001 25,516 9,084 4,8312002 24,561 8,258 5,6782003 23,440 8,232 6,1482004 19,847 5,506 3,8282005 22,519 6,303 5,5742006 22,504 6,478 5,3482007 25,576 7,126 5,5042008 24,332 8,552 5,5222009 24,840 8,221 5,5402010 24,085 9,153 5,558

Saudi Arabia - Tesfamichael and Rossing 177Appendix Table A9. Composition of the total catch (in tonnes) of Saudi Arabia’s fisheries in the Red Sea by major taxa.Year 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 161950 1,622 594 1,114 669 0 160 891 297 594 520 343 364 0 1 0 01951 1,622 594 1,114 669 0 160 891 297 594 520 343 364 0 1 0 01952 1,622 594 1,114 669 0 160 891 297 594 520 343 364 0 1 0 01953 1,622 594 1,114 669 0 160 891 297 594 520 343 364 0 1 0 01954 1,663 609 1,142 685 0 164 914 305 609 533 351 373 0 1 0 01955 1,704 624 1,170 702 0 168 936 312 624 546 360 382 0 1 0 01956 1,744 639 1,198 719 0 172 958 319 639 559 369 391 0 1 0 01957 1,785 654 1,226 735 0 177 981 327 654 572 377 400 0 1 0 01958 1,825 669 1,254 752 0 181 1,003 334 669 585 386 410 0 1 0 01959 1,866 683 1,281 769 0 185 1,025 342 683 598 394 419 0 1 0 01960 1,906 698 1,309 786 0 189 1,047 349 698 611 403 428 0 1 0 01961 1,947 713 1,337 802 0 193 1,070 357 713 624 411 437 0 1 0 01962 1,987 728 1,365 819 0 197 1,092 364 728 637 420 446 0 1 0 01963 2,028 743 1,393 836 0 201 1,114 371 743 650 429 455 0 1 0 01964 1,802 660 1,238 743 0 178 990 330 660 578 413 404 0 1 0 01965 2,080 762 1,428 857 0 206 1,143 381 762 667 477 467 0 1 0 01966 2,214 811 1,521 913 0 219 1,217 406 811 710 509 497 0 1 0 11967 2,383 873 1,637 982 0 236 1,309 436 873 764 549 535 0 1 0 11968 2,603 953 1,788 1,073 0 257 1,430 477 953 834 600 584 0 1 0 11969 2,925 1,071 2,009 1,205 0 289 1,607 536 1,071 937 676 656 0 2 0 11970 2,920 1,090 2,005 1,213 0 289 1,604 535 1,069 936 676 655 0 17 0 11971 2,914 1,109 2,002 1,222 0 288 1,601 534 1,067 934 676 654 0 33 0 11972 2,986 1,156 2,051 1,261 0 295 1,641 547 1,094 957 694 670 0 48 0 11973 3,057 1,203 2,100 1,301 0 302 1,680 560 1,120 980 711 686 0 64 0 11974 3,128 1,249 2,148 1,341 0 309 1,719 573 1,146 1,003 729 702 0 79 0 11975 3,199 1,296 2,197 1,380 0 316 1,757 586 1,172 1,025 747 718 0 95 0 11976 3,269 1,342 2,245 1,419 0 323 1,796 599 1,197 1,048 765 733 0 110 0 11977 3,263 1,361 2,241 1,427 0 323 1,793 598 1,195 1,046 765 732 0 126 0 11978 4,119 1,695 2,829 1,790 0 407 2,263 754 1,509 1,320 968 924 0 142 0 11979 3,610 1,529 2,480 1,591 0 357 1,984 661 1,322 1,157 850 810 0 157 0 11980 3,292 1,434 2,261 1,471 0 326 1,809 603 1,206 1,055 776 739 0 172 0 11981 4,100 1,391 2,550 1,601 0 405 1,400 864 1,031 1,041 976 684 0 187 0 21982 4,113 1,472 2,675 1,614 1,710 576 1,404 895 1,029 1,047 980 684 466 209 0 1971983 4,333 1,319 2,719 1,525 1,670 783 773 1,066 688 880 1,039 523 455 231 0 1951984 4,847 2,126 2,686 1,970 1,938 999 1,084 1,207 530 643 703 363 528 256 0 2281985 7,437 3,953 3,441 3,330 1,894 1,439 1,964 1,830 484 502 436 248 516 283 0 2261986 7,748 4,174 3,695 3,470 1,897 1,653 2,048 1,932 503 529 458 259 517 306 0 2281987 9,845 5,219 4,672 4,372 1,512 2,068 2,602 2,450 639 671 583 330 412 332 0 1881988 10,565 5,471 4,734 4,697 3,009 1,828 2,788 2,563 689 705 619 352 820 336 0 3541989 10,590 5,620 5,011 4,710 1,717 2,204 2,798 2,632 687 721 629 354 468 366 0 2131990 9,777 5,215 4,566 4,377 1,912 1,951 2,583 2,415 635 662 580 327 521 374 0 2321991 9,772 5,266 4,640 4,382 3,890 2,057 2,582 2,432 634 666 583 327 1,060 394 0 4571992 9,780 5,361 4,802 4,392 2,007 2,279 2,587 2,471 633 676 588 329 547 418 0 2471993 10,527 5,716 5,081 4,722 2,106 2,330 2,783 2,639 682 722 632 353 574 433 0 2581994 10,513 5,744 5,108 4,725 4,697 2,374 2,780 2,643 681 723 633 353 1,280 451 0 5511995 3,312 3,423 3,054 2,373 7,724 4,224 1,008 1,007 370 369 341 596 2,105 687 0 8961996 3,436 4,424 3,610 3,785 6,300 1,876 1,005 1,029 368 401 340 463 1,717 702 0 7331997 4,233 4,370 3,837 3,405 6,616 2,248 1,295 1,186 415 429 388 523 1,803 759 0 7791998 5,393 3,863 3,364 3,684 5,559 2,442 1,266 1,140 413 376 381 519 1,515 765 0 6531999 4,086 4,622 3,800 4,280 4,532 3,335 1,361 1,481 365 665 531 557 1,235 787 0 5422000 3,943 2,439 947 1,451 3,222 3,419 184 1,089 351 630 515 300 83 483 1,200 3952001 4,295 2,606 759 1,637 3,057 3,512 446 424 384 643 560 374 103 508 1,260 3772002 4,000 2,533 676 1,549 3,592 3,370 150 481 357 711 523 291 5 503 1,066 4362003 3,807 2,582 1,205 1,253 3,890 3,278 199 933 339 73 500 283 39 537 1,118 4692004 2,789 2,148 784 1,489 2,422 3,140 167 349 198 59 344 146 5 557 715 2812005 2,953 2,582 956 1,498 3,526 3,061 282 560 216 50 494 219 11 564 1,019 4552006 2,269 2,519 761 1,547 3,383 3,335 160 425 185 35 513 284 1 583 1,121 3932007 2,898 2,809 1,080 1,807 3,482 4,222 207 538 259 65 710 217 5 596 1,200 3992008 2,911 2,797 850 1,475 3,494 4,237 147 563 261 80 703 316 2 615 1,107 4192009 2,923 2,722 807 1,574 3,505 4,252 201 450 262 63 708 266 44 630 1,286 4202010 2,936 2,830 816 1,483 3,516 4,266 193 525 263 61 712 280 3 645 1,150 421

1: Scomberomorus commerson; 2: Lethrinidae; 3: Carangidae; 4: Serranidae; 5: Leiognathidae; 6: Rastrelliger kanagurta; 7: Lutjanidae; 8: Sphyraena spp.; 9: Valamugil seheli; 10: Scombridae; 11: Elasmobranchii; 12: Scaridae; 13: Penaeidae; 14: Sparidae; 15: Lethrinus lentjan; 16: Terapon spp.

178

Table A9 continuedYear 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 321950 0 7 0 0 0 1 6 0 0 0 0 0 5 0 0 2431951 0 7 0 0 0 1 6 0 0 0 0 0 5 0 0 2431952 0 7 0 0 0 1 6 0 0 0 0 0 5 0 0 2431953 0 7 0 0 0 1 6 0 0 0 0 0 5 0 0 2431954 0 7 0 0 0 1 6 0 0 0 0 0 6 0 0 2471955 0 7 0 0 0 1 6 0 0 0 0 0 6 0 0 2501956 0 7 0 0 0 1 6 0 0 0 0 0 6 0 0 2541957 0 7 0 0 0 1 7 0 0 0 0 0 6 0 0 2571958 0 8 0 0 0 1 7 0 0 0 0 0 6 0 0 2601959 0 8 0 0 0 1 7 0 0 0 0 0 6 0 0 2641960 0 8 0 0 0 1 7 0 0 0 0 0 6 0 0 2671961 0 8 0 0 0 1 7 0 0 0 0 0 7 0 0 2711962 0 8 0 0 0 1 7 0 0 0 0 0 7 0 0 2741963 0 8 0 0 0 1 7 0 0 0 0 0 7 0 0 2771964 0 7 0 0 0 1 7 0 0 0 0 0 6 0 0 2581965 0 9 0 0 0 1 8 0 0 0 0 0 7 0 0 2821966 0 9 0 0 0 1 8 0 0 0 0 0 7 0 0 2931967 0 10 0 0 0 1 9 0 0 0 0 0 8 0 0 3011968 0 11 0 0 0 1 10 0 0 0 0 0 9 0 0 3141969 0 12 0 0 0 1 11 0 0 0 0 0 10 0 0 3351970 0 12 0 0 0 1 11 0 0 0 0 0 10 0 0 3341971 0 12 0 0 0 1 11 0 0 0 0 0 10 0 0 3321972 0 12 0 0 0 1 11 0 0 0 0 0 10 0 0 3371973 0 13 0 0 0 1 11 0 0 0 0 0 10 0 0 3241974 0 13 0 0 0 1 12 0 0 0 0 0 10 0 0 3401975 0 13 0 0 0 1 12 0 0 0 0 0 11 0 0 3451976 0 14 0 0 0 1 12 0 0 0 0 0 11 0 0 3351977 0 14 0 0 0 1 12 0 0 0 0 0 11 0 0 3311978 0 17 0 0 0 1 15 0 0 0 0 0 14 0 0 4081979 0 15 0 0 0 1 13 0 0 0 0 0 12 0 0 3771980 0 14 0 0 0 1 12 0 0 0 0 0 11 0 0 3631981 0 34 1 0 0 3 30 0 0 0 0 0 28 0 0 7671982 47 160 85 0 0 5 51 0 0 0 110 0 58 0 0 1,4091983 93 190 117 0 0 9 88 0 0 0 108 0 72 0 0 1,8641984 139 222 154 0 0 11 108 0 0 0 125 0 78 0 0 2,0691985 191 253 185 0 0 15 147 0 0 0 122 0 94 0 0 2,3971986 285 272 217 0 0 17 171 0 0 0 122 0 99 0 0 2,5521987 352 285 242 0 0 22 214 0 0 0 98 0 111 0 0 2,9401988 252 361 236 0 0 18 182 0 0 0 194 0 136 0 0 3,2701989 372 311 259 0 0 23 228 0 0 0 111 0 120 0 0 3,1771990 317 301 235 0 0 20 200 0 0 0 123 0 115 0 0 2,9801991 351 438 318 0 0 22 213 0 0 0 251 0 148 0 0 3,6361992 422 336 295 0 0 25 240 0 0 0 129 0 121 0 0 3,2581993 414 347 295 0 0 25 243 0 0 0 136 0 128 0 0 3,3971994 429 518 386 0 0 25 249 0 0 0 303 0 170 0 0 4,1861995 407 788 473 0 0 797 311 0 58 0 498 0 283 0 0 5,2721996 417 639 432 0 0 695 262 0 80 0 406 0 212 0 0 4,4551997 512 820 496 0 0 1,012 418 0 138 0 427 0 329 0 0 5,7011998 512 659 424 0 0 598 326 0 145 0 359 0 249 0 0 4,9211999 603 642 362 0 0 636 311 0 194 0 292 0 254 0 0 5,0552000 312 256 331 280 721 614 311 725 200 628 208 484 228 283 244 11,0412001 345 197 326 670 636 669 327 728 209 815 197 585 240 430 367 11,7792002 397 363 337 817 896 623 310 832 104 731 232 18 236 516 563 11,3102003 476 295 342 339 801 593 299 1,467 592 760 251 522 233 240 509 9,6272004 461 163 264 575 596 272 211 458 554 528 156 601 136 303 366 7,9522005 583 228 422 958 855 263 218 614 710 668 228 558 181 367 480 8,6752006 515 218 351 1,108 801 305 250 551 774 677 218 677 195 268 495 9,4242007 555 234 376 1,052 847 298 545 494 884 785 225 390 243 375 475 9,9422008 622 236 377 1,006 824 292 449 605 938 612 225 527 204 597 555 10,3862009 615 239 378 1,160 860 294 451 578 1,017 514 226 719 204 714 354 10,1892010 588 239 379 1,104 718 295 452 711 1,027 675 227 608 205 721 306 10,464

17: Sepiidae; 18: Gerres spp.; 19: Brachyura; 20: Sphyraena barracuda; 21: Penaeus semisulcatus; 22: Siganus spp.; 23: Netuma thalassina; 24: Epinephelus tauvina; 25: Euthynnus affinis; 26: Decapterus russelli; 27: Trichiuridae; 28: Atule mate; 29: Clupeidae; 30: Carangoides bajad; 31: Gnathanodon speciosus; 32: Others

Jordan and Israel - Tesfamichael et al. 179

preliminary reConstruCtion of fisheries CatChes of Jordan and israel in the inner gulf of aqaba, red sea, 1950-20101

Dawit Tesfamichaela,b, Rhona Govendera and Daniel Paulya

a Sea Around Us, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada

b Department of Marine Sciences, University of Asmara, Asmara, Eritrea.d.tesfamichael@fisheries.ubc.ca, rhonag @gmail.com; d.pauly @fisheries.ubc.ca

abstraCt

The fisheries catch taken within the small Exclusive Economic Zones (EEZ) of Jordan and Israel, in the inner Gulf of Aqaba, Red Sea, was reconstructed from a variety of government and non-government sources for the years 1950-2010, and compared with the catch these two countries report annually to the Food and Agriculture Organization of the United Nations (FAO). The different sectors of the fisheries in each country are treated separately and the composition of the catches estimated. There is a strong discrepancy between the reconstructed catch and FAO data, in part due to these countries’ fleet having operated outside of their EEZ (Israel in what are now Eritrean waters, from 1958 to the early 1970s; Jordan in Saudi Arabian waters, from 1950 to 1984), and to an overall lack of interest in collecting data for what are rather small operations, with very low catch level. For Jordan, the catch was around 150 t·year-1 from 1950 to the mid-1960s. This catch then declined, due to conflicts in the area, and started to increase again in the mid-1980s, with some fluctuations. The highest catch of 330 t was achieved in 2009. Israel’s total catch in its Red Sea EEZ was less than 100 t·year-1 in the early 1950s, then increased until it reached its peak of around 300 t·year-1 in the early 1980s, and it later decreased to around 100 t·year-1 in the late 2000s. Overall, the estimated reconstructed catch of Jordan from 1950 to 2010 was 1.7 times what is reported in the FAO database and for Israel it was 1.4 times. The reconstruction exercise, with its explicit stated procedures and assumptions, accounting all the sectors comprehensively, can be a good starting point to improve the quality of the data for these countries and for better management of resources, which are under continuous pressure from fishing and other developments in the region.

introduCtion

The Hashemite Kingdom of Jordan and the State of Israel share the north-eastern tip of the Gulf of Aqaba, Red Sea, with small, quasi-Exclusive Economic Zones of about 95 and 29 km2, respectively (MoE, 2002; Al Ouran, 2005) (Figure 1). This unique region harbors the world’s northernmost coral reef ecosystem (Khalaf and Disi, 1997; MoE, 2002) and is characterized as hypersaline, with waters averaging 42 psu (Sneh and Friedman, 1985). This is in part due to its semi-enclosed nature (Hargreaves, 1981), which allows for a complete renewal of the water basin only once every 20 years (Lapidoth-Eschelbacher, 1982). These factors not only lead to a high degree of endemism in the region, but also increase the susceptibility to pollution, which, jointly with overfishing, affect the diversity and abundance of the fish stocks, as well as the health of the coral reefs (Tellawi, 2001). The two major settlements in the gulf are Aqaba and Eilat in Jordan and Israel, respectively. The two cities have major ports for their respective countries in the Red Sea. For Jordan, the only access to the sea is through the Red Sea, which makes the port of Aqaba its sole port. The fish landing site of Jordan is at Sidra, near the town of Aqaba, where fish are sold directly to merchants, hotels and restaurants based in Aqaba (PERSGA, 2002).

In 1949, Israel conducted an experimental fishing expedition from the port of Eilat which confirmed the potential for a commercial fishery in the region, previously exploited by poorly-documented traditional fisheries. Due to the limited area available for fishing (Farid, 1984), the fisheries of both countries soon expanded beyond the inner Gulf of Aqaba. Jordanian fishers engaged in fishing along the coast of neighboring Saudi Arabia (PERSGA, 2002), while Israel ventured further south to Eritrea beginning in 1957 (Ben-Tuvia, 1968).1 Cite as: Tesfamichael, D., Govender, R. and Pauly, D. (2012) Preliminary reconstruction of fisheries catches of Jordan and Israel in the inner Gulf of Aqaba, Red Sea, 1950-2010. pp. 179-204. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosysytem by countries (1950-2010). Fisheries Centre Research Reports 20(1). Fisheries Centre, University of British Columbia [ISSN 1198-6727].

Figure 1. The Gulf of Aqaba, Red Sea, with shelf areas and Exclusive Economic Zones (EEZ) of Jordan and Israel.

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The predominant gears utilized by fishers in Israel are beach seines, gill-nets, and trammel nets (Ben-Tuvia, 1968), and the fishing boats range in length from 7 to 11 m (Shapiro, 2007). In Jordan, beach seines, gill-nets, and trammel nets are also used, along with hand lines and longlines, various traps, and (illegally) spear guns and explosives. The main species targeted by the Jordanian fleet are snappers (Family Lutjanidae), groupers (Family Serranidae) and emperors (Family Lethrinidae), along with numerous incidental species (Khalaf and Disi, 1997). The catch, which is not iced, is landed from boats ranging from 5.5 to 11 meters (PERSGA, 2002), and sold immediately to merchants in the port of Aqaba.

In addition to fishing, several other anthropogenic factors have been linked to impact the Jordanian waters over the past few decades. Commercial fish farms, sewage overflow, and phosphate emissions from nearby industrial terminals have led to increasing levels of eutrophication (MoE, 2002; Al Ouran, 2005), which is having an adverse effect on the coral reefs. For example, in 1996, 70% of the coral were reported to be alive, yet in 2002 the reef was comprised of only 30% live coral in Jordan (MoE, 2002). These unfavorable marine conditions, coupled with fishing (Tellawi, 2001), are responsible for the increase of pressure on the ecosystem. The extent of the impact of these pressures needs to be studied and monitored. Some of the impacts are obvious, for example in 2006 half of all the Jordanian fishing boats were permanently anchored (IRIN, 2006).

The state of the fisheries in the inner Gulf of Aqaba cannot be assessed using only the catch data which Israel and Jordan submit to the Food and Agriculture Organization (FAO) of the United Nations (Pauly and Zeller, 2003). Rather, as for other countries and territories, it is necessary to ‘reconstruct’ historic catch trends to acquire a minimum understanding of the evolution of these fisheries (Zeller et al., 2006; Zeller et al., 2007).

materials and methods

The total marine catches by Jordan and Israel within their territorial waters in the Gulf of Aqaba were estimated by country for the period from 1950 to 2010. The required data were primarily obtained from government reports and the scientific literature. The fishery sectors in each country are treated separately, and for each country, the reconstructed total catch is divided into reported and unreported catch. Since the fisheries of the two countries are dominated by artisanal fisheries, which use selective gear (PERSGA, 2002), there is no discarded catch or, if it exists, it is negligible. Emphasis was given to ‘hard’ estimates of the catch of distinct fisheries, which were used as ‘anchor points’ (Zeller et al., 2006; Zeller et al., 2007) between which estimates for missing years could be obtained by interpolation.

Jordan

Artisanal fishery

For some years, the Jordanian Red Sea fisheries data were obtained from peer-reviewed articles, government reports and grey literature (Table 1). The catch estimates for years without sources were derived by interpolation between years with known catch. Also, the 1965 value was carried back to 1950, as the fishing fleet and environmental conditions have experienced few changes from 1950 to 1964 (Barrania, 1979). After 1985, the fishery statistical reporting ceased and the catch values available were based on researchers from Jordanian universities (PERSGA, 2002). These values match what are available in the FAO database for the later years. Thus, the FAO values were used from 1998 to 2010.

The landings in the Jordanian port of Aqaba prior to 1985 included both catches in Jordanian waters and catches from Saudi Arabian waters up to 300 km south of Aqaba. In 1985, access to these southern fishing grounds ceased, as did the collection of fisheries statistics by the government (PERSGA, 2002). Until 1984, approximately half of the catch was obtained in Saudi Arabian waters (Barrania, 1979) and thus only half of the reconstructed catch was applied to the Jordanian catch. The other half, which was caught in Saudi waters was accounted in the Saudi Arabia’s catch reconstruction in its Red Sea EEZ (see Tesfamichael and Rossing, 2012 this volume).

In addition to fishing in foreign waters, there are mentions of high spoilage rates due to low handling standards and insufficient amount of ice to preserve the catch. Estimated rates of spoilage ranged from 0.4 to 54% (Table 2) (Barrania, 1979). The values from 1972 to 1978 included spoilage, whereas the data for the previous years did not. A conservative estimate of 19%, calculated by taking the average spoilage values from 1972 to 1976, was added to the catch in all years prior to 1972.

Table 2. Percentage of spoiled fish in the Jordanian catch.Year % 1972 54.11973 1.71974 10.81975 27.91976 1.11977 n.a.1978 0.4

Table 1. Sources for estimating the Jordanian marine catch in the Gulf of Aqaba.

Year Catch (t) Source1965 180 Barrania (1979)1966 180 Ben-Tuvia (1968)1972 143 Barrania (1979)1973 93 Barrania (1979)1974 103 Barrania (1979)1975 90 Barrania (1979)1976 49 Barrania (1979)1977 31 Barrania (1979)1978 31 Barrania (1979)1983 100 Chakraborty (1984)1985 125 Chesrown (2004)1993 103 FAO (2003)1995 150 FAO (2003)1998 120 FAOa, PERGSA (2002)1999 160 FAO2000 150 FAO2001 170 FAO2002 176 FAO2003 131 FAO2004 144 FAO2005 160 FAO2006 147 FAO2007 156 FAO2008 150 FAO2009 219 FAO2010 136 FAO

a http://www.fao.org/fishery/topic/16072/en

Jordan and Israel - Tesfamichael et al. 181

Finally, the reconstructed catch was disaggregated into major taxa. There were two sources of catch composition data, one for the early period (Barrania, 1979) and for the later period (1998 – 2010) from the FAO database. The Jordan fishery in the Gulf of Aqaba had two distinct periods before and after 1985. This coincides with the time the fishers were allowed to operate in the waters of neighboring countries, mainly in Saudi waters, or not. When they fished outside their waters, most of the local fishing sector was focused on inshore and coral reef fishes (Barrania, 1979). Once they were prevented from fishing outside of Jordanian waters, in 1985, most of their catch focused on pelagic fishes (PERSGA, 2002). Accordingly, the composition from 1950 to 1984 was calculated based on the data from Barrania (1979). Only local names were available in the report and their corresponding scientific and English common names were obtained from Tesfamichael and Awadh (2012), Fishbase (Froese and Pauly, 2012) and Dr. Dori Edelist (University of Haifa, Israel, pers. comm.). The report by Barrania (1979) had catch composition estimates for only 8 of the taxa in the catch, while the rest were put under ‘others’. However, local names for some of the components of the ‘others’ were available, and we assumed a value of 0.3% for each of the taxa for which we were able to find the corresponding scientific names in our sources (Italics in Table 3); only the rest were categorized under ‘others’. The FAO catch composition was used from 1998 to 2010 (Table 4). From 1990 to 1997, the values of 1998 were used. From 1985 to 1989, we interpolated the catch composition to allow a relatively smoother transition of the fishery from inshore coral reef to pelagic. Although there is evidence that the fishery switched its target fishes from reef-associated to pelagic, it is unrealistic to assume the shift happened within a year, as there are capital investment and technical issues that need to be considered. We allowed 5 years for the shift to happen.

Subsistence fishery

The catch of the subsistence fishery consists of two components; the first is the catch of small boats mainly for direct consumption by the fishers’ families and communities. A small portion of their catch may be sold or exchanged in kind. These catches are not reported at all. The second component of the subsistence catch is part of the catch of the bigger boats that is consumed by the crew and given to family and friends. For the small boats it was calculated based on a survey (Barrania, 1979), where it was estimated that a total of about 12 boats made day trips and caught 6 – 10 kg (average 8 kg∙day-1). We assumed the total number of fishing days per year to be 250 and thus could compute the total catch to be 24 t·year-1. For the bigger boats, we assumed that 10% of their catch was consumed by crew and/or given to family members. The percentages used to calculate the artisanal fishery catch composition were used to calculate the composition of subsistence catch composition as well, because they employ similar gears.

Table 3. Catch composition (%) for Jordanian artisanal fishery from 1950 to 1984 (Barrania 1979).Arabic name Scientific name Common name Family Catch %Sho’or Lethrinidae Emperors Lethrinidae 57.2Fares Lutjanidae Snappers Lutjanidae 18.4Segan Siganidae Rabbit fishes Siganidae 3.0Reem Carangoides spp. Trevallies Carangidae 2.9Freeden Polysteganus coeruleopunctatus Blueskin seabream Sparidae 2.6Bohar Lutjanus bohar Two-spot red snapper Lutjanidae 1.7Gerbeden Sparidae Porgies Sparidae 1.7Sultan Ibrahim Mullidae Goat fish Mullidae 0.4Reshan Gerres oyena Common silver-biddy Gerreidae 0.3a

Qamar Gymnocranius grandoculis Blue-lined large-eye bream Lethrinidae 0.3Hereed Scaridae Parrotfish Scaridae 0.3Dagham Epinephelus spp. Grouper Serranidae 0.3Shran Cephalopholis miniata Coral hind Serranidae 0.3Tween Serranidae Grouper Serranidae 0.3Othersb — — — 10.2a Italic values are assumed percentages, bOthers include taxa with local names Aisoun, Boas and Track.

Table 4. Catch composition (%) of Jordanian artisanal fishery from 1998 to 2010 based on FAO data. Common name Scientific name 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010Emperors Lethrinidae 1.66 1.25 0.67 1.18 0.57 0.76 0.69 1.25 0.68 1.28 2.00 4.11 5.15Frigate/bullet tunas Auxis spp. 1.66 2.50 1.33 2.94 2.84 3.05 2.78 3.13 2.72 3.21 4.00 4.11 4.41Fusiliers Caesionidae 12.47 11.25 11.31 8.82 6.82 9.92 8.33 8.75 7.48 8.33 8.67 6.85 6.62Kawakawa Euthynnus affinis 21.62 22.50 21.96 23.53 22.73 25.19 24.31 25.00 29.93 28.85 28.00 21.00 25.00Longtail tuna Thunnus tonggol 1.66 1.25 1.33 1.76 1.70 1.53 2.08 1.25 1.36 2.56 3.33 5.02 7.35Marine fishes Others 2.49 4.38 4.66 3.53 5.68 6.11 6.94 6.25 4.76 6.41 6.67 9.13 4.41Narrow-barred Spanish mackerel

Scomberomorus commerson

0.21 0.63 0.17 0.59 0.57 0.76 0.69 1.25 1.36 1.28 1.33 3.20 5.15

Scads nei Decapterus spp. 16.63 15.63 16.64 15.29 14.20 16.79 13.89 10.63 10.20 12.82 10.67 12.33 5.88Skipjack tuna Katsuwonus pelamis 29.11 27.50 29.95 30.59 29.55 32.82 31.25 34.38 34.01 28.21 28.67 20.55 20.59Rabbitfishes Siganidae 8.32 7.50 6.66 6.47 4.55 0.00 3.47 3.75 2.72 2.56 2.00 4.57 4.41Tuna-like fishes Scombridae 2.49 2.50 3.33 2.35 7.95 0.00 3.47 2.50 2.04 2.56 2.00 4.57 5.15Yellowfin tuna Thunnus albacares 1.66 3.13 2.00 2.94 2.84 3.05 2.08 1.88 2.72 1.92 2.67 4.57 5.88

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Recreational fishery

A recreational fishery exists in the Jordanian Gulf of Aqaba and it is growing fast (FAO, 2003). However, data on its size and catches do not exist. The recreational fishery catch was estimated using the population of Aqaba, the main coastal settlement on the Jordanian coast, taken from www .populstat.info and Wikipedia (2012). Data were not available for the whole time series, and interpolation was used to fill the gaps (Table 5). The recreational fishery was assumed to start in 1974, after the war between Israel and Arab countries in 1973, so zero was assigned from 1950 to 1973. From 1974 onward, it was calculated using a participation rate of 8%. To derive this rate we started with the regional participation value of 0.12 (Cisneros-Montemayor and Sumaila, 2010). Note the participation ratios in Cisneros-Montemayor and Sumaila (2010) are given for the whole country and as a percentage. In our calculations, we used population size of only Aqaba, the main coastal settlement because the coastal people are the ones to be involved more in recreational fishing than people far from the coast. Therefore the rate of 0.12% was adjusted for the population size of Aqaba using the ratio of Aqaba population to the total Jordanian population from 1974 to 2010, which was 1.5 % (i.e., the total population is 65 times that of Aqaba). Hence the participation ratio was multiplied by 65, making the participation percentage only for Aqaba to be 8%. In addition, we assumed that recreational fishers go fishing a total of 15 days·year-1. As for the catch rate, we assumed a rate of 1 kg·day-1 for 1974 and 0.5 kg·day-1 for 2010. The rate was interpolated between those two years. Finally, the annual recreational fishery estimate was calculated as a product of population, participation ratio, number of days per year, and catch rate. The catch composition of recreational fishery was taken from Saudi Arabia’s recreational fishery in the Red Sea, where emperors accounted for 40%, sea breams 30%, groupers 20% and ‘others’ 10% (Tesfamichael and Rossing, 2012).

Israel

Artisanal fishery

Fishery catch data were obtained from ‘Bamidgeh’, a publication of the Israeli Department of Agriculture for some years between 1954 and 1985, after which we used reports from ‘The Fisheries and Aquaculture of Israel’ (Table 6). The 1954 total catch estimate, from Cohen (1957), was carried back to 1950 as the gear and fishing grounds appear to have remained similar during those years. For periods where data were missing, FAO data were used selectively. The FAO data for Israel have some inconsistency, mainly reports of zero catches for some periods; however we were able to get non-zero estimates from national sources. On the other hand, for some periods, the catch values reported in the FAO database matched the sources from the Israeli fishery administration. It is safe to conclude that Israel reported its fishery catch in the Red Sea accurately to FAO, for some periods, vis-à-vis its national reports. Thus, we used FAO data from 1981 to 1985 because the FAO data and other sources for neighboring years (1979, 1980 and 1986) were the same. Similarly, FAO data were used from 1991 to 2002 and 2008. FAO data were not used for 1955 – 1967, 1969 – 1978, 1987, 1989 – 1990, where FAO data contained numerous zero catches. Instead the catches were estimated using interpolation. For 2009 and 2010, data from Israeli Department of Fisheries Statistical Yearbooks, DoFSY (Dr. Dori Edelist, pers. comm.) were used; these values differed from the FAO dataset.

The composition of the catch, predominantly comprised of snappers (Table 7) was obtained from Sarig (1982) and was used from 1950 to 2005. However, since 2006, the catch composition changed, as pelagic species started to become abundant in the catch. So for 2006–2010, catch composition data obtained from DoFSY (Dr. Dori Edelist, pers. comm.) were used.

Israel fished in Eritrean waters beginning in 1958 (Ben-Tuvia, 1968; Sarig, 1969). Since these catches originated from Eritrean waters, they are reported in the Eritrea catch reconstruction (see Tesfamichael and Mohamud, 2012 this volume for details on this fishery).

Table 5. Population of AqabaYear Pop. (103) Year Pop. (103)1970 15 1993 671979 27 1994 631985 36 1998 801986 37 2002 961989 44 2007 981990 46 2009 109Source: www.populstat.info, except 2007 and 2009 from Wikipedia

Table 6. Data sources for estimating Israel’s catch in the Gulf of Aqaba.

Year Catch (t) Source1954 60 Cohen (1957)1968 200 Ben-Tuvia (1968)1979 250 Sarig (1982)1980 283 Sarig (1982)1981 257 FAOa

1982 76 FAO1983 68 FAO1984 102 FAO1985 150 FAO1986 150 Sarig (1987)1988 130 Anonymyous (1992)1991 35 FAO1992 98 FAO1993 80 FAO1994 110 FAO1995 150 FAO1996 225 FAO1997 171 FAO1998 137 FAO1999 98 FAO2000 120 FAO2001 120 FAO2002 30 FAO2003 30 Snovsky and Shapiro (2004)2004 100 Shapiro (2005)2005 75 Shapiro (2006)2006 75 Shapiro (2007)2007 50 Shapiro (2008)2008 50 FAO2009 70 DoFSYb

2010 40 DoFSY a http://www.fao.org/fishery/topic/16072/en b Based on Israeli Department of Fisheries statistical yearbooks

Jordan and Israel - Tesfamichael et al. 183

Subsistence fishery

Israel publishes its annual fishery statistics for its fishery in the Gulf of Aqaba, and that is also what is reported to FAO, at least for most years. The reports clearly state that the data do not include part of the catch that is consumed by the crew and catch given to families and friends (Snovsky and Shapiro, 2004). This constitutes the subsistence fishery in our report. The subsistence catch in the Israeli Gulf of Aqaba fishery was estimated as a percentage of the artisanal catches. Based on interviews with fishers (Dr. Dori Edelist, pers. comm.), 5% of the total catch of artisanal fishers is consumed by the crew or given freely to family and friends, which was used as an anchor point for 2010. As observed in other Red Sea countries, the ratio is generally higher for earlier years (see the other chapters). We assumed 10% in 1950. The ratio was interpolated from 1950 to 2010. The composition of the subsistence fishery was taken from the ratios of the artisanal fishery.

Recreational fishery

Similar to Jordan, the recreational fishery of Israel in the Gulf of Aqaba was calculated based on the population of its largest coastal city in the Red Sea, Eilat (Table 8). The recreational fishery was assumed to start in 1974, after the 1973 war. A participation ratio of 0.12 was used in the calculations (Cisneros-Montemayor and Sumaila, 2010) and the number of days fished per year was assumed to be 20. Again, similar to Jordan, the participation ratio was adjusted to the population of Eilat, which had an average of a little less than 1% of the total Israeli population from 1974 to 2010. We assumed 1% and multiplied the participation ratio by 100. The catch rate per day was assumed to be 1 kg·day-1 for 1974 and 0.5 kg·day-1 in 2010. Catch rates were interpolated for the intervening years. The catch composition of the recreational fishery was taken from Saudi Arabia’s recreational fishery in the Red Sea, where emperors accounted for 40%, sea breams 30%, groupers 20% and ‘others’ 10% (Tesfamichael and Rossing, 2012).

Comparing reconstructed catches with FAO data

The reconstructed catches , i.e., what were caught in the EEZ’s of the respective countries and excluding what they caught in other countries’ EEZ’s , were compared to the data for the respective country in the FAO database ww w. fao.org/fishery/statistics/software/fishstat/en). Since the subsistence and recreational fisheries were not reported at all, only the reconstructed artisanal catches were compared to the FAO data. In order to be able to compare taxon by taxon, the FAO data, when only totals were given, were divided into the components using the ratios in the reconstructed catches. For Israel, large quantities of brush-tooth lizardfish (Saurida undosquamis) and narrow-barred Spanish mackerel (Scomberomorus commerson) catches were reported in the FAO data mainly from 1965 to 1972, which were higher than the reconstructed total catch. This is the period when Israel fished in Eritrean waters, so they were excluded from the taxon-to-taxon comparison as they were deemed to be caught outside the EEZ. For other taxa, if the amount in the reconstruction was higher than its value in the FAO database, the difference was assigned as ‘unreported catch’; if it was the opposite, then it was ‘over-reported catch’. The part of the reconstructed catch that is accounted in the FAO data is referred as ‘reported catch’ in our result.

results

Jordan

Our results suggest that the catch in Jordanian waters ranged from slightly less than 150 t in 1950 to a maximum of a little more than 300 t in 2009. The lowest catch was towards the second half of the 1970s (Figure 2) and also given in Appendix Table (A1). The total catch showed an increasing trend from its lowest values in the late 1970s until its peak in 2009. In contrast, the data supplied to FAO were lower than the reconstructed total catch for most of the period, except in the early period, where a total of 200 t was reported in the FAO for a few years. These years correspond with the time the Jordanian fishers were fishing outside the Jordanian waters, i.e., mainly in Saudi Arabia. Since the origin of these catch was outside Jordan, we did not include them as Jordanian catch from Jordanian waters in our reconstruction. Instead they were accounted in their country of origin, Saudi Arabia (see Tesfamichael

Table 7. Catch composition (%) of Israel’s artisanal fisheries in the Gulf of Aqaba.

Common name Scientific name 1950-2005 2006-2010Red snapper Lutjanidae 48 10Tuna-like Scombridae 32 30Groupers Serranidae 12 7Jacks and pompanos Carangidae 0 20Swordfish Xiphias gladius 0 10Goatfish Mullidae 0 5Cephalopods Cephalopods 0 5Barracudas Sphyraena spp. 0 3Rabbitfish Siganus spp. 0 2Others Others 8 8

Table 8. Population of Eilat. Year Pop. (103) Year Pop. (103)1972 13 1995 321974 14 1999 401979 19 2000 411983 19 2002 431992 30 2008 471994 33 2010 48Source: http://www.populstat.info/, except 2008 and 2010 from Wikipedia

184

and Rossing, 2012 this volume). Similar to the reconstruction, the highest catch reported in the FAO database was for 2009. The FAO database has zero catches for some years. This is due to a lack of reporting by Jordan to FAO and does not mean that there were no fishery catches. Such data gaps can be very misleading in the assessment and management of fishery (Pitcher et al., 2002). From the late 1990s, the FAO data were equal to the total artisanal fishery, which is the only reported fishery to FAO as subsistence and recreational are not reported at all.

When the reconstructed total catch of Jordan in Jordanian waters is divided into different sectors, the artisanal fishery has the lion’s share with 62%, followed by the subsistence fishery at 20% and the recreational fishery at 18% (Figure 2, Table A1). Jordan does not have an industrial fishery (PERSGA, 2002), therefore, the artisanal fishery has the strongest influence on the pattern of the overall total. The subsistence fishery follows a pattern similar to that of the artisanal fishery because it was calculated as a ratio of the artisanal fishery. The recreational fishery started in 1974 and its contribution became important only in the later years.

The total marine catch within Jordanian waters was found to be 1.7 times the catches reported to the FAO from 1950 to 2010. This can be attributed to two main factors: first there are zero catches for some years in the FAO database. Second, the unreported catch, which consists mainly of subsistence and recreational fisheries, is not included in the FAO database at all. The unreported catch accounted for 52% of the reconstructed total catch. The reported catch (part of the reconstructed catch accounted in the FAO data) represented only 48% of the total catch (Figure 3, Table A2).

There are 21 identified taxonomic groups that made up the total artisanal fishery catch of Jordan in the inner Gulf of Aqaba (Figure 4). The most dominant taxon is emperors (Lethrinidae) at 29%, followed by skipjack tuna (Katsuwonus pelamis) at 15% and kawakawa (Euthynnus affinis) at 12%. Although there are numerous other taxa in the catch, they contribute smaller amounts, hence showing all of them on the composition figure is difficult and superfluous. Thus, the taxa with minor contribution are lumped together with the category ‘others’ in the figure for all sectors in this report. A more detailed taxonomic composition is, however, given in the appendix tables (e.g., see Table A 3 for Jordan’s artisanal fishery). The catch composition of Jordan’s artisanal fishery exhibits two distinct phases, one before 1985 and the second after 1990. The earlier catch composition consisted mainly of coral reef-associated fishes, without a component of pelagic taxa. In contrast, the later period consisted of mainly pelagic taxa, with the reef-associated fishes being less abundant. Based on the sources for the composition (see methods), a reasonable explanation for the shift can be that in the early period, when Jordanian fishers used to venture out to neighboring countries, their target was coral reef-associated fishes. Therefore, the gear and technology they used must have influenced the fishers fishing in Jordanian waters to also target coral reef-associated fishes and/or the fishers visiting neighboring waters may also spend time fishing domestic waters. In addition, even if the reef-associated total catch was not high compared to the total catch from pelagic resources in the later years (see Figure 4, the total catch after 1985 is

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (t

)

0

150

300

Reported

Unreported

Figure 3. Total catch of the Jordanian fishery in the Gulf of Aqaba by components from 1950 to 2010. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.

Figure 4. Catch composition of the Jordanian artisanal fishery in the Gulf of Aqaba from 1950 to 2010.

Figure 2. Total catch of the Jordanian fishery in the Gulf of Aqaba by sectors and the total catch Jordan reported to FAO from 1950 to 2010.

Jordan and Israel - Tesfamichael et al. 185

generally higher than the period before), it would have been a good addition to their catches from the neighboring waters. However, later when they were not allowed to fish in neighboring waters, they had to focus on Jordanian resources and target the more abundant resource which is the pelagic fishes.

The catch composition of the subsistence fishery is similar to the artisanal fishery (Figure 5, Table A4), as the same catch composition ratios were used. However, it does not show strong fluctuations like the artisanal fishery; it stays more or less stable. This is quite realistic for a subsistence fishery. As its name indicates, this is catch consumed by locals, is a source of food security, and it is usually less affected by external factors (e.g., market and politics) compared to the other fisheries. The catch composition of the recreational fishery has only three identified taxa (Figure 6, Table A5). The composition of the total catch of Jordan in the Red Sea strongly resembles that of the artisanal fishery (Figure 7, Table A6), simply because the artisanal fishery has the highest contribution to the total catch.

Israel

The reconstructed total catch of Israel in the Gulf of Aqaba increased continuously from its low value of a little more than 60 t·year-1 at the beginning of the 1950s until it reached its peak of 346 t in 1980 (Figure 8, Table A7). After 1980, it exhibited more fluctuations than in earlier years and stayed at relatively lower values, except for a smaller peak in 1996. Compared to Jordan, Israeli catches showed lower fluctuations. There are large discrepancies between the reconstructed catch and the data submitted to FAO by Israel, with the latter ranging from zero catches from 1950 to 1964 to a peak of 1,000 t in 1965. While the early catches of zero show the absence of reporting and should not mean there was no fishing. The high values are what Israel caught in the whole Red Sea, including outside its EEZ in the Eritrean EEZ, because catch statistics by the FAO are categorized by FAO statistical area (to which the whole Red Sea falls into one category) and fishing country, without any information indicating EEZ area. However, our catch reconstruction focuses on the use of catch data for ecosystem management, which makes it practical to report by the EEZ the catch originated, with clear indication who caught the fish as well. Thus, the Israeli catches from Eritrean waters are reported in the catch reconstruction of Eritrea (see Tesfamichael and Mohamud, 2012 this volume). Starting 1979, the FAO data matched with the artisanal catches, the only sector reported to FAO, except when the FAO values were zero, which again was due to lack of reporting. The artisanal sector had the highest contribution to the reconstructed total catch of the Israeli fishery in the Gulf of Aqaba, contributing 76%. The second was recreational fishery with 18%; the subsistence fishery (6%) was last (Figure 8). Artisanal and subsistence fisheries operated for the entire period, 1950 – 2010, while the recreational fishery began only in 1974. As in Jordan, the pattern of the total catch is shaped mainly by the artisanal fishery.

Overall, the reconstructed catch was 1.4 times the catches reported to FAO. If the years where Israel was fishing in Eritrean waters, from 1958 to 1968, are excluded from the analysis, the reconstructed catch is 1.8 times the catches reported to FAO. The unreported catch accounts for 62% of the reconstructed catch. The reported catch (part of the reconstructed catch accounted in the FAO data) represented only 38% (Figure 9, Table A8).

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (t

)

0

30

60

Lethrinidae

Sparidae

Serranidae

Others

Figure 5. Catch composition of the Jordanian subsistence fishery in the Gulf of Aqaba from 1950 to 2010.

Figure 6. Catch composition of the Jordanian recreational fishery in the Gulf of Aqaba from 1950 to 2010.

Figure 7. Composition of the total catch of Jordanian fisheries in the Gulf of Aqaba from 1950 to 2010.

186

The catch composition of the artisanal fishery was dominated by snappers (Lutjanidae) accounting for 47% of the reconstructed total catch. The second most important group was pelagic species mackerels (Scombridae), with a contribution of 32% and groupers (Serranidae) was third with 12% (Figure 10, Table A9). These three groups accounted for more than 90% of the reconstructed total catch. The diversity of the total catch was higher in the later years with some taxa, mainly pelagic, that were not dominant in the early years were represented with a higher percentage in the later years. The catch composition of the subsistence fishery was the same as that of the artisanal fishery, because the catch composition ratios used in the artisanal fishery were used for the subsistence fishery as well (Figure 11, Table A10).

The total recreational catch estimate for Israel in the Gulf of Aqaba was generally low, a maximum of 63 t·year-1 in the early 2000s. It increased continuously until it reached its peak and then declined slowly (Figure 12, Table A11). As compared to the Israeli recreational fishery in Mediterranean, where the catch of recreational fishery was comparable to the that of the artisanal fishery (Edelist et al., in press), our estimate for the Gulf of Aqaba was very conservative; only 24% of the artisanal catch. The composition of the recreational fishery was dominated by three taxa (Figure 12). The catch composition of the total catch reflected more or less that of the artisanal fishery. The contribution of snappers (Lutjanidae) was reduced from 47% in the artisanal fishery to 38% in the total catch and that of mackerels (tuna-like) fishes was also reduced from 32% to 26%. On the other hand, the contribution of groupers (Serranidae) increased from 12% to 13%. Although, the contribution of the three taxa was moderated by the contribution of the other sectors to the artisanal fishery, they still were the dominant taxa in the total catch (Figure 13, Table A12).

disCussion

Jordan and Israel have been plagued by numerous conflicts since 1950. This tumultuous history is mirrored in the state of the fisheries. Some of the fluctuations of their fisheries are attributed to political stability or the lack of it in the region. Their small coastal access to the Gulf of Aqaba made them to have the lowest total catch of all the countries bordering the Red Sea. Hence, there is little motivation for either country to collect data, and assess and manage their fisheries. Most of the fisheries data appear to be collected only by university researchers and sporadically by the fisheries administrations (Tellawi, 2001). For effective policies to manage the fisheries to be developed and implemented, consistent time series data are essential (Caddy and Gulland, 1983; PERSGA, 2002; Tesfamichael, 2012).

This study showed considerable discrepancies between the reconstructed catch and data supplied to the FAO by the Jordanian and Israeli governments. One source of discrepancy is the fact that the ‘official data’ is for a larger spatial area (an FAO area) than what we are trying to reconstruct (an EEZ), and therefore do not necessarily refer to Israeli or Jordanian waters, but also to waters further south (in Eritrea for Israel, and Saudi Arabia for Jordan).

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (t

)

0

200

100

300

Lutjanidae

Scombridae

SerranidaeOthers

Xiphias gladiusCarangidae

Figure 9. Total catch of the Israeli fishery in the Gulf of Aqaba by components from 1950 to 2010. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.

Figure 10. Catch composition of the Israeli artisanal fishery in the Gulf of Aqaba from 1950 to 2010.

Figure 8. Total catch of the Israeli fishery in the Gulf of Aqaba by sectors and the total catch Israel reported to FAO from 1950 to 2010.

Jordan and Israel - Tesfamichael et al. 187

However, for the period after fishing in the southern Red Sea waters ended, the reconstructed catch is 148% and 65% higher than the catches that Jordan and Israel, respectively, reported to the FAO. We note that such ‘official’ underestimates are common (Zeller and Harper, 2009).

The sharp decline of the Jordanian fisheries catch in the 1970s and 1980s could be due to the political instability and a direct result of phosphate dust emissions (PERSGA, 2006), compounded by harmful fishing practices. Jordan has a substantial phosphate mine. Industrial pollution of the marine environment is a recurrent theme on the Jordanian side of the Gulf of Aqaba, and affects fishery (IRIN, 2006). Tourism is an important contributor to the local economies (Al Ouran, 2005), and it will be impacted if pollution and excess fishing harm the reefs which form the main habitat in the inner Gulf of Aqaba. The Israeli fishery also showed a decline in the Gulf of Aqaba.

The reconstructed catch derived here is proposed as an improvement over the data currently available. All our estimates are conservative and our assumptions clearly stated. It will be beneficial to strike a balance between industrial development, fisheries and tourism for the inner Gulf of Aqaba, which will permit the coexistence of these sectors, along with a revival of the natural habitats and their fauna and flora. Examples exist of such beneficial coexistence, one being Monterey Bay, in California, USA, which experienced a tourism-led revival following its near destruction by a succession of out-of-control industries (Palumbi and Sotka, 2010). This may serve as a model for the inner Gulf of Aqaba.

aCknowledgements

We would like to thank Dr. Dori Edelist from the University of Haifa for providing insights and data for the Israeli fishery in the Gulf of Aqaba and reading the draft of the report. His comments enriched the content of the report. We also thank Dr. James Shapiro for supplying data on Israel’s fisheries. This is a contribution of the Sea Around Us, a scientific collaboration between the University of British Columbia and The Pew Charitable Trust.

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (t

)

0

10

20

Lutjanidae

Scombridae

Serranidae

Others

Carangidae

Xiphias gladius

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (t

)

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Lethrinidae

Sparidae

Serranidae

Others

1950 1960 1970 1980 1990 2000 2010Year

Cat

ch (t

)0

200

100

300

Lutjanidae

Scombridae

Serranidae

Others

LethrinidaeSparidae

CarangidaeXiphias gladius

Figure 11. Catch composition of the Israeli subsistence fishery in the Gulf of Aqaba from 1950 to 2010.

Figure 12. Catch composition of the Israeli recreational fishery in the Gulf of Aqaba from 1950 to 2010.

Figure 13. Composition of the total catch of the Israeli fisheries in the Gulf of Aqaba from 1950 to 2010.

188

referenCes

Al Ouran, N. (2005) Environmental Assessment , Documentation and Spatial Modeling of Heavy Metal Pollution along the Jordan Gulf of Aqaba Using Coral Reefs as Environmental Indicator Umweltbewertung, Dokumentation und räumliche Modellierung der Schwermetallverschmutzung ent. 158-158 p.

Anonymyous (1992) Israel fisheries in 1988. Thessaloniki.Barrania, A.A. (1979) Report on the Socioeconomic Survey of the Gulf of Aqaba, the Hashemite Kingdom of Jordan.

Development of Fisheries in Areas of the Red Sea and Gulf of Aden. United Nations Development Programme (UNDP) and Food and Agriculture Organization (FAO) of the United Nations, Cairo, Egypt.

Ben-Tuvia, A. (1968) Report on the fisheries investigation of the Israel South Red Sea expeditions, 1962. Sea Fish Res. Stn. Haifa, Bull. 52: 21–55.

Caddy, J.F. and Gulland, J.A. (1983) Historical patterns of fish stocks. Marine Policy 7(4): 267-278.Chakraborty, D. (1984) Fish landings on the Red Sea and Gulf of Aden coast of the member countries: A preliminary

estimate. Development of Fisheries in Areas of the Red Sea and Gulf of Aden. United Nations Development Programme (UNDP) and Food and Agriculture Organization (FAO) of the United Nations, Suez, Egypt, 29 p.

Chesrown, S. (2004) Jordan Valley Preliminary Land Use Master Plan Project : Final Land Use Report. 1. Jordan Valley Authority.

Cisneros-Montemayor, A. and Sumaila, U.R. (2010) A global estimate of benefits from ecosystem-based marine recreation: potential impacts and implications for management. Journal of Bioeconomics 12(3): 245-268.

Cohen, S.B. (1957) Israel’s Fishing Industry. Geographical Review 47(1): 66-85.Edelist, D., Scheinin, A., Sonin, O., Shapiro, J., Salameh, P., Rilov, G., Benayahu, Y., Schulz, D. and Zeller, D. (in press)

Israel: Reconstructed estimates of total fisheries removals in the Mediterranean, 1950–2010. Acta Adriatica.Farid, A.M. (1984) The Red Sea: Prospects for Stability. St. Martin’s Press, New York, 173 p.Froese, R. and Pauly, D., eds. (2012) FishBase.Hargreaves, P. (1981) The Red Sea and Persian Gulf. Wayland Publishers Ltd, Hove, 67-67 p.Khalaf, M.A. and Disi, A.M. (1997) Fishes of the Gulf of Aqaba. Marine Science Station, Aqaba, 252-252 p.Lapidoth-Eschelbacher, R. (1982) The Red Sea and the Gulf of Aden, International Straits of the World. Martinus

Nijhoff Publishers, 265-265 p.MoE (2002) Protecting the Gulf of Eilat/Aqaba. Israel Environment Bulletin 25. Ministry of the Environment. Volume

25, No. 3, 5 p.Palumbi, S. and Sotka, C. (2010) The Death and Life of Monterey Bay: A story of revival. Island Press, Washington,

216 p.Pauly, D. and Zeller, D. (2003) The global fisheries crisis as a rationale for improving the FAO’s database of fisheries

statistics. pp. 1–9. In: Zeller, D., Booth, S., Mohammed, E. and Pauly, D. (eds.) From Mexico to Brazil: Central Atlantic fisheries catch trends and ecosystem models. Fisheries Centre Research Reports, Vol. 11 (6), Vancouver, Canada.

PERSGA (2002) Status of the Living Marine Resources in the Red Sea and Gulf of Aden and Their Management. Strategic action programme for the Red Sea and Gulf of Aden. Regional Organization for the Conservation of the Environment of the Red Sea and Gulf of Aden (PERSGA), Jeddah, Saudi Arabia, 134 p.

PERSGA (2006) Status of the Living Marine Resources in the Red Sea and Gulf of Aden and Their Management. Strategic action programme for the Red Sea and Gulf of Aden. Regional Organization for the Conservation of the Environment of the Red Sea and Gulf of Aden (PERSGA), Jeddah, Saudi Arabia, 260 p.

Pitcher, T.J., Watson, R., Forrest, R., Valtysson, H.P. and Guenette, S. (2002) Estimating illegal and unreported catches from marine ecosystems: a basis for change. Fish and Fisheries 3(4): 317-339.

Sarig, S. (1969) Fisheries and Fish Culture in Israel in 1968. Israeli J. Aquaculture – Bamidgeh 1(40): 95-113.Sarig, S. (1982) Fisheries and Fish Culture in Israel in 1980. Israeli J. Aquaculture – Bamidge 34(1): 1-32.Sarig, S. (1987) Fisheries and Fish Culture in Israel in 1986. Israeli J. Aquaculture – Bamidgeh 34(1).Shapiro, J. (2005) The Fisheries and Aquaculture of Israel 2004. Ministry of Agriculture, Department of Fisheries.Shapiro, J. (2006) The Fisheries and Aquaculture of Israel 2005. Ministry of Agriculture and Rural Development,

Department of Fisheries and Aquaculture, 41 p.Shapiro, J. (2007) The Fisheries and Aquaculture of Israel 2006. Ministry of Agriculture, Department of Fisheries, 47

p.Shapiro, J. (2008) The Fisheries and Aquaculture of Israel 2007. Ministry of Agriculture, Department of Fisheries, 48

p.Sneh, A. and Friedman, G.M., eds. (1985) Hypersaline Ecosystems: the Gavish Sabkha. Springer-Verlag, New York.Snovsky, G. and Shapiro, J. (2004) The Fisheries and Aquaculture of Israel 2003. Ministry of Agriculture, Department

of Fisheries, 37-37 p.Tellawi, A.-M.M. (2001) Conservation and sustainable use of biological diversity in Jordan: First National Report of

The Hashemite Kingdom of Jordan on the Implementation of Article 6 of the Convention on Biological Diversity. The General Corporation for the Environment Protection, Amman, 118 p.

Tesfamichael, D. (2012) Assessment of the Red Sea ecosystem with emphasis on fisheries. University of British Columbia, Vancouver 241 p.

Tesfamichael, D. and Awadh, H. (2012) Common names of exploited fish and invertebrates of the Red Sea. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Jordan and Israel - Tesfamichael et al. 189

Tesfamichael, D. and Mohamud, S. (2012) Reconstructing Red Sea fisheries of Eritrea: A case study of the relationship between political stability and fisheries development. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael, D. and Rossing, P. (2012) Reconstructing Red Sea fisheries catches of Saudi Arabia: National wealth and fisheries transformation. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Zeller, D., Booth, S., Craig, P. and Pauly, D. (2006) Reconstruction of coral reef fisheries catches in American Samoa, 1950-2002. Coral Reefs 25(1): 144-152.

Zeller, D., Booth, S., Davis, G. and Pauly, D. (2007) Re-estimation of small-scale fisheries catches for U.S. flag island areas in the Western Pacific: The last 50 years. US Fishery Bulletin 105(2): 266-277.

Zeller, D. and Harper, S. (2009) Fisheries Catch Reconstructions: Islands, Part I. Fisheries Centre Research Report. Volume 17 (5), Vancouver, 104 p.

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Appendix Table A1. Total catch of the Jordanian fishery in the Gulf of Aqaba by sectors and the total catch (in tonnes) Jordan reported to FAO from 1950 to 2010. Year FAO landings Reconstructed total catch Artisanal Subsistence Recreational1950 100 142 107 35 01951 100 142 107 35 01952 100 142 107 35 01953 200 142 107 35 01954 200 142 107 35 01955 100 142 107 35 01956 0.25 142 107 35 01957 100 142 107 35 01958 100 142 107 35 01959 100 142 107 35 01960 100 142 107 35 01961 100 142 107 35 01962 200 142 107 35 01963 200 142 107 35 01964 200 142 107 35 01965 200 142 107 35 01966 200 142 107 35 01967 100 135 101 34 01968 100 129 95 34 01969 100 122 89 33 01970 100 116 83 32 01971 200 109 77 32 01972 100 102 71 31 01973 100 75 46 29 01974 92 105 51 29 241975 65 99 45 29 261976 49 78 25 26 271977 31 69 15 26 281978 31 70 16 26 291979 36 79 22 26 301980 56 88 29 27 311981 35 96 36 28 321982 19 105 43 28 331983 17 114 50 29 351984 2 156 88 33 351985 2 198 125 37 361986 2 196 122 36 371987 2 194 120 36 391988 2 193 117 36 401989 2 191 114 35 421990 2 189 111 35 431991 20 192 109 35 491992 30 194 106 35 541993 45 196 103 34 591994 60 218 127 37 541995 75 246 150 39 571996 90 238 140 38 601997 100 229 130 37 621998 120 220 120 36 641999 160 266 160 40 662000 150 257 150 39 672001 170 280 170 41 692002 176 288 176 42 702003 131 237 131 37 692004 144 250 144 38 682005 160 266 160 40 662006 147 251 147 39 652007 156 260 156 40 642008 150 255 150 39 662009 219 332 219 46 672010 136 242 136 38 68

Jordan and Israel - Tesfamichael et al. 191Appendix Table A2. Total catch (in tonnes) of the Jordanian fishery in the Gulf of Aqaba by components from 1950 to 2010. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.

Year Reported Unreported1950 100 421951 100 421952 100 421953 107 351954 107 351955 100 421956 0 1421957 100 421958 100 421959 100 421960 100 421961 100 421962 107 351963 107 351964 107 351965 107 351966 107 351967 100 351968 95 341969 89 331970 83 321971 77 321972 71 311973 46 291974 51 541975 45 541976 25 531977 15 541978 16 551979 22 561980 29 581981 35 611982 19 861983 17 971984 2 1541985 2 1961986 2 1941987 2 1921988 2 1911989 2 1891990 2 1871991 20 1721992 30 1641993 45 1511994 60 1581995 75 1711996 90 1481997 100 1291998 120 1001999 160 1062000 150 1062001 170 1102002 176 1122003 131 1062004 144 1062005 160 1062006 147 1042007 156 1042008 150 1052009 219 1132010 136 106

192

Appendix Table A3. Catch composition (in tonnes) of the Jordanian artisanal fishery in the Gulf of Aqaba from 1950 to 2010. Year Lethrinidae Katsuwonus

pelamisEuthynnus

affinisLutjanidae Decapterus

spp.Caesionidae Siganidae Scombridae Carangoides

spp. Auxis spp.

Polysteganus coeruleopunctatus

1950 61 0 0 20 0 0 3 0 3 0 31951 61 0 0 20 0 0 3 0 3 0 31952 61 0 0 20 0 0 3 0 3 0 31953 61 0 0 20 0 0 3 0 3 0 31954 61 0 0 20 0 0 3 0 3 0 31955 61 0 0 20 0 0 3 0 3 0 31956 61 0 0 20 0 0 3 0 3 0 31957 61 0 0 20 0 0 3 0 3 0 31958 61 0 0 20 0 0 3 0 3 0 31959 61 0 0 20 0 0 3 0 3 0 31960 61 0 0 20 0 0 3 0 3 0 31961 61 0 0 20 0 0 3 0 3 0 31962 61 0 0 20 0 0 3 0 3 0 31963 61 0 0 20 0 0 3 0 3 0 31964 61 0 0 20 0 0 3 0 3 0 31965 61 0 0 20 0 0 3 0 3 0 31966 61 0 0 20 0 0 3 0 3 0 31967 58 0 0 19 0 0 3 0 3 0 31968 54 0 0 18 0 0 3 0 3 0 21969 51 0 0 16 0 0 3 0 3 0 21970 48 0 0 15 0 0 2 0 2 0 21971 44 0 0 14 0 0 2 0 2 0 21972 41 0 0 13 0 0 2 0 2 0 21973 27 0 0 9 0 0 1 0 1 0 11974 29 0 0 9 0 0 2 0 1 0 11975 26 0 0 8 0 0 1 0 1 0 11976 14 0 0 5 0 0 1 0 1 0 11977 9 0 0 3 0 0 0 0 0 0 01978 9 0 0 3 0 0 0 0 0 0 01979 13 0 0 4 0 0 1 0 1 0 11980 17 0 0 5 0 0 1 0 1 0 11981 21 0 0 7 0 0 1 0 1 0 11982 25 0 0 8 0 0 1 0 1 0 11983 29 0 0 9 0 0 2 0 1 0 11984 50 0 0 16 0 0 3 0 3 0 21985 60 6 5 19 3 3 5 1 3 0 31986 47 12 9 15 7 5 6 1 2 1 21987 35 17 13 11 10 7 7 1 2 1 21988 24 23 17 7 13 10 8 2 1 1 11989 12 28 21 3 16 12 8 2 1 2 01990 2 32 24 0 19 14 9 3 0 2 01991 2 32 23 0 18 14 9 3 0 2 01992 2 31 23 0 18 13 9 3 0 2 01993 2 30 22 0 17 13 9 3 0 2 01994 2 37 27 0 21 16 11 3 0 2 01995 2 44 32 0 25 19 12 4 0 2 01996 2 41 30 0 23 17 12 3 0 2 01997 2 38 28 0 22 16 11 3 0 2 01998 2 35 26 0 20 15 10 3 0 2 01999 2 44 36 0 25 18 12 4 0 4 02000 1 45 33 0 25 17 10 5 0 2 02001 2 52 40 0 26 15 11 4 0 5 02002 1 52 40 0 25 12 8 14 0 5 02003 1 43 33 0 22 13 0 0 0 4 02004 1 45 35 0 20 12 5 5 0 4 02005 2 55 40 0 17 14 6 4 0 5 02006 1 50 44 0 15 11 4 3 0 4 02007 2 44 45 0 20 13 4 4 0 5 02008 3 43 42 0 16 13 3 3 0 6 02009 9 45 46 0 27 15 10 10 0 9 02010 7 28 34 0 8 9 6 7 0 6 0

Jordan and Israel - Tesfamichael et al. 193

Table A3 continuedYear Thunnus

albacaresThunnus tonggol

Lutjanus bohar

Sparidae Serranidae Scomberomorus commerson

Mullidae Gerres oyena

Gymnocranius grandoculis

Scaridae Others

1950 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111951 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111952 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111953 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111954 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111955 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111956 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111957 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111958 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111959 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111960 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111961 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111962 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111963 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111964 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111965 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111966 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111967 0 0 2 2 1 0 0.4 0.3 0.3 0.3 101968 0 0 2 2 1 0 0.4 0.3 0.3 0.3 101969 0 0 2 2 1 0 0.4 0.3 0.3 0.3 91970 0 0 1 1 1 0 0.3 0.2 0.2 0.2 81971 0 0 1 1 1 0 0.3 0.2 0.2 0.2 81972 0 0 1 1 1 0 0.3 0.2 0.2 0.2 71973 0 0 1 1 0 0 0.2 0.1 0.1 0.1 51974 0 0 1 1 1 0 0.2 0.2 0.2 0.2 51975 0 0 1 1 0 0 0.2 0.1 0.1 0.1 51976 0 0 0 0 0 0 0.1 0.1 0.1 0.1 31977 0 0 0 0 0 0 0.1 0.0 0.0 0.0 21978 0 0 0 0 0 0 0.1 0.0 0.0 0.0 21979 0 0 0 0 0 0 0.1 0.1 0.1 0.1 21980 0 0 0 0 0 0 0.1 0.1 0.1 0.1 31981 0 0 1 1 0 0 0.1 0.1 0.1 0.1 41982 0 0 1 1 0 0 0.2 0.1 0.1 0.1 41983 0 0 1 1 1 0 0.2 0.2 0.2 0.2 51984 0 0 1 1 1 0 0.4 0.3 0.3 0.3 91985 0 0 2 2 1 0 0.4 0.3 0.3 0.3 111986 1 1 1 1 1 0 0.3 0.2 0.2 0.2 91987 1 1 1 1 1 0 0.2 0.2 0.2 0.2 81988 1 1 1 1 0 0 0.2 0.1 0.1 0.1 61989 2 2 0 0 0 0 0.1 0.1 0.1 0.1 41990 2 2 0 0 0 0 0.0 0.0 0.0 0.0 31991 2 2 0 0 0 0 0.0 0.0 0.0 0.0 31992 2 2 0 0 0 0 0.0 0.0 0.0 0.0 31993 2 2 0 0 0 0 0.0 0.0 0.0 0.0 31994 2 2 0 0 0 0 0.0 0.0 0.0 0.0 31995 2 2 0 0 0 0 0.0 0.0 0.0 0.0 41996 2 2 0 0 0 0 0.0 0.0 0.0 0.0 31997 2 2 0 0 0 0 0.0 0.0 0.0 0.0 31998 2 2 0 0 0 0 0.0 0.0 0.0 0.0 31999 5 2 0 0 0 1 0.0 0.0 0.0 0.0 72000 3 2 0 0 0 0 0.0 0.0 0.0 0.0 72001 5 3 0 0 0 1 0.0 0.0 0.0 0.0 62002 5 3 0 0 0 1 0.0 0.0 0.0 0.0 102003 4 2 0 0 0 1 0.0 0.0 0.0 0.0 82004 3 3 0 0 0 1 0.0 0.0 0.0 0.0 102005 3 2 0 0 0 2 0.0 0.0 0.0 0.0 102006 4 2 0 0 0 2 0.0 0.0 0.0 0.0 72007 3 4 0 0 0 2 0.0 0.0 0.0 0.0 102008 4 5 0 0 0 2 0.0 0.0 0.0 0.0 102009 10 11 0 0 0 7 0.0 0.0 0.0 0.0 202010 8 10 0 0 0 7 0.0 0.0 0.0 0.0 6

194Appendix Table A4. Catch composition (in tonnes) of the Jordanian subsistence fishery in the Gulf of Aqaba from 1950 to 2010.Year Lethrinidae Katsuwonus

pelamisLutjanidae Euthynnus

affinisDecapterus

spp.Caesionidae Siganidae Carangoides

spp. Polysteganus

coeruleopunctatusScombridae Auxis

spp. 1950 20 0 6 0 0 0 1 1 1 0 01951 20 0 6 0 0 0 1 1 1 0 01952 20 0 6 0 0 0 1 1 1 0 01953 20 0 6 0 0 0 1 1 1 0 01954 20 0 6 0 0 0 1 1 1 0 01955 20 0 6 0 0 0 1 1 1 0 01956 20 0 6 0 0 0 1 1 1 0 01957 20 0 6 0 0 0 1 1 1 0 01958 20 0 6 0 0 0 1 1 1 0 01959 20 0 6 0 0 0 1 1 1 0 01960 20 0 6 0 0 0 1 1 1 0 01961 20 0 6 0 0 0 1 1 1 0 01962 20 0 6 0 0 0 1 1 1 0 01963 20 0 6 0 0 0 1 1 1 0 01964 20 0 6 0 0 0 1 1 1 0 01965 20 0 6 0 0 0 1 1 1 0 01966 20 0 6 0 0 0 1 1 1 0 01967 20 0 6 0 0 0 1 1 1 0 01968 19 0 6 0 0 0 1 1 1 0 01969 19 0 6 0 0 0 1 1 1 0 01970 18 0 6 0 0 0 1 1 1 0 01971 18 0 6 0 0 0 1 1 1 0 01972 18 0 6 0 0 0 1 1 1 0 01973 16 0 5 0 0 0 1 1 1 0 01974 17 0 5 0 0 0 1 1 1 0 01975 16 0 5 0 0 0 1 1 1 0 01976 15 0 5 0 0 0 1 1 1 0 01977 15 0 5 0 0 0 1 1 1 0 01978 15 0 5 0 0 0 1 1 1 0 01979 15 0 5 0 0 0 1 1 1 0 01980 15 0 5 0 0 0 1 1 1 0 01981 16 0 5 0 0 0 1 1 1 0 01982 16 0 5 0 0 0 1 1 1 0 01983 17 0 5 0 0 0 1 1 1 0 01984 19 0 6 0 0 0 1 1 1 0 01985 17 2 6 1 1 1 1 1 1 0 01986 14 4 4 3 2 2 2 1 1 0 01987 11 5 3 4 3 2 2 1 0 0 01988 7 7 2 5 4 3 2 0 0 1 01989 4 9 1 6 5 4 3 0 0 1 01990 1 10 0 8 6 4 3 0 0 1 11991 1 10 0 8 6 4 3 0 0 1 11992 1 10 0 7 6 4 3 0 0 1 11993 1 10 0 7 6 4 3 0 0 1 11994 1 11 0 8 6 5 3 0 0 1 11995 1 11 0 8 6 5 3 0 0 1 11996 1 11 0 8 6 5 3 0 0 1 11997 1 11 0 8 6 5 3 0 0 1 11998 1 10 0 8 6 4 3 0 0 1 11999 1 11 0 9 6 5 3 0 0 1 12000 0 12 0 9 6 4 3 0 0 1 12001 0 13 0 10 6 4 3 0 0 1 12002 0 12 0 9 6 3 2 0 0 3 12003 0 12 0 9 6 4 0 0 0 0 12004 0 12 0 9 5 3 1 0 0 1 12005 1 14 0 10 4 4 2 0 0 1 12006 0 13 0 12 4 3 1 0 0 1 12007 1 11 0 11 5 3 1 0 0 1 12008 1 11 0 11 4 3 1 0 0 1 22009 2 9 0 10 6 3 2 0 0 2 22010 2 8 0 9 2 2 2 0 0 2 2

Jordan and Israel - Tesfamichael et al. 195

Table A4 continuedYear Thunnus

albacaresLutjanus

boharSparidae Thunnus

tonggolSerranidae Scomberomorus

commersonMullidae Gerres

oyenaGymnocranius

grandoculisScaridae Others

1950 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41951 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41952 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41953 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41954 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41955 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41956 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41957 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41958 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41959 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41960 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41961 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41962 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41963 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41964 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41965 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41966 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 41967 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 31968 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 31969 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 31970 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 31971 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 31972 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 31973 0 0 0 0 0.3 0 0.1 0.1 0.1 0.1 31974 0 0 0 0 0.3 0 0.1 0.1 0.1 0.1 31975 0 0 0 0 0.3 0 0.1 0.1 0.1 0.1 31976 0 0 0 0 0.3 0 0.1 0.1 0.1 0.1 31977 0 0 0 0 0.3 0 0.1 0.1 0.1 0.1 31978 0 0 0 0 0.3 0 0.1 0.1 0.1 0.1 31979 0 0 0 0 0.3 0 0.1 0.1 0.1 0.1 31980 0 0 0 0 0.3 0 0.1 0.1 0.1 0.1 31981 0 0 0 0 0.3 0 0.1 0.1 0.1 0.1 31982 0 0 0 0 0.3 0 0.1 0.1 0.1 0.1 31983 0 0 0 0 0.3 0 0.1 0.1 0.1 0.1 31984 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 31985 0 1 1 0 0.3 0 0.1 0.1 0.1 0.1 31986 0 0 0 0 0.2 0 0.1 0.1 0.1 0.1 31987 0 0 0 0 0.2 0 0.1 0.1 0.1 0.1 21988 0 0 0 0 0.1 0 0.0 0.0 0.0 0.0 21989 0 0 0 0 0.1 0 0.0 0.0 0.0 0.0 11990 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 11991 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 11992 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 11993 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 11994 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 11995 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 11996 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 11997 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 11998 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 11999 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 22000 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 22001 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 12002 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 22003 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 22004 1 0 0 1 0.0 0 0.0 0.0 0.0 0.0 32005 1 0 0 1 0.0 1 0.0 0.0 0.0 0.0 32006 1 0 0 1 0.0 1 0.0 0.0 0.0 0.0 22007 1 0 0 1 0.0 1 0.0 0.0 0.0 0.0 32008 1 0 0 1 0.0 1 0.0 0.0 0.0 0.0 32009 2 0 0 2 0.0 1 0.0 0.0 0.0 0.0 42010 2 0 0 3 0.0 2 0.0 0.0 0.0 0.0 2

196Appendix Table A5. Catch composition (in tonnes) of the Jordanian recreational fishery in the Gulf of Aqaba from 1950 to 2010.

Year Lethrinidae Sparidae Serranidae Others1950 0 0 0 01951 0 0 0 01952 0 0 0 01953 0 0 0 01954 0 0 0 01955 0 0 0 01956 0 0 0 01957 0 0 0 01958 0 0 0 01959 0 0 0 01960 0 0 0 01961 0 0 0 01962 0 0 0 01963 0 0 0 01964 0 0 0 01965 0 0 0 01966 0 0 0 01967 0 0 0 01968 0 0 0 01969 0 0 0 01970 0 0 0 01971 0 0 0 01972 0 0 0 01973 0 0 0 01974 10 7 5 21975 10 8 5 31976 11 8 5 31977 11 8 6 31978 12 9 6 31979 12 9 6 31980 13 9 6 31981 13 10 6 31982 13 10 7 31983 14 10 7 31984 14 11 7 41985 15 11 7 41986 15 11 7 41987 16 12 8 41988 16 12 8 41989 17 13 8 41990 17 13 9 41991 19 15 10 51992 22 16 11 51993 24 18 12 61994 22 16 11 51995 23 17 11 61996 24 18 12 61997 25 19 12 61998 26 19 13 61999 26 20 13 72000 27 20 13 72001 28 21 14 72002 28 21 14 72003 28 21 14 72004 27 20 14 72005 27 20 13 72006 26 20 13 72007 26 19 13 62008 26 20 13 72009 27 20 13 72010 27 20 14 7

Jordan and Israel - Tesfamichael et al. 197

Appendix Table A6. Composition of the total catch (in tonnes) of Jordanian fisheries in the Gulf of Aqaba from 1950 to 2010.Year Lethrinidae Katsuwonus

pelamisEuthynnus

affinisLutjanidae Decapterus

spp.Sparidae Caesionidae Serranidae Siganidae Carangoides

spp. Scombridae

1950 81 0 0 26 0 0 0 1 4 4 01951 81 0 0 26 0 0 0 1 4 4 01952 81 0 0 26 0 0 0 1 4 4 01953 81 0 0 26 0 0 0 1 4 4 01954 81 0 0 26 0 0 0 1 4 4 01955 81 0 0 26 0 0 0 1 4 4 01956 81 0 0 26 0 0 0 1 4 4 01957 81 0 0 26 0 0 0 1 4 4 01958 81 0 0 26 0 0 0 1 4 4 01959 81 0 0 26 0 0 0 1 4 4 01960 81 0 0 26 0 0 0 1 4 4 01961 81 0 0 26 0 0 0 1 4 4 01962 81 0 0 26 0 0 0 1 4 4 01963 81 0 0 26 0 0 0 1 4 4 01964 81 0 0 26 0 0 0 1 4 4 01965 81 0 0 26 0 0 0 1 4 4 01966 81 0 0 26 0 0 0 1 4 4 01967 77 0 0 25 0 0 0 1 4 4 01968 74 0 0 24 0 0 0 1 4 4 01969 70 0 0 22 0 0 0 1 4 4 01970 66 0 0 21 0 0 0 1 3 3 01971 62 0 0 20 0 0 0 1 3 3 01972 59 0 0 19 0 0 0 1 3 3 01973 43 0 0 14 0 0 0 1 2 2 01974 56 0 0 15 0 7 0 6 2 2 01975 52 0 0 14 0 8 0 6 2 2 01976 40 0 0 9 0 8 0 6 2 1 01977 35 0 0 8 0 8 0 6 1 1 01978 35 0 0 8 0 9 0 6 1 1 01979 40 0 0 9 0 9 0 7 1 1 01980 45 0 0 10 0 9 0 7 2 2 01981 49 0 0 12 0 10 0 7 2 2 01982 54 0 0 13 0 10 0 7 2 2 01983 59 0 0 15 0 10 0 8 2 2 01984 83 0 0 22 0 11 0 8 4 3 01985 92 8 6 25 4 11 3 9 6 4 11986 76 15 11 19 9 11 7 9 8 3 11987 61 23 17 14 13 12 10 9 9 2 21988 47 30 22 9 17 12 13 9 10 1 31989 33 36 27 5 21 13 16 9 11 1 31990 20 43 32 0 24 13 18 9 12 0 41991 22 42 31 0 24 15 18 10 12 0 41992 24 41 30 0 23 16 18 11 12 0 41993 26 40 30 0 23 18 17 12 11 0 31994 24 47 35 0 27 16 20 11 14 0 41995 26 55 41 0 31 17 24 11 16 0 51996 27 52 39 0 30 18 22 12 15 0 41997 28 49 36 0 28 19 21 12 14 0 41998 28 45 34 0 26 19 19 13 13 0 41999 29 55 45 0 31 20 23 13 15 0 52000 28 57 42 0 31 20 21 13 13 0 62001 30 65 50 0 32 21 19 14 14 0 52002 29 64 49 0 31 21 15 14 10 0 172003 29 55 42 0 28 21 17 14 0 0 02004 28 57 44 0 25 20 15 14 6 0 62005 29 69 50 0 21 20 18 13 8 0 52006 27 63 56 0 19 20 14 13 5 0 42007 28 55 56 0 25 19 16 13 5 0 52008 30 54 53 0 20 20 16 13 4 0 42009 38 54 56 0 33 20 18 13 12 0 122010 36 36 43 0 10 20 11 14 8 0 9

198

Table A6 continuedYear Polysteganus

coeruleopunctatusAuxis spp.

Thunnus albacares

Thunnus tonggol

Lutjanus bohar

Sparidae Scomberomorus commerson

Mullidae Gerres oyena

Gymnocranius grandoculis

Scaridae Others

1950 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141951 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141952 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141953 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141954 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141955 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141956 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141957 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141958 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141959 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141960 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141961 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141962 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141963 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141964 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141965 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141966 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141967 4 0 0 0 2 2 0 1 0.4 0.4 0.4 141968 3 0 0 0 2 2 0 1 0.4 0.4 0.4 131969 3 0 0 0 2 2 0 0 0.4 0.4 0.4 121970 3 0 0 0 2 2 0 0 0.3 0.3 0.3 121971 3 0 0 0 2 2 0 0 0.3 0.3 0.3 111972 3 0 0 0 2 2 0 0 0.3 0.3 0.3 101973 2 0 0 0 1 1 0 0 0.2 0.2 0.2 81974 2 0 0 0 1 1 0 0 0.2 0.2 0.2 111975 2 0 0 0 1 1 0 0 0.2 0.2 0.2 101976 1 0 0 0 1 1 0 0 0.2 0.2 0.2 81977 1 0 0 0 1 1 0 0 0.1 0.1 0.1 71978 1 0 0 0 1 1 0 0 0.1 0.1 0.1 71979 1 0 0 0 1 1 0 0 0.1 0.1 0.1 81980 1 0 0 0 1 1 0 0 0.2 0.2 0.2 91981 2 0 0 0 1 1 0 0 0.2 0.2 0.2 101982 2 0 0 0 1 1 0 0 0.2 0.2 0.2 111983 2 0 0 0 1 1 0 0 0.2 0.2 0.2 121984 3 0 0 0 2 2 0 0 0.4 0.4 0.4 161985 3 0 0 0 2 2 0 1 0.4 0.4 0.4 181986 3 1 1 1 2 2 0 0 0.3 0.3 0.3 161987 2 1 1 1 1 1 0 0 0.2 0.2 0.2 141988 1 2 2 2 1 1 0 0 0.2 0.2 0.2 121989 1 2 2 2 0 0 0 0 0.1 0.1 0.1 101990 0 2 2 2 0 0 0 0 0.0 0.0 0.0 81991 0 2 2 2 0 0 0 0 0.0 0.0 0.0 81992 0 2 2 2 0 0 0 0 0.0 0.0 0.0 91993 0 2 2 2 0 0 0 0 0.0 0.0 0.0 91994 0 3 3 3 0 0 0 0 0.0 0.0 0.0 101995 0 3 3 3 0 0 0 0 0.0 0.0 0.0 101996 0 3 3 3 0 0 0 0 0.0 0.0 0.0 101997 0 3 3 3 0 0 0 0 0.0 0.0 0.0 101998 0 3 3 3 0 0 0 0 0.0 0.0 0.0 101999 0 5 6 3 0 0 0 0 0.0 0.0 0.0 152000 0 3 4 3 0 0 0 0 0.0 0.0 0.0 162001 0 6 6 4 0 0 1 0 0.0 0.0 0.0 142002 0 6 6 4 0 0 1 0 0.0 0.0 0.0 192003 0 5 5 3 0 0 1 0 0.0 0.0 0.0 172004 0 5 4 4 0 0 1 0 0.0 0.0 0.0 192005 0 6 4 3 0 0 3 0 0.0 0.0 0.0 192006 0 5 5 3 0 0 3 0 0.0 0.0 0.0 152007 0 6 4 5 0 0 3 0 0.0 0.0 0.0 192008 0 8 5 6 0 0 3 0 0.0 0.0 0.0 192009 0 11 12 13 0 0 8 0 0.0 0.0 0.0 312010 0 8 10 13 0 0 9 0 0.0 0.0 0.0 14

Jordan and Israel - Tesfamichael et al. 199

Appendix Table A7. Total catch (in tonnes) of the Israeli fishery in the Gulf of Aqaba by sectors and the total catch Israel reported to FAO from 1950 to 2010. Year FAO landings Reconstructed total catch Artisanal Recreational Subsistence1950 0 66 60 0 61951 0 66 60 0 61952 0 66 60 0 61953 0 66 60 0 61954 0 66 60 0 61955 0 77 70 0 71956 0 88 80 0 81957 0 98 90 0 81958 0 109 100 0 91959 0 120 110 0 101960 0 131 120 0 111961 0 142 130 0 121962 0 153 140 0 131963 0 163 150 0 131964 0 174 160 0 141965 1,000 185 170 0 151966 500 196 180 0 161967 700 206 190 0 161968 400 217 200 0 171969 500 222 205 0 171970 500 227 209 0 171971 400 231 214 0 181972 400 236 218 0 181973 200 241 223 0 181974 14 279 227 34 181975 0 286 232 35 181976 0 292 236 37 191977 0 299 241 39 191978 0 305 245 41 191979 250 311 250 42 191980 283 346 283 42 211981 257 317 257 41 191982 76 122 76 40 61983 68 113 68 40 51984 102 151 102 42 71985 150 204 150 43 111986 0 206 150 45 111987 0 196 140 47 101988 40 187 130 48 91989 0 155 98 50 71990 0 122 67 51 41991 35 90 35 53 21992 98 158 98 54 61993 80 141 80 56 51994 110 175 110 58 71995 150 214 150 55 91996 225 296 225 57 141997 171 240 171 59 101998 137 206 137 61 81999 98 166 98 63 62000 0 190 120 63 72001 120 190 120 63 72002 30 95 30 63 22003 30 94 30 63 22004 100 168 100 62 52005 75 141 75 62 42006 75 140 75 61 42007 50 113 50 61 32008 50 112 50 60 32009 50 132 70 59 42010 50 99 40 57 2

200 Appendix Table A8. Total catch (in tonnes)of the Israeli fishery in the Gulf of Aqaba by components from 1950 to 2010. Reported catch refers to the part of the reconstructed catch accounted in the FAO data.Year Reported Unreported

1950 0 661951 0 661952 0 661953 0 661954 0 661955 0 771956 0 881957 0 981958 0 1091959 0 1201960 0 1311961 0 1421962 0 1531963 0 1631964 0 1741965 170 151966 0 1951967 99 1071968 104 1131969 200 221970 200 271971 200 311972 100 1361973 200 411974 14 2651975 0 2861976 0 2921977 0 2991978 0 3051979 250 611980 283 631981 257 601982 56 661983 33 791984 61 901985 72 1321986 0 2061987 0 1961988 0 1871989 0 1551990 0 1221991 35 551992 62 961993 80 611994 110 651995 150 641996 225 711997 171 691998 137 691999 98 682000 0 1902001 120 702002 30 652003 30 642004 100 682005 75 662006 75 652007 50 632008 50 622009 50 822010 40 59

Jordan and Israel - Tesfamichael et al. 201

Appendix Table A9. Catch composition (in tonnes) of the Israeli artisanal fishery in the Gulf of Aqaba from 1950 to 2010. Year Lutjanidae Scombridae Serranidae Carangidae Xiphias gladius Mullidae Sphyraena spp. Siganus spp. Cephalopods Others1950 29 19 7 0 0 0 0 0 0 51951 29 19 7 0 0 0 0 0 0 51952 29 19 7 0 0 0 0 0 0 51953 29 19 7 0 0 0 0 0 0 51954 29 19 7 0 0 0 0 0 0 51955 34 22 8 0 0 0 0 0 0 61956 38 26 10 0 0 0 0 0 0 61957 43 29 11 0 0 0 0 0 0 71958 48 32 12 0 0 0 0 0 0 81959 53 35 13 0 0 0 0 0 0 91960 58 38 14 0 0 0 0 0 0 101961 62 42 16 0 0 0 0 0 0 101962 67 45 17 0 0 0 0 0 0 111963 72 48 18 0 0 0 0 0 0 121964 77 51 19 0 0 0 0 0 0 131965 82 54 20 0 0 0 0 0 0 141966 86 58 22 0 0 0 0 0 0 141967 91 61 23 0 0 0 0 0 0 151968 96 64 24 0 0 0 0 0 0 161969 98 65 25 0 0 0 0 0 0 161970 100 67 25 0 0 0 0 0 0 171971 103 68 26 0 0 0 0 0 0 171972 105 70 26 0 0 0 0 0 0 171973 107 71 27 0 0 0 0 0 0 181974 109 73 27 0 0 0 0 0 0 181975 111 74 28 0 0 0 0 0 0 191976 113 76 28 0 0 0 0 0 0 191977 116 77 29 0 0 0 0 0 0 191978 118 79 29 0 0 0 0 0 0 201979 120 80 30 0 0 0 0 0 0 201980 136 91 34 0 0 0 0 0 0 231981 123 82 31 0 0 0 0 0 0 211982 36 24 9 0 0 0 0 0 0 61983 33 22 8 0 0 0 0 0 0 51984 49 33 12 0 0 0 0 0 0 81985 72 48 18 0 0 0 0 0 0 121986 72 48 18 0 0 0 0 0 0 121987 67 45 17 0 0 0 0 0 0 111988 62 42 16 0 0 0 0 0 0 101989 47 31 12 0 0 0 0 0 0 81990 32 21 8 0 0 0 0 0 0 51991 17 11 4 0 0 0 0 0 0 31992 47 31 12 0 0 0 0 0 0 81993 38 26 10 0 0 0 0 0 0 61994 53 35 13 0 0 0 0 0 0 91995 72 48 18 0 0 0 0 0 0 121996 108 72 27 0 0 0 0 0 0 181997 82 55 21 0 0 0 0 0 0 141998 66 44 16 0 0 0 0 0 0 111999 47 31 12 0 0 0 0 0 0 82000 58 38 14 0 0 0 0 0 0 102001 58 38 14 0 0 0 0 0 0 102002 14 10 4 0 0 0 0 0 0 22003 14 10 4 0 0 0 0 0 0 22004 48 32 12 0 0 0 0 0 0 82005 36 24 9 0 0 0 0 0 0 62006 8 23 5 15 8 4 2 2 4 62007 5 15 4 10 5 3 2 1 3 42008 5 15 4 10 5 3 2 1 3 42009 7 21 5 14 7 4 2 1 4 62010 4 12 3 8 4 2 1 1 2 3

202

Appendix Table A10. Catch composition (in tonnes) of the Israeli subsistence fishery in the Gulf of Aqaba from 1950 to 2010.Year Lutjanidae Scombridae Serranidae Carangidae Xiphias gladius Cephalopods Mullidae Sphyraena spp. Siganus spp. Others1950 3 2 1 0 0.0 0.0 0.0 0.0 0.0 01951 3 2 1 0 0.0 0.0 0.0 0.0 0.0 01952 3 2 1 0 0.0 0.0 0.0 0.0 0.0 01953 3 2 1 0 0.0 0.0 0.0 0.0 0.0 01954 3 2 1 0 0.0 0.0 0.0 0.0 0.0 01955 3 2 1 0 0.0 0.0 0.0 0.0 0.0 11956 4 2 1 0 0.0 0.0 0.0 0.0 0.0 11957 4 3 1 0 0.0 0.0 0.0 0.0 0.0 11958 4 3 1 0 0.0 0.0 0.0 0.0 0.0 11959 5 3 1 0 0.0 0.0 0.0 0.0 0.0 11960 5 4 1 0 0.0 0.0 0.0 0.0 0.0 11961 6 4 1 0 0.0 0.0 0.0 0.0 0.0 11962 6 4 2 0 0.0 0.0 0.0 0.0 0.0 11963 6 4 2 0 0.0 0.0 0.0 0.0 0.0 11964 7 5 2 0 0.0 0.0 0.0 0.0 0.0 11965 7 5 2 0 0.0 0.0 0.0 0.0 0.0 11966 7 5 2 0 0.0 0.0 0.0 0.0 0.0 11967 8 5 2 0 0.0 0.0 0.0 0.0 0.0 11968 8 5 2 0 0.0 0.0 0.0 0.0 0.0 11969 8 6 2 0 0.0 0.0 0.0 0.0 0.0 11970 8 6 2 0 0.0 0.0 0.0 0.0 0.0 11971 8 6 2 0 0.0 0.0 0.0 0.0 0.0 11972 9 6 2 0 0.0 0.0 0.0 0.0 0.0 11973 9 6 2 0 0.0 0.0 0.0 0.0 0.0 11974 9 6 2 0 0.0 0.0 0.0 0.0 0.0 11975 9 6 2 0 0.0 0.0 0.0 0.0 0.0 11976 9 6 2 0 0.0 0.0 0.0 0.0 0.0 11977 9 6 2 0 0.0 0.0 0.0 0.0 0.0 11978 9 6 2 0 0.0 0.0 0.0 0.0 0.0 21979 9 6 2 0 0.0 0.0 0.0 0.0 0.0 21980 10 7 3 0 0.0 0.0 0.0 0.0 0.0 21981 9 6 2 0 0.0 0.0 0.0 0.0 0.0 21982 3 2 1 0 0.0 0.0 0.0 0.0 0.0 01983 2 2 1 0 0.0 0.0 0.0 0.0 0.0 01984 4 2 1 0 0.0 0.0 0.0 0.0 0.0 11985 5 3 1 0 0.0 0.0 0.0 0.0 0.0 11986 5 3 1 0 0.0 0.0 0.0 0.0 0.0 11987 5 3 1 0 0.0 0.0 0.0 0.0 0.0 11988 4 3 1 0 0.0 0.0 0.0 0.0 0.0 11989 3 2 1 0 0.0 0.0 0.0 0.0 0.0 11990 2 1 1 0 0.0 0.0 0.0 0.0 0.0 01991 1 1 - 0 0.0 0.0 0.0 0.0 0.0 01992 3 2 1 0 0.0 0.0 0.0 0.0 0.0 11993 2 2 1 0 0.0 0.0 0.0 0.0 0.0 01994 3 2 1 0 0.0 0.0 0.0 0.0 0.0 11995 4 3 1 0 0.0 0.0 0.0 0.0 0.0 11996 7 4 2 0 0.0 0.0 0.0 0.0 0.0 11997 5 3 1 0 0.0 0.0 0.0 0.0 0.0 11998 4 3 1 0 0.0 0.0 0.0 0.0 0.0 11999 3 2 1 0 0.0 0.0 0.0 0.0 0.0 02000 3 2 1 0 0.0 0.0 0.0 0.0 0.0 12001 3 2 1 0 0.0 0.0 0.0 0.0 0.0 12002 1 1 0 0 0.0 0.0 0.0 0.0 0.0 02003 1 1 0 0 0.0 0.0 0.0 0.0 0.0 02004 3 2 1 0 0.0 0.0 0.0 0.0 0.0 02005 2 1 0 0 0.0 0.0 0.0 0.0 0.0 02006 0 1 0 1 0.4 0.2 0.2 0.1 0.1 02007 0 1 0 1 0.3 0.1 0.1 0.1 0.1 02008 0 1 0 1 0.3 0.1 0.1 0.1 0.1 02009 0 1 0 1 0.4 0.2 0.2 0.1 0.1 02010 0 1 0 0 0.2 0.1 0.1 0.1 0.0 0

Jordan and Israel - Tesfamichael et al. 203Appendix Table A11. Catch composition (in tonnes) of the Israeli recreational fishery in the Gulf of Aqaba from 1950 to 2010.

Year Lethrinidae Sparidae Serranidae Others1950 0 0 0 01951 0 0 0 01952 0 0 0 01953 0 0 0 01954 0 0 0 01955 0 0 0 01956 0 0 0 01957 0 0 0 01958 0 0 0 01959 0 0 0 01960 0 0 0 01961 0 0 0 01962 0 0 0 01963 0 0 0 01964 0 0 0 01965 0 0 0 01966 0 0 0 01967 0 0 0 01968 0 0 0 01969 0 0 0 01970 0 0 0 01971 0 0 0 01972 0 0 0 01973 0 0 0 01974 13 10 7 31975 14 11 7 41976 15 11 7 41977 16 12 8 41978 16 12 8 41979 17 13 8 41980 17 12 8 41981 16 12 8 41982 16 12 8 41983 16 12 8 41984 17 12 8 41985 17 13 9 41986 18 14 9 51987 19 14 9 51988 19 15 10 51989 20 15 10 51990 21 15 10 51991 21 16 11 51992 22 16 11 51993 22 17 11 61994 23 17 12 61995 22 16 11 51996 23 17 11 61997 24 18 12 61998 24 18 12 61999 25 19 13 62000 25 19 13 62001 25 19 13 62002 25 19 13 62003 25 19 13 62004 25 19 12 62005 25 19 12 62006 24 18 12 62007 24 18 12 62008 24 18 12 62009 23 18 12 62010 23 17 11 6

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Appendix Table A12. Composition of the total catch (in tonnes) of the Israeli fisheries in the Gulf of Aqaba from 1950 to 2010.Year 1 2 3 4 5 6 7 8 9 10 11 121950 32 21 8 0 0 0 0 0 0 0 0 51951 32 21 8 0 0 0 0 0 0 0 0 51952 32 21 8 0 0 0 0 0 0 0 0 51953 32 21 8 0 0 0 0 0 0 0 0 51954 32 21 8 0 0 0 0 0 0 0 0 51955 37 25 9 0 0 0 0 0 0 0 0 61956 42 28 11 0 0 0 0 0 0 0 0 71957 47 32 12 0 0 0 0 0 0 0 0 81958 52 35 13 0 0 0 0 0 0 0 0 91959 58 38 14 0 0 0 0 0 0 0 0 101960 63 42 16 0 0 0 0 0 0 0 0 101961 68 45 17 0 0 0 0 0 0 0 0 111962 73 49 18 0 0 0 0 0 0 0 0 121963 78 52 20 0 0 0 0 0 0 0 0 131964 84 56 21 0 0 0 0 0 0 0 0 141965 89 59 22 0 0 0 0 0 0 0 0 151966 94 63 23 0 0 0 0 0 0 0 0 161967 99 66 25 0 0 0 0 0 0 0 0 171968 104 69 26 0 0 0 0 0 0 0 0 171969 106 71 27 0 0 0 0 0 0 0 0 181970 109 72 27 0 0 0 0 0 0 0 0 181971 111 74 28 0 0 0 0 0 0 0 0 191972 113 76 28 0 0 0 0 0 0 0 0 191973 116 77 29 0 0 0 0 0 0 0 0 191974 118 79 36 13 10 0 0 0 0 0 0 231975 120 80 37 14 11 0 0 0 0 0 0 241976 122 82 38 15 11 0 0 0 0 0 0 241977 125 83 39 16 12 0 0 0 0 0 0 251978 127 85 40 16 12 0 0 0 0 0 0 251979 129 86 41 17 13 0 0 0 0 0 0 261980 146 97 45 17 12 0 0 0 0 0 0 281981 133 88 41 16 12 0 0 0 0 0 0 261982 39 26 18 16 12 0 0 0 0 0 0 111983 35 23 17 16 12 0 0 0 0 0 0 101984 52 35 21 17 12 0 0 0 0 0 0 131985 77 51 28 17 13 0 0 0 0 0 0 171986 77 51 28 18 14 0 0 0 0 0 0 171987 72 48 27 19 14 0 0 0 0 0 0 171988 67 44 26 19 15 0 0 0 0 0 0 161989 50 34 23 20 15 0 0 0 0 0 0 131990 34 23 19 21 15 0 0 0 0 0 0 111991 18 12 15 21 16 0 0 0 0 0 0 81992 50 33 23 22 16 0 0 0 0 0 0 141993 41 27 21 22 17 0 0 0 0 0 0 121994 56 37 26 23 17 0 0 0 0 0 0 151995 77 51 30 22 16 0 0 0 0 0 0 181996 115 76 40 23 17 0 0 0 0 0 0 251997 87 58 34 24 18 0 0 0 0 0 0 201998 70 46 30 24 18 0 0 0 0 0 0 181999 50 33 25 25 19 0 0 0 0 0 0 152000 61 41 28 25 19 0 0 0 0 0 0 162001 61 41 28 25 19 0 0 0 0 0 0 162002 15 10 16 25 19 0 0 0 0 0 0 92003 15 10 16 25 19 0 0 0 0 0 0 92004 51 34 25 25 19 0 0 0 0 0 0 152005 38 25 22 25 19 0 0 0 0 0 0 132006 8 24 18 24 18 16 8 4 4 2 2 122007 5 16 16 24 18 11 5 3 3 2 1 102008 5 16 16 24 18 11 5 3 3 2 1 102009 7 22 17 23 18 15 7 4 4 2 1 122010 4 13 14 23 17 8 4 2 2 1 1 91: Lutjanidae; 2: Scombridae; 3: Serranidae; 4: Lethrinidae; 5: Sparidae; 6: Carangidae; 7: Xiphias gladius; 8: Cephalopods; 9: Mullidae; 10: Sphyraena spp.; 11: Siganus spp.; 12: Others

Local names - Tesfamichael and Saeed 205

Common names of exploited fish and invertebrates of the red sea1

Dawit Tesfamichaela,b and Hesham Saeedc

a Sea Around Us, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, BC., V6T 1Z4, Canada

b Department of Marine Sciences, University of Asmara, Eritrea.c Marine research and resource center, Hodeidah, Yemen

d.tesfamichael @fisheries.ubc.ca;<alsaeed_co @yahoo.com

abstraCt

We present 465 local names for 500 distinct fish and invertebrate taxa of the Red Sea, as used in Egypt, Sudan, Eritrea, Yemen Saudi Arabia and Jordan. The local names used in each country are clearly indicated. The total of scientific-local name combination is 870. Most of the names are in Arabic, a common language in the region in general and the coastal communities in particular. The names were acquired mainly from published reports and papers. Interviews were made to clarify some names and also to add new names. The process of acquisition, verification and standardization of these names, presented in both Arabic and Roman script along with the corresponding scientific names, is described. A brief discussion of some cultural aspects of these names is presented.

introduCtion

Traditionally, fisheries science has been focused on assessment of stocks, i.e., estimating changes in catch per effort, estimating potential harvest levels, and generally providing advice to the fishery sector on the exploitation of the resources and fishing gears. Moreover, it has become clear that, once the assessment work is done, there is a need for both incorporating local knowledge derived from fishers and communicating the results of analyses to policy makers and ultimately to the users (fishers) in a way they can understand. Such communication will be heavily influenced by the cultural context where the fisheries assessment and management is being done. Most of the fish and fisheries knowledge is documented in English for the simple reason that English has become the undisputed global language of science, see contributions in Ammon (2001).

However, in countries where English is not the main language, it cannot be used for communication with fishers. This is especially true in the case of communication about fish, whose common names is the only key to the knowledge that fishers may have on any given species. However, the common names of fish are, within languages and countries highly variable (Freire and Pauly 2005), Only few countries have standardized official list of fish common names e.g., US and Canada in English and Spanish.

FishBase, the online global encyclopedia of over 33,000 described fish species (www.fishbase.org), whose main contents is in English, has attempted to deal with the language issue by providing an interface that can be toggled to other languages and their associated non-Roman scripts (e.g., Arabic), and especially by providing about 305,000 local common names (228,000 in languages other than English) for over 25,900 species in 338 languages spoken throughout the world. SeaLifeBase, as a database similar to FishBase (see www.sealifebase.org), covering 70,000 marine animals other than fishes (marine mammals and reptiles, seabirds, and the great invertebrate host), also includes common names in various languages, but its coverage is more spotty, with overall 28,600 common names for 3,500 species, of which 7,400 are in 87 languages other than English.

There is a high level of illiteracy in fishing communities, especially small scale fisheries in tropical and subtropical areas. Fishing communities in those areas, such as the Red Sea, are usually at the bottom of the socio-economic ladder and use oral story telling tradition as a way of communicating and transferring their knowledge from generation to generation (Tonkin 1986). Paying attention to the oral traditions can give a good insight into the society and their interactions with the environment (Johannes 1981; Becker and Ghimire 2003). Language (words and expressions) and stories are expressions of the collective experiences and consciousness of a society (Burns and Engdahl 1998; Freire and Pauly 2003). Words and expressions flourish out of common and collective experience of a society and acceptance of words to represent materials and ideas. When systematically collected and analyzed the names and stories (knowledge) of communities can be an asset in understanding and managing resources (Palomares et al. 1999; Johannes et al. 2000; Freire and Pauly 2005; Tesfamichael et al. in press).

To assist in these efforts, we have compiled the local names of fish and invertebrates from the Red Sea, i.e., of the species that are commonly targeted by the fishers. The Red Sea is bordered by seven countries. Although some countries (e.g., Sudan and Eritrea) have diverse languages, Arabic is a common language along most of the coastal areas of the Red Sea and there are strong cultural similarities among the coastal communities of the different countries. Thus, the local names are given in Arabic (written both in Arabic and Roman characters). Although most of the species commonly exploited by the fishers are included, this list is not exhaustive. Notably, the Hebrew names of fishes, used in Israel are not included (but see http://www.dafni.com/fish/list.htm).1 Cite as: Tesfamichael, D. and Saeed, H.(2012) Common names of exploited fish and invertebrates of the Red Sea. pp. 205-238. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosysytem by countries (1950-2010). Fisheries Centre Research Reports 20(1). Fisheries Centre, University of British Columbia [ISSN 1198-6727].

206

method

The collection and compilation of local names of the Red Sea fishes was carried out based on published reports and interviews. We searched published papers, local fishery reports, technical reports and books that contain corresponding species names and local names. Most of the fishery survey and assessment reports have information on the local names of the most common species of the fishery of the respective country. The earliest report used here were from the 1960s, when systematic exploration of the fishery resources the Red Sea countries started. However, we are aware of earlier expeditions in the Red Sea (Tesfamichael and Pauly 2012), which introduced Arabic fish names to Europe, e.g., those of Forsskål (1775), Rüppell (1826), and the Mabahiss Expedition (Tesfamichael 2005), where in most of the cases, the scientific name is exactly or based on the local name. Most of the recent works we used for our collection were done by fisheries foreign experts in collaboration with their local counterparts, and most of them added an appendix of the local names of the fishes they encounter during their visits to the region, a practice holding into the 2000s. There are few publications by local researchers, e.g., local names for the fishes of Eritrea (Tesfamichael and Sebahtu 2006) and Sudan (Abu-Gideiri 1984).

We looked for reports that have the local names and corresponding valid scientific names (the latter as provided by FishBase or SeaLifeBase; see below), preferably at species level. When names were not available at species level, the name of the genus or family was used. There were few reports that gave only the common names; their names were not included. Another type of sources were national fish catalogues, available for Sudan (Reed 1964; Abu-Gideiri 1984), Eritrea (Tesfamichael and Sebahtu 2006) and Jordan (Khalaf and Disi 1997). Sources that were comprehensive in their coverage were given priority for compiling names.

Fish names were also obtained from fishers at landing sites in Egypt, Sudan, Eritrea and Yemen by using either freshly caught specimens or color photos of fishes. Most of the fishes were already covered by the sources we used and the interviews were mainly used for verify confusing names. There are very few names that were acquired through interview.

Once the local and scientific names were compiled they were checked for the valid scientific names. The main catalogues used for checking valid names were FishBase (Froese and Pauly 2012) for fish and SeaLifeBase (Palomares and Pauly 2012) for invertebrates. Some names were not available in the above two databases and we used other online databases, i.e., Catalogue of life http://www.catalogueoflife.org, Integrated Taxonomic Information System (ITTS) http://www.itis.gov, World Register of Marine Species (WoRMS) http://www.marinespecies.org, and FishWise professional http://

www.fishwisepro.com.

The published sources usually had the scientific name and the local names written in Roman characters; very few had names written in Arabic as well. The local names transcribed in Roman characters by different authors were different based on their transcription process. We standardized those names, and changed a few other names that were misspelled, or consisted of variants considered not different enough to be represented separately, e.g., ‘Abu gurz’ and ‘Abu gurs’ are represented in our table only by ‘Abu gurz’. However, when similar names were given differently, and we were not sure how to standardize them, we kept the variants, because even if Arabic is spoken all over the Red Sea, local dialects are different; thus, by retaining those differences, we can cover this diversity. The common names are presented on two tables, one sorted by the scientific names, the other by the local names in Arabic script. The names will be included in FishBase (www.fishbase.org) and SeaLifeBase (www.sealifebase.org).

result and disCussion

We identified 500 distinct taxa with 465 local names, and 870 scientific name - common name combinations, i.e., many taxa have more than one local names and some local names are also used for different taxa (Tables 1 and 2), as also observed, e.g., by Freire and Pauly (2003). While scientific systematic nomenclature uses detailed characters for identification (e.g., fin ray counts in fishes, genetics) to categorize organisms, local names are usually based on characteristics that are easy to observe (Berlin 1992; Palomares et al. 1999). Hence, local names do not have as high resolution as the scientific names.

One major difference of scientific and common names is that the latter are usually not unique. Thus, for example, the generic Caranx has the highest number of local names, i.e., 10. On the other hand, ‘Beyad’, the most frequent local name is used for 17 different taxa (Table 2) and all the local names with high occurrence frequency in Table (2) have higher number of occurrences than the high frequency scientific names with different local names in Table (1), except for Caranx. Taxa that have

Table 2. Number of fish species with the the same local names.Local name No. of spp.Beyad 17Muesy 13Fanas 13Moscht 13Arabi 11Kushar 10Bagha 10Abu sheneb 9Ghabban 9Shu’ur 8Um qaren 8

Table 1. Taxa with high number of local names.Taxa No. of local namesCaranx spp. 10Euthynnus affinis 7Rachycentron canadum 7Lethrinus spp. 7Mugil spp. 7Lutjanidae 7Epinephelus tauvina 7Epinephelus areolatus 6Haemulidae 6Cephalopholis miniata 6Acanthopagrus bifasciatus 6Diagramma pictum 6

Local names - Tesfamichael and Saeed 207

more than one local names either have one name per country, but occur in several countries (e.g. Atule mate has three different names depending on country) or they are so common and important to local communities that they have more than one local name within the same country (e.g., Acanthopagrus bifasciatus has four different names in Eritrea; see Appendix Table A1).

Sometimes the different names given to one species may refer to the different developmental stages. In similar study in Brazil, fishes that are commercially important and fishes that inhabit habitats frequented by fishers have on average 6 local names per species, while fishes that inhabit deeper waters and not fished by local do not have local names. These discrepancies are believed to affect the data collection system (Freire and Pauly 2005). Similar results were also found for the Philippines (Palomares et al. 1999).

Most of the local names compiled here are based on Arabic language, which is the common language in the coastal communities of the Red Sea. However, few names are based on European (mainly Italian) language. Those names are for taxa (often invertebrates) that were not readily consumed by local residents, at least in the past, but by Europeans when they frequented the Red Sea area. Thus, the locals named these taxa based on their European common names, e.g., in some communities shrimp are called ‘Gamberi, which is based on Italian. Local names are, however, given to some invertebrates not commonly consumed locally, e.g., crabs are generally called ‘Abu mekass’ or ‘Abu mokas’ meaning scissors. The first author has observed local fishers discarding big size crabs, which they see as nuisance for their fishing operation, and rarely shrimps used as bait to catch fish.

Only few taxa are reported in many of the countries compared to an ecological check list of fishes in the ecosystem. These are taxa that are common and important to fishers throughout the Red Sea. For example, the two-spot snapper Lutjanus bohar is reported from almost all Red Sea countries. Based on interviews with fishers, it is clear that it is an important species to them, a priority target for handlining fishery. The local name is ‘Bohar’, which is also the species epithet in the scientific name. Indeed, it is so important to the region that sometimes all Lutjanus species are referred to as ‘Bohar’. It is common practice for the fishers to use the same local name to a specific species or as generic name to a group either at genus level or even family level. Scomberomorus commerson ‘Dirak’ is the equivalent of Lutjanus bohar, in terms of its important, for the pelagic fishery, which in the Red Sea is mainly gillnetting. Other names reported in most of the countries include ‘Beyad’ (Caranx spp.). Agam (Sphyraena barracuda), Bagha (Rastrelliger kanagurta), and Salmani (Chanos chanos). These names would be the names usually known by anyone, even children. The list of all the names sorted in ascending order of the scientific names is given in Appendix Table (A1) and sorted by the local names in Appendix Table (A2).

The usefulness of such local names table is many folds. As language is the registry of the collective consciousness of societies (Burns and Engdahl 1998), which depends on their experiences (their interactions with the environment and each other) and livelihood; looking at local names of fishes, one can learn the fishing habits and behaviours of a fishing community. Although most member of Red Sea coastal communities cannot read and write, their knowledge of the sea is extensive. Tapping into that wealth of experiential knowledge can help in understanding the ecological and social system for informed planning and management (Johannes et al. 2000). Knowledge gained from fishers can be as informative as knowledge gained through other analytical means (Tesfamichael et al. in press). In order to tap to fishers’ knowledge, knowing the names of the items of discussion (i.e., fish) is critical.

aCknowledgement

We would like to thank the fishers who cooperated with us during interviews for their time and willingness to share their knowledge. Thanks also go to Ken for helping entering names into the database, Myriam Khalfallah for double checking the local names written in Arabic, and Daniel Pauly for helping us contextualizing our research, which was supported by Sea Around Us, a scientific collaboration between the University of British Columbia and The Pew Charitable Trust.

referenCes

Abu-Gideiri YB (1984) Fishes of the Sudan. University Press, Khartoum. 66 p.Ammon U, editor (2001) The dominance of English as a language of science: Effects on other languages and language

communities 84. Walter de Gruyter.Barrania A, Bringi MR and Saleh M (1980) Socio-economic aspects of the Saudi Arabian fisheries in the Red Sea. FAO/

UNDP Proj. for Development of Fisheries in Areas of the Red Sea and Gulf of Aden, Suez, Egypt.Bayoumi AR (1972) Recent biological investigation in the Red Sea along the A.R.E coasts. I–On some demersal fishes

of economic importance from the Red Sea with notes on migration of fish through the Suez Canal. Bull. Inst. Oceanogr. Fish., UAR 2: 159-183.

Becker CD and Ghimire K (2003) Synergy Between Traditional Ecological Knowledge and Conservation Science Supports Forest Preservation in Ecuador. Conservation Ecology 8.

Berlin B (1992) Ethnobiological Classification: Principles of Categorization of Plants and Animals in Traditional Societies. Princeton University Press, Princeton. 335 p.

Bonfiglioli A and Hariri KI (2004) Small-scale fisheies in Yemen: Social assessment and development prospects. FAO, The World Bank. 11 p.

Burns TR and Engdahl E (1998) The social construction of consciousness. Part 1: collective consciousness and its socio-cultural foundations. Journal of Consciousness Studies 5(1): 67-85.

208

El-Saby MK and Farina L (1954) Report to the government of Saudi Arabia on possibility for development of marine fisheries. FAO, Rome.

FHAS (1984) Fish production in Sudan — a study on the methodology and the data collected during 1979 and 1980. FAO/UNDP, SUEZ (EGYPT).

Forsskål P (1775) Descriptiones animalium, avium, amphibiorum, piscium, insectorum, vermium; quae in itinere orientali observavit. Hauniae, Copenhagen.

Freire KMF and Pauly D (2003) What’s in there: Common name of Brazilian marine fishes. pp. 439-444 In Haggan N, Brignall C and Wood L (eds.), Putting fisher’s knowledge to work. Fisheries Centre Research Reports, Vol. 11 (1), Vancouver, Canada.

Freire KMF and Pauly D (2005) Richness of common names of Brazilian marine fishes and its effect on catch statistics. Journal of Ethnobiology 25(2): 279-296.

Froese R and Pauly D (2012) FishBase. Available at: www.fishbase.org [Accessed: May 24, 2012].Johannes RE (1981) Words of the Lagoon: Fishing and Marine Lore in the Palau District of Micronesia University of

California, Barkley.Johannes RE, Freeman MMR and Hamilton RJ (2000) Ignore fishers’ knowledge and miss the boat. Fish and Fisheries

1(3): 257-271.Khalaf MA and Disi AM (1997) Fishes of the Gulf of Aqaba. Marine Science Station, Aqaba. 252-252 p.MEPI (1993) Identification study for Sudan Red Sea fisheries. Ministry of Economic Planning and Investment,

Khartoum. 213 p.MOF (2012) Eritrean Fisheries Database System. Ministry of Fisheries, Massawa, EritreaPalomares MLD, Garilao CV and Pauly D (1999) On the biological information content of common names: a

quantitative case study of Philippine fishes. In Séret B and Sire J-Y (eds.), Proceedings of the 5th Indo-Pacific Fish Conference, Nouméa, 3-8 November 1997, Paris.

Palomares MLD and Pauly D (2012) SeaLifeBase. Available at: www.sealifebase.org [Accessed: May 24, 2012].Rafail SZ (1972) Studies of Red Sea fisheries by light and purse-seine near Al-Ghardaqa. Bull. Inst. Oceanogr. Fish.,

UAR 2: 25-49.Reed W (1964) Red Sea fisheries of Sudan. Game and Fisheries Section, Ministry of Animal Resources, Sudan,

Khartoum.Rüppell E (1826) Atlas zu der Reise im nördlichen Afrika1826-1828. Gedruckt und in Commission bei Heinr. Ludw.

Brönner, Frankfurt am Main.Tesfamichael AG and Sebahtu SH (2006) Commercial Fish of the Eritrean Red Sea. Apex publishing Ltd, Essex,

England.Tesfamichael D (2005) Reconstructing the John Murray/Mabahiss expedition. The Sea Around Us Project Newletter

(29): 4.Tesfamichael D and Pauly D (2012) Introduction to the Red Sea ecosystem and its fisheries. In Tesfamichael D and

Pauly D (eds.), Catch reconstruction for the Red Sea large marine ecosystem by countries (1950 – 2010). Fisheries Centre Research Reports, Vol. 20 (1), Vancouver.

Tesfamichael D, Pitcher TJ and Pauly D (in press) Assessing changes in fisheries using fishers’ knowledge to generate long time series of catch rates: a case study from the Red Sea. Ecology and society.

Tonkin E (1986) Investigating Oral Tradition. The Journal of African History 27(02): 203-213.Walczak P (1977) The Yemen Arab Republic. A study of the marine resources of the Yemen ArabRepublic. A report

prepared for the Fisheries Development Project. FAO, Rome. 67 p.Walczak P and Gudmundsson J (1975) Yemen Arab Republic–Summary of fish stock assessment work. FAO, Rome.

14 p.

Local names - Tesfamichael and Saeed 209

Appendix Table A1. Common names of Red Sea fish and invertebrates sorted by scientific names.No. Scientific name Common name Local name Arabic name Countrya Sourceb

1 Abalistes stellatus Starry triggerfish Hijma هجمه Aq 142 Abudefduf sexfasciatus Scissortail sergeant Shabbar شبار Aq 143 Abudefduf sordidus Blackspot sergeant Shabbar شبار Aq 144 Abudefduf vaigiensis Indo-Pacific sergeant Shabbar شبار Aq 145 Acanthopagrus berda Picnic seabream Abu kuhul ابوكحل Su 66 Abu berite ابوبريت Er 117 Acanthopagrus bifasciatus Twobar seabream Rabaag رباج Aq,SA 1,148 Abu kuhul ابو كحل Er,Su 5,7,109 Fogil فوجيل Su 510 Butel hammed بطل حماد Er 1111 Abu berite ابو بريت Er 1112 Abyad ابيض Er 1013 Acanthurus blochii Ringtail surgeonfish Gahm جهم Er 1114 Zizan زيزان Er 1115 Acanthurus gahhm Black surgeonfish Gahm جهم SA 116 Kohom كوهم Su 5,717 Acanthurus nigricauda Epaulette surgeonfish Gahm جهم Er 1118 Zizan زيزان Er 1119 Acanthurus nigrofuscus Brown surgeonfish Juneh جنه Aq 1420 Acanthurus sohal Sohal surgeonfish Suhal سوهل SA 121 Sahla سهله Aq 1422 Zizan زيزان Er 1123 Gahm جهم Er 1124 Acanthurus xanthopterus Yellowfin surgeonfish Gahm جهم Er 1125 Zizan زيزان Er 1126 Aethaloperca rogaa Redmouth grouper Kushar كشر Er 1127 Katarban كتربان Su 5,728 Karban كربان Er 1029 Ruga روجا SA 130 Albula vulpes Bonefish Bounouk بو نوك SA,Su 1,5,6,731 Alectis ciliaris African pompano Pompano بمبانو Er 1132 Beyad بياد Er 1033 Alectis indicus Indian threadfish Beyad abu tabag بياد ابو تابج SA 134 Shawish شاويش Su 5,6,735 Alepes djedaba Shrimp scad Beyad بياد Er 1136 Djebbada دجبدة Ye 337 Alopias vulpinus Thintail thresher Gursh husseni قرش حصينى SA 138 Aluterus monoceros Unicorn leatherjacket filefish Um qaren ام قرن Aq 1439 Aluterus scriptus Scribbled leatherjacket filefish Kotub كوتب Su 040 Amanses scopas Broom filefish Um qaren ام قرن Aq 1441 Amblygaster leiogaster Smooth-belly sardinella Moza موزة Eg 1342 Amblygaster sirm Spotted sardinella Sardina marboum سردينه مبروم Eg 1343 Aida عيدة Er 1144 Belem بليم Er 1145 Amphiprion bicinctus Twoband anemonefish Om Al dukhan ام الدخان Aq 1446 Anampses caeruleopunctatus Bluespotted wrasse Muesy ميسي Aq 1447 Anampses lineatus Lined wrasse Muesy ميسي Aq 1448 Anampses meleagrides Spotted wrasse Muesy ميسي Aq 1449 Anampses twistii Yellowbreasted wrasse Muesy ميسي Aq 1450 Anchoviella spp. Anchovies Fagima فقيمة Su 5,751 Anthias spp. Serranidae Zargh زرغ SA 952 Aphareus furca Small toothed jobfish Anteg عنتق Er 1053 Apogon aureus Ring-tailed cardinalfish Fanas فانس Aq 1454 Apogon bifasciatus Twobelt cardinal Fanas فانس Aq 1455 Apogon cyanosoma Yellowstriped cardinalfish Fanas فانس Aq 1456 Apogon exostigma Narrowstripe cardinalfish Fanas فانس Aq 14a Aq = Aquaba (mainly Jordan), Eg = Egypt, Er = Eritrea, SA = Saudi Arabia, Su = Sudan, Ye = Yemenb 1 Barrania et al. (1980), 2 Walczak and Gudmundsson (1975), 3 Walczak (1977), 4 Bonfiglioli and Hariri (2004), 5 MEPI (1993), 6 Abu-Gideiri (1984), 7 Reed (1964), 8 FHAS (1984), 9 El-Saby and Farina (1954), 10 MOF (2012), 11 Tesfamichael and Sebahtu (2006), 12 Bayoumi (1972), 13 Rafail (1972), 14 Khalaf and Disi (1997), 15 Interview.

210

Table A1 continuedNo. Scientific name Common name Local name Arabic name Country Source57 Apogon kallopterus Iridescent cardinalfish Fanas فانس Aq 1458 Apogon nigrofasciatus Blackstripe cardinalfish Fanas فانس Aq 1459 Apolemichthys xanthotis Yellow-ear angelfish Moscht مشط Aq 1460 Aprion spp. Snappers Farsi فارسي Su 5,761 Aprion virescens Green jobfish Farsi فارسي Su 662 Argyrops filamentosus Soldierbream Jarbeeden جربيدن Aq 1463 Argyrops spinifer King soldierbream Morjan مرجان Eg,Su 7,1264 Fofal فوفل Er,Su 5,7,1065 Najar نجار Aq 1466 Abyad ابيض Er 1067 Najar نجار SA 1,968 Ariomma brevimanus Pomfret Maslimani مسلمانى Aq 1469 Arius spp. Sea catfishes Abu sheneb ابو شنب SA 970 Arothron diadematus Masked puffer Hadhroom حضروم Aq 1471 Arothron hispidus White-spotted puffer Drimma دريما SA 172 Hadhroom حضروم Aq 1473 Arothron immaculatus Immaculate puffer Drimma دريما SA 174 Arothron stellatus Stellate puffer Hadhroom حضروم Aq 1475 Drimma دريما SA 176 Atherinomorus lacunosus Hardyhead silverside Balem بليم Aq 1477 Gurgush جرجوش Su 5,778 Atule mate Yellowtail scad Haboot هابوت Su 5,779 Saibariya صعباريا Ye 1580 Beyad بياد Er,SA 1,1181 Auxis thazard thazard Frigate tuna Sherwi شروي SA 182 Tuna تونة Su 583 Balistapus undulatus Orange-lined triggerfish Um qaren ام قرن Aq 1484 Khanzeer خنزير SA 185 Ajame عجامة Er 1186 Balistes spp. Triggerfishes Schiyram shiram شيرام شيرام SA 987 Canzir كنزير Er 1088 Balistoides viridescens Titan triggerfish Ajame عجامة Er 1189 Faki sharam فاكي شرام Su 5,790 Bodianus anthioides Lyretail hogfish Muesy ميسي Aq 1491 Bodianus axillaris Axilspot hogfish Deek ديك SA 192 Bolbometopon muricatum Green humphead parrotfish Harida حريدا Er 1193 Bothus pantherinus Leopard flounder Hisan al-Bahar حصان البحر SA 194 Shebet al bahir شيبت البحر Er 1195 Tabaq طبق Aq 1496 Brachyura Crab Abu mokas ابو مقص Ye 2,397 Branchiostegus sawakinensis Freckled tilefish Theena تحينا Su 698 Caesio lunaris Lunar fusilier Bagha باغة Aq 1499 Caesio striata Striated fusilier Kourab el bahr كراب البحر Er 11100 Caesio suevica Suez fusilier Bagha باغة Aq 14101 Kourab el bahr كراب البحر Er 11102 Caesio varilineata Variable-lined fusilier Bagha hamra باغة حمراء Aq 14103 Callyodon spp. Parrotfishes Harid حريد Su 5,7104 Calotomus viridescens Viridescent parrotfish Ghabban غبان Aq 14105 Cantherhines pardalis Honeycomb filefish Um qaren ام قرن Aq 14106 Canthigaster coronata Crowned puffer Hadhroom حضروم Aq 14107 Canthigaster margaritata Pufferfish Hadhroom حضروم Aq 14108 Carangoides armatus Longfin trevally Beyad بياد Er 11109 Carangoides bajad Orangespotted trevally Beyad بياد Er,Su 5,10110 Reema safra ريم سفره Aq 14111 Beyad gazza بياد جازة SA 9112 Carangoides coeruleopinnatus Coastal trevally Beyad goutar بياد جوتر Er,Su 6,10113 Carangoides equula Whitefin trevally Subaria صعباريا Ye 3114 Carangoides ferdau Blue trevally Beyad بياد Er 11115 Carangoides fulvoguttatus Yellowspotted trevally Gutur جوتر Su 5116 Reem ريم Aq 14117 Seleikh سيليخ Su 5,7

Local names - Tesfamichael and Saeed 211

Table A1 continuedNo. Scientific name Common name Local name Arabic name Country Source118 Carangoides fulvoguttatus Yellowspotted trevally Beyad gaz بياد جاز SA 1119 Beyad goutar بياد جوتر Er,Su 5,11120 Carangoides gymnostethus Bludger Beyad بياد Er 10121 Carangoides malabaricus Malabar trevally Beyad بياد Er 11122 Carangoides oblongus Coachwhip trevally Beyad girm بياد جريم SA 9123 Caranx ignobilis Giant trevally Girim جيريم Su 5124 Beyad بياد Er,SA,Su 1,5,10125 Caranx melampygus Bluefin trevally Beyad girm بياد جريم Er,SA 1,10126 Caranx sexfasciatus Bigeye trevally Beyad بياد Er,SA,Su 1,5,10127 Caranx spp. Jacks and pompanos Tak’oi تكاوي Su 7128 Safloh سفلوح Su 7129 Haboot هابوت Su 7130 Lamenab لايمناب Su 7131 Goutar قوتر Su 5,7132 Seleikh سيليخ Su 7133 Girim جيريم Su 7134 Beyad بياد Er,SA,Su,Ye 3,7,9,10135 Goareit جواريت Su 7136 Karb كرب Su 5,7137 Carcharhinidae Requiem sharks Lokhem لخام Ye 2138 Dohoosh طاهوش Ye 2139 Girish قريش SA,Su 5,8,9140 Autat عوتات Er 10141 Carcharhinus amblyrhynchos Grey reef shark Gursh al baba قرش البابا SA 1142 Carcharhinus limbatus Blacktip shark Autat عوتات Er 11143 Gursh al sahl قرش السهل SA 1144 Carcharhinus melanopterus Blacktip reef shark Autat عوتات Er 11145 Zingi زنجى Er 11146 Carcharhinus plumbeus Sandbar shark Autat عوتات Er 11147 Gursh قرش Aq 14148 Carcharodon carcharias Great white shark Gursh قرش SA 1149 Centropyge multispinus Dusky angelfish Moscht مشط Aq 14150 Cephalopholis argus Peacock hind Ghohlab جو هلاب Su 6151 Kushar abu blaha كشر ابو بلحة Er,SA 1,11152 Cephalopholis hemistiktos Yellowfin hind Mumen مومان Aq 14153 Cephalopholis miniata Coral hind Ferek فريق Er 11154 Ghohlab جو هلاب Su 6155 Ahmer احمر Er 11156 Kushar كشر SA 1157 Kushar abu adas كشر ابو عداس SA 9158 Shirni شيرنى Aq 14159 Cephalopholis sexmaculata Sixblotch hind Abu shirni ابو شرني Aq 14160 Cephalopholis spp. Sea basses: groupers and fairy

bassletsGahlab جهلب Su 5

161 Cetoscarus bicolor Bicolour parrotfish Ghabban غبان Aq 14162 Harida حريدا Er 11163 Chaetodon auriga Threadfin butterflyfish Gringish جرينجش SA 1164 Moscht مشط Aq 14165 Chaetodon austriacus Blacktail butterflyfish Moscht مشط Aq 14166 Chaetodon fasciatus Diagonal butterflyfish Moscht مشط Aq 14167 Chaetodon melannotus Blackback butterflyfish Moscht مشط Aq 14168 Chaetodon paucifasciatus Eritrean butterflyfish Moscht مشط Aq 14169 Chaetodon semilarvatus Bluecheek butterflyfish Moscht مشط Aq 14170 Chaetodon trifascialis Chevron butterflyfish Moscht مشط Aq 14171 Chanos chanos Milkfish Salmani سلماني Er,SA,Su,Ye 1,3,5,6,7,11172 Bunji بونجي Su 5,6,7173 Cheilinus abudjubbe Abudjubbe wrass Rabadi ربادي Aq 14174 Arousset el baher عروسة البحر Er 11175 Esha mer’e عش ميري Er 11176 Cheilinus lunulatus Broomtail wrasse Rabadia ربادي Aq 14177 Cheilinus mentalis Mental wrasse Muesy ميسي Aq 14178 Cheilinus trilobatus Tripletail wrasse Abu mulees ابو مليس SA 1

212Table A1 continued

No. Scientific name Common name Local name Arabic name Country Source179 Cheilinus undulatus Humphead wrasse Esha mer’e عش ميري Er 11180 Arousset el baher عروسة البحر Er 11181 Terbaany تيرباني SA 1182 Limalima ليما ليما Su 7183 Abu jibba ابو جيبا Su 5,6,7184 Cheilodipterus lachneri Fanas فانس Aq 14185 Cheilodipterus macrodon Large toothed cardinalfish Fanas فانس Aq 14186 Cheilodipterus novemstriatus Indian Ocean twospot

cardinalfishFanas فانس Aq 14

187 Chelonioidea Marine tutles Sulhafa سلحافه Ye 3188 Chilomycterus spilostylus Spotbase burrfish Hadhroom abu shouka حضروم ابو شوكة Aq 14189 Chirocentrus dorab Dorab wolf-herring Nakanaf نكاناف Ye 3190 Mekhlef مخلف Er 11191 Abu seif ابو سيف SA,Su 1,5,6192 Chlorurus gibbus Heavybeak parrot fish Abu greeyan ابو جريان SA 1193 Chlorurus sordidus Daisy parrotfish Ghabban غبان Aq 14194 Choerodon robustus Robust tuskfish Far al-Bahar فار البحر Aq 14195 Cholorurus sordidus Daisy parrotfish Hareeth حريث SA 1196 Chrysoblephus spp. Porgies Haffar حفار SA 9197 Clupeidae Herrings,shads,sardines,menh

adensAida عيدة Ye 3

198 Sardin سردين Ye 3199 Wasif وزف Ye 2200 Cociella crocodilus Crocodile flathead Rugud روجود SA 1201 Conger cinereus Longfin African conger Hanish silab حنيش سيلاب SA 1202 Coris aygula Clown coris Heqab حيقب Aq 14203 Coris caudimacula Spottail coris Muesy ميسي Aq 14204 Coris variegata Dapple coris Muesy ميسي Aq 14205 Coryphaena hippurus Common dolphinfish Saif سيف Aq 14206 Um falloos ام فلوس SA,Su 1,5,7207 Corythoichthys flavofasciatus Network pipefish Masas ramli مساس رملي Aq 14208 Corythoichthys schultzi Schultz’s pipefish Masas ramli مساس رملي Aq 14209 Crenidens crenidens Karenteen seabream Haffar حفار SA 1210 Hindook هيندوك Su 5,7211 Crenimugil crenilabis Fringelip mullet Arabi عربي Aq 14212 Crenimugil spp. Mullet Arabi عربي Er,SA 1,10213 Cristacirrhitus punctatus Blackspotted hawkfish Jarbua جربوعه SA 1214 Ctenochaetus striatus Striated surgeonfish Juneh جنه Aq 14215 Cynoglossus bilineatus Fourlined tonguesole Hisan al-Bahar حصان البحر SA 1216 Dactyloptena peterseni Starry flying gurnard Boomet al-Bahar بومة البحر Aq 14217 Dascyllus trimaculatus Threespot dascyllus Kharayeh خاراية Aq 14218 Dasyatidae Stingrays Fahodoo فهودو Ye 2219 Abu remis ابو راميز Ye 15220 Taira طيرة Ye 3221 Bakhat باخات Ye 2222 Dasyatis spp. Stingrays Abu soot ابو سوط Su 5223 Rugtia روجتيه SA 1224 Decapterus macarellus Mackerel scad Amia اميه Aq 14225 Decapterus macrosoma Shortfin scad Sardina سردينه Aq 14226 Decapterus maruadsi Japanise scad Bagha باغة Su 5227 Decapterus punctatus Round scad Bagha باغة Eg 13228 Decapterus russelli Indian scad Bagha باغة Eg 13229 Shadba شدبا Su 5,6,7230 Sardina aredha سردينه عريضة Aq 14231 Decapterus spp. Jacks and pompanos Shaduba شدوبا SA 1232 Dendrochirus brachypterus Shortfin turkeyfish Rani, Abu al-Laban رنى- ابو اللبن Aq 14233 Diagramma pictum Painted sweetlips Shutaf شوطاف Er,Ye 2,11234 Shakfa شكفا Su 5,6,7235 Caterin قطرين Ye 2236 Sobaity سوبيتى Er 11237 Fataleeta فتاليتا Su 5,6,7238 Istaf استاف Aq 14239 Diagramma spp. Haemulidae Shutaf شوطاف SA 9

Local names - Tesfamichael and Saeed 213Table A1 continued

No. Scientific name Common name Local name Arabic name Country Source240 Diodon hystrix Spot-fin porcupinefish Drimma دريما SA 1241 Hadhroom abu shouka حضروم ابو شوكة Aq 14242 Diplodus noct Red Sea seabream Noct نوكت Aq 14243 Dussumieria acuta Rainbow sardine Belem بليم Er 11244 Aida عيدة Er 11245 Echeneis naucrates Live sharksucker Qamlet alqersh قملة القرش Aq 14246 Gamla جمله SA 1247 Echeneis spp. Remoras Kamlet al darfil قملة الدرفيل SA 9248 Echidna nebulosa Snowflake moray Qmum muraqata قموم مرقطة Aq 14249 Elagatis bipinnulata Rainbow runner Beyad بياد Er 10250 Adad اداد Su 5251 Muslabah مسلابه Er,SA 1,11252 Elops affinis Pacific ladyfish Salmani سلماني SA 9253 Elops machnata Tenpounder Khanny خاني SA 1254 Shagool شجول Su 5,6,7255 Encrasicholina heteroloba Shorthead anchovy Aida عيدة Er 11256 Wesif وزف Er 11257 Belem بليم Er 11258 Epenephelus spp. Sea basses: groupers and fairy

bassletsKushar كشر Su 8

259 Epinephelus areolatus Areolate grouper Kushar nagel كشر ناجل Er,SA 9,11260 Abu ades ابو عدس Er 11261 Shelwa شيلوة Aq 14262 Kodad كداد Su 7263 Seetiati سيتياتي Su 7264 Gishir shooni جيشر شونى Su 5,6,7265 Epinephelus chlorostigma Brownspotted grouper Samman سمن Er 11266 Gishir جيشر Su 5267 Epinephelus fasciatus Blacktip grouper Kushar كشر Er 11268 Daghma دغمة Aq 14269 Epinephelus fuscoguttatus Brown-marbled grouper Kushar كشر Er 11270 Epinephelus lanceolatus Giant grouper Kushar twini كشر طويني SA 9271 Epinephelus malabaricus Malabar grouper Kushar twini كشر طويني Er,SA 9,10272 Epinephelus merra Honeycomb grouper Ghoshar قشار Su 6273 Epinephelus morrhua Comet grouper Daghma دغمة Aq 14274 Kushar abu lulu كشر ابو لولو SA 1275 Epinephelus polylepis Smallscaled grouper Angar عنقر Ye 15276 Epinephelus polyphekadion Camouflage grouper Gishir جيشر Su 5277 Kushar كشر Er 11278 Epinephelus radiatus Oblique-banded grouper Daghma دغمة Aq 14279 Epinephelus spp. Sea basses: groupers and fairy

bassletsKushar كشر Er,SA 9,10

280 Epinephelus summana Summan grouper Kushar mubal’at كشر موبالات Er,SA 1,11281 Gishir جيشر Su 5282 Aqshar اقشر Aq 14283 Epinephelus tauvina Greasy grouper Hubog حوبج SA 9284 Tauwina طوينا Er,Su 5,6,7,11285 Toona تونا Su 7286 Gishir tauwina جيشر توينه Su 5,6,7287 Kushar tauwina كشر توينه Eg,SA 1,12288 Aqshar اقشر Aq 14289 Kushar كشر Er,Ye 2,11290 Etelis carbunculus Ruby snapper Hamaroon حمرون Su 5,7291 Etrumeus teres Red-eye round herring Sardin سردين Su 5292 Sardina masreya سردينه مصرية Aq 14293 Euthynnus affinis Kawakawa Ma’agab ماعجب Er,SA,Su 1,5,6,7,10294 Abu dam ابو دجن Su 5,6,7295 Fatla فتلة Aq 14296 Zainub زينب Ye 2297 Tun تن Ye 2298 Sherwa شروة Er,Ye 2,11299 Tonno تونو Er 11300 Exallias brevis Leopard blenny Arfaj عرفج Aq 14

214

Table A1 continuedNo. Scientific name Common name Local name Arabic name Country Source301 Fenneropenaeus indicus Indian white prawn Gamberi جمبري Er 11302 Fistularia commersonii Bluespotted cornetfish Qasaba كسبا Aq 14303 Fistularia spp. Cornetfishes Khurm al baaha خرم الباحه SA 1304 Galeocerdo cuvier Tiger shark Abu nebir ابو نبير Er 10305 Nebrawi نبراوي Er 11306 Gursh nimrany قرش نمراني SA 1307 Numrani نمراني Ye 3308 Gursh قرش Aq 14309 Genicanthus caudovittatus Zebra angelfish Moscht مشط Aq 14310 Gerres longirostris Strongspine silver-biddy Mukeresh مكارش Er 11311 Gerres oyena Common silver-biddy Kass كس Er,SA,Su 1,6,7,11312 Rishan ريشان Aq 14313 Mehara مهارا Ye 15314 Gerres spp. Mojarras Abu gurz ابو جرز SA 9315 Gash قش SA 9316 Afs عفس SA 9317 Glaucostegus halavi Halavi ray O’ud عود Er 11318 Gnathanodon speciosus Golden trevally Bagesh بجيش Ye 2319 Beyad gaz بياد جاز SA 1320 Beyad بياد Er,Su 5,11321 Gomphosus caeruleus Green birdmouth wrasse Muesy ميسي Aq 14322 Grammistes spp. Sea basses: groupers and fairy

bassletsKushar abu adas كشر ابو عدس SA 1

323 Gymnocranius grandoculis Blue-lined large-eye bream Qamar قمر Aq 14324 Gymnosarda unicolor Dogtooth tuna Shak abu ein شك ابو عين Aq 14325 Tomad تمد Su 5326 Gymnothorax johnsoni Whitespotted moray Qmum قموم Aq 14327 Gymnothorax nudivomer Starry moray Qmum قموم Aq 14328 Gymnothorax spp. Moray eels Shaaga شعاجه SA 1329 Gymnothorax undulatus Undulated moray Shaaga شعاجه SA 1330 Haemulidae Grunts Nakem ناكم Ye 2331 Getran جيتران Er 10332 Sobaity سوبيتى Er 10333 Shatef شاتف Er 10334 Shefsh شيفش Er 10335 Koko كوكو Er 10336 Halichoeres hortulanus Checkerboard wrasse Muesy ميسي Aq 14337 Deek ديك SA 1338 Halichoeres scapularis Zigzag wrasse Muesy ميسي Aq 14339 Hemiramphus spp. Halfbeaks Selenti سيلينتى Su 5340 Heniochus acuminatus Pennant coralfish Gringish جرينجش SA 1341 Heniochus diphreutes False moorish idol Um shiraa ام شراع Aq 14342 Heniochus intermedius Red Sea bannerfish Um shiraa ام شراع Aq 14343 Herklotsichthys punctatus Spotback herring Shagool شجول Su 5344 Herklotsichthys

quadrimaculatusBluestripe herring Sardina سردينه Aq 14

345 Belem بليم Er 11346 Aida عيدة Er 11347 Abu ras ابو راس Er 11348 Himantura uarnak Honeycomb stingray Abromis ابروميس Er 11349 Halali هلالى Er 11350 Hippocampus histrix Thorny seahorse Hisan al-Bahar حصان البحر Aq 14351 Hippocampus kuda Spotted seahorse Hisan al-Bahar حصان البحر Aq 14352 Hippocampus spp. Pipefishes and seahorses Fara al bahr فاره البحر SA 1353 Hipposcarus harid Candelamoa parrotfish Harid حريد Aq,Su 5,14354 Holothuriidae Sea cucumber Kheiar albahr خيار البحر Ye 4355 Hidra حيدره Er 15356 Hypoatherina temminckii Samoan silverside Gashgoosha جشجوشه SA 1357 Hyporhamphus dussumieri Dussimier’s halfbeak Zirgaan زيرجان SA 1358 Silinti سيلنتي Su 6359 Hyporhamphus gamberur Red Sea halfbeak Korom قورم Er 11360 Far فار Er 11361 Iniistius pentadactylus Fivefinger wrasse Far al-Bahar فار البحر Aq 14

Local names - Tesfamichael and Saeed 215

Table A1 continuedNo. Scientific name Common name Local name Arabic name Country Source362 Istiblennius edentulus Rippled rockskipper Arfaj عرفج Aq 14363 Istiompax indica Black marlin Faras al Bahr فارس البحر SA 1364 Istiophoridae Billfishes Feraz فيرز Ye 2365 Istiophorus platypterus Indo-Pacific sailfish Abu feres ابو فيراس Er 11366 Abu shirah ابو شراع Su 5,6367 Faras al Bahr فارس البحر SA,Su 1,5,6368 Faras فارس Aq 14369 Isurus spp. Mackerel sharks or white shark Gursh deeba قرش ديبا SA 1370 Katsuwonus pelamis Skipjack tuna Ma’agab ماعجب SA 1371 Fatleh فتله Aq 14372 Tuna تونة Su 5373 Zeinub زينوب Er 11374 Sherwi شروي Er 11375 Kuhlia mugil Barred flagtail Ghlaimeh جليمه Aq 14376 Kyphosus cinerascens Blue seachub Tahmal تحمل SA 1377 Lagocephalus sceleratus Silver-cheeked toadfish Alnaguem الناقم Aq 14378 Leiognathidae Slimys, slipmouths, or

ponyfishesAfsh عفش Er 10

379 Botatos بوطاطوس Er 10380 Kash كش Ye 2381 Gutat جوتات Er 10382 Leiognathus spp. Slimys,slipmouths,or ponyfishes Arian عريان Su 5383 Abu gurz ابو جرز SA 1384 Leptoscarus vaigiensis Marbled parrotfish Hareeth حريث SA 1385 Lethrinidae Emperors or scavengers Afsh عفش Ye 2386 Shu’ur شعور Er,Su 8,10387 Terhani ترهاني Er 10388 Lethrinus borbonicus Snubnose emperor Qeda قدة Aq 14389 Lethrinus harak Thumbprint emperor Shu’ur شعور Er,Su 5,10390 Abu nugta ابو نقطة Er,Su 5,10391 Lethrinus lentjan Pink ear emperor Suli صولي Er 11392 Shu’ur شعور Er,Su 5,10393 Lethrinus mahsena Sky emperor Qeda قدة Aq 14394 Shu’ur شعور Er,Su 5,10395 Mahsena محسنه Er 11396 Lethrinus microdon Smalltooth emperor Shu’ur شعور Er 10397 Suli صولي Er 10398 Lethrinus miniatus Trumpet emperor Shu’ur dibi شعور دبي SA 9399 Lethrinus nebulosus Spangled emperor Shu’ur ramaka شعور رامكا SA 9400 Shu’ur mehseny شعور محيسنى SA 1401 Shu’ur شعور Aq,Er,Su 5,10,14402 Afsh عفش Ye 2403 Suli صولي Er 11404 Lethrinus spp. Emperors or scavengers Shu’ur abu zahwa شعور ابو زهوه SA 1405 Gash قش Ye 3406 Shu’ur ramaka شعور رامكا SA 1407 Shu’ur khirmiya شعور خرمية SA 1408 Afsh عفش Ye 3409 Shu’ur deeb شعور ديب SA 1410 Shu’ur شعور SA,Su 5,7,9411 Lethrinus variegatus Slender emperor Bunqus khermawi بنقوس خرماوي Aq 14412 Liza macrolepis Largescale mullet Arabi عربي Er,SA 1,11413 Liza vaigiensis Squaretail mullet Arabi عربي Er 10414 Lobotes surinamensis Atlantic tripletail Abu hajar ابو هاجر Er 11415 Rougaah روجاه SA 9416 Loliginidae Squids Kalamari كلاماري Su 5417 Loligo forbesii Veined squid Abu midad ابو مداد Er 11418 Lutjanidae Snappers Shaefen شعفن Er 10419 Anteg عنتق Er 10420 Sheik ali شيخ على Er 10421 Farsi فارسي Su 8422 Huberi حوبيري Er 10

216

Table A1 continuedNo. Scientific name Common name Local name Arabic name Country Source423 Lutjanidae Snappers Naisarah نيصاره Er 10424 Bohar بوهر Er 10425 Lutjanus argentimaculatus Mangrove red snapper Safin سفين Su 5,6,7426 Shaefen شعفن Er,SA 1,11427 Lutjanus bohar Two-spot red snapper Garabganat جرابجانت Su 7428 Lolab لو لاب Su 7429 Bohar بوهر Aq,Er,SA,Su,Ye 1,2,5,7,9,10430 Lutjanus ehrenbergii Blackspot snapper Hebra حبرا Aq 14431 Shaefen شعفن Er 11432 Lutjanus fulviflamma Dory snapper Hubr حوبر)حبر( SA 1433 Shaefen شعفن Er 11434 Habair هبير Su 5,6,7435 Hobara هوبارا SA 9436 Lutjanus gibbus Humpback red snapper Himbuk هيمبوك Er 11437 Asmoodi عصمودي SA 1438 Bohar بوهر Er 10439 Asmoot عصموت Er,Su 5,6,11440 Huberi حوبيري Er 10441 Lutjanus johnii John’s snapper Hubr حوبر)حبر( SA 1442 Lutjanus kasmira Common bluestripe snapper Huberi حوبيري Er,SA 1,10443 Ableen asfar ابلين عصفر Su 5,6,7444 Bohar بوهر Er 10445 Lutjanus lutjanus Bigeye snapper Shukrum شخروم Su 5446 Lutjanus malabaricus Malabar blood snapper Hamari حماري Er 11447 Gehab جيهاب Er 10448 Bohar بوهر Er 10449 Lutjanus rivulatus Blubberlip snapper Shaefen شعفن Er 11450 Lutjanus russellii Russell’s snapper Hubr حوبر)حبر( SA 1451 Lutjanus sanguineus Humphead snapper Nirjan نيرجان Ye 2452 Morjan مرجان Ye 2453 Lutjanus sebae Emperor red snapper Himbuk هيمبوك Er 11454 Lutjanus spp. Snappers Hobara هوبارا SA 9455 Asmoot عصموت Su 8456 Macolor niger Black and white snapper Kust كست Su 5457 Shaefen شعفن Er 11458 Kut كت Su 7459 Makaira nigricans Blue marlin Faras al Bahr فارس البحر SA 1460 Manta spp. Eagle and manta rays Rugia milla روجي ميله SA 1461 Marsupenaeus japonicus Kuruma prawn Gamberi جمبري Er 11462 Megalaspis cordyla Torpdeo scad Beyad turfa بياد طرفه SA 1463 Sherwi شروي Er 11464 Khurtum خرطوم Su 5,6,7465 Melicertus latisulcatus Western king prawn Gamberi جمبري Er 11466 Metapenaeus monoceros Speckled shrimp Gamberi جمبري Er 11467 Mobula spp. Eagle and manta rays Rugtia روجتيه SA 1468 Mola spp. Molas or Ocean Sunfishes Milla ميله SA 1469 Monacanthus spp. Filefishes Abu shaukah ابو شوكة SA 9470 Monodactylus argenteus Silver moony Haymaan حيمان SA 1471 Monotaxis grandoculis Humpnose big-eye bream Qamar Abu ein قمر ابو عين Aq 14472 Shu’ur abu’ayn شعور ابو عين SA 1473 Mugil cephalus Flathead grey mullet Arabi عربي Er,SA 1,10474 Mugil spp. Mullets Ka’oi كاوي Su 7475 Shole شول Su 7476 Fasekh فاسخ Su 7477 Tadab تدب Su 7478 Arabi عربي Su 5,7,8479 Jilan جيلان Su 7480 Sha’aboi شعبوي Su 8,7481 Mugilidae Mullets Arabi عربي Er,Ye 10,15482 Mullidae Goatfishes Barbuni بربونى Er 10483 Abu digin ابو دجن Er 10

Local names - Tesfamichael and Saeed 217

Table A1 continuedNo. Scientific name Common name Local name Arabic name Country Source484 Mullidae Goatfishes Abu sheneb ابو شنب Er 10485 Ambir امبير Ye 2486 Mulloidichthys flavolineatus Yellowstripe goatfish Abu digin ابو دجن Su 5487 Sabalan سبلان Aq 14488 Mulloidichthys vanicolensis Yellowfin goatfish Sabalan سبلان Aq 14489 Mustelus mosis Arabian smooth-hound Gursh قرش Aq 14490 Myripristis murdjan Pinecone soldierfish Fanas فانس Aq 14491 Iyya sagheera اييا صغيرة SA 1492 Narcine bentuviai Elat electric ray Khadala خداله Aq 14493 Naso brevirostris Spotted unicornfish Abu karn ابو قرن Er 11494 Kurnjal قرنجل Er 11495 Naso lituratus Orangespine unicornfish Akra abu garn عكرا ايبو جرم SA 1496 Rahu رحو Aq 14497 Naso spp. Surgeonfishes,tangs,unicornfi

shesAbu karn ابو قرن Su 8

498 Naso unicornis Bluespine unicornfish Abu garin ابو جرين SA,Su 1,5,6499 Rahu رحو Aq 14500 Kurnjal قرنجل Er 11501 Neamia octospina Eightspine cardinalfish Fanas فانس Aq 14502 Nebrius ferrugineus Tawny nurse shark Gursh massassa قرش مصاصا SA 1503 Negaprion acutidens Sicklefin lemon shark Autat عوتات Er 11504 Zingi زنجي Er 11505 Nemipteridae Threadfin breams Sare سار Er 10506 Ser’a سيره Er 10507 Nemipterus japonicus Japanese threadfin bream Sare سار Eg 12508 Homiara حوميره Ye 2509 Morjan مرجان SA 9510 Nemipterus marginatus Red filament threadfin bream Fares فارس Eg 12511 Nemipterus spp. Threadfin breams Morjan مرجان SA 9512 Nofrah نوفره SA 9513 Neoniphon sammara Sammara squirrelfish Kheha خيها Aq 14514 Iyya sagheera اييا صغيرة SA 1515 Netuma thalassina Giant seacatfish Garmout قرموط Su 5516 Kumal كومل Er 11517 Shilan شيلان Er 10518 Octopus aegina Sandbird octopus Amfesis امفيسيس Er 11519 Akhtebut اخطبوط Er 11520 Octopus cyanea Big blue octopus Akhtebut اخطبوط Er 11521 Amfesis امفيسيس Er 11522 Octopus vulgaris Common octopus Akhtebut اخطبوط Er 11523 Amfesis امفيسيس Er 11524 Odonus niger Red-toothed triggerfish Shuroma شرومة Aq 14525 Oedalechilus labiosus Hornlip mullet Arabi عربي Er 10526 Ostichthys hypsipterygion Kheha خيها Aq 14527 Ostracion cubicus Yellow boxfish Abu sandoug ابو صندوق SA,Su 1,6528 Sanduk al-bahar صندوق البحر Aq 14529 Ostracion cyanurus Bluetail trunkfish Sanduk al-bahar صندوق البحر Aq 14530 Ostracion spp. Boxfishes Abu sandoug ابو صندوق SA 9531 Otolithes spp. Drums or croakers Lut لت Su 5532 Oxycheilinus diagramma Cheeklined wrasse Abu mulees ابو مليس SA 1533 Palinuridae Spiny lobsters Um ruban ام ربان Ye 2534 Sharkha شركا Er 10535 Panulirus homarus Scalloped spiny lobster Sharkha شركا Er 11536 Langus لانجس Er 11537 Panulirus ornatus Ornate spiny lobster Langus لانجس Er 11538 Sharkha شركا Er 10539 Panulirus penicillatus Pronghorn spiny lobster Sharkha شركا Er 10540 Panulirus spp. Spiny lobsters Estakoza استاكوزا Su 5541 Panulirus versicolor Painted spiny lobster Sharkha شركا Er 10542 Langus لانجس Er 11543 Paracaesio xanthura Yellowtail blue snapper Sarra’ ساره SA 1544 Paraexocoetus spp. Flyingfishes Jiraad al bahr جرده البحر SA 1

218Table A1 continued

No. Scientific name Common name Local name Arabic name Country Source545 Paramonacanthus pusillus Faintstripe filefish Um qaren ام قرن Aq 14546 Parapercis hexophtalma Speckled sandperch Dab ramly دب رملي Aq 14547 Parapercis somaliensis Somali sandperch Dab دب Aq 14548 Parastromateus niger Black pomfret Alsa السا Er 11549 Pardachirus marmoratus Finless sole Tabaq طبق Aq 14550 Pardachirus spp. Soles Hisan al-Bahar حصان البحر SA 1551 Parexocoetus brachypterus Sailfin flyingfish Farash فراش Aq 14552 Parupeneus cyclostomus Gold-saddle goatfish Sabalan asfar سبلان اصفر Aq 14553 Parupeneus forsskali Red Sea goatfish Sabalan abu nocta سبلان ابو نقطة Aq 14554 Abu digin ابو دجن SA 1555 Inber baladi عنبر بلدي Eg 12556 Parupeneus heptacanthus Cinnabar goatfish Sabalan سبلان Aq 14557 Abu sheneb ابو شنب Er 11558 Parupeneus macronemus Long-barbel goatfish Sabalan ahmar سبلان احمر Aq 14559 Parupeneus rubescens Rosy goatfish Barbuni بربونى Er 10560 Abu sheneb ابو شنب Er 10561 Sabalan سبلان Aq 14562 Abu digin ابو دجن Er 10563 Parupeneus spp. Goatfishes Abu sheneb ابو شنب Su 5564 Pempheris vanicolensis Vanikoro sweeper Fanas فانس Aq 14565 Penaeus monodon Giant tiger prawn Gamberi جمبري Er 11566 Penaeus semisulcatus Green tiger prawn Gamberi جمبري Er 11567 Penaeus spp. Shrimps Rubean روبين Ye 2568 Gamberi جمبري Su,Ye 2,5569 Zinga زينجا Ye 2570 Abu gobgab ابو قبقاب SA 9571 Pervagor randalli Um qaren ام قرن Aq 14572 Platax orbicularis Orbicular batfish Kanaf كناف Su 5,7573 Platax pinnatus Dusky batfish Kanaf كناف SA 1574 Platycephalidae Flathead Ro’ed رويد Er 10575 Ruad رواد Er 10576 Sumar صومر Er 10577 Plectorhinchus gaterinus Blackspotted rubberlip Qatran, staff قطرين, ستاف Aq 14578 Gadreneb جدرينيب Su 7579 Sobaity سوبيتى Er 11580 Gaterin جاترين Er,SA,Su 1,7,11581 Plectorhinchus schotaf Minstrel sweetlip Sobaity سوبيتى Er 11582 Shutaf شوطاف SA 1583 Istaf استاف Aq 14584 Telham تلهام Su 5,6,7585 Plectorhinchus spp. Sweetlips Gaterin جاترين Ye 3586 Plectropomus maculatus Spotted coralgrouper Kushar كشر Er 11587 Shu’ur شعور Er 10588 Najil ناجل Er,SA,Su 1,5,7,10589 Plectropomus pessuliferus Roving coralgrouper Najil ناجل Aq 14590 Plectropomus spp. Sea basses: groupers and fairy

bassletsNajil ناجل Su 8

591 Plicofollis dussumieri Blacktip catfish Kumal كومل Ye 2592 Polysteganus

coeruleopunctatusBlueskin seabream Fareedin فريدين Aq 14

593 Pomacanthus imperator Emperor angelfish Moscht مشط Aq 14594 Pomacanthus maculosus Yellowbar angelfish Moscht مشط Aq 14595 Pomadasys argenteus Silver grunt Koko كوكو Er,Su 5,10596 Shefsh شيفش Er 10597 Getran جيتران Er 10598 Sobaity سوبيتى Er 10599 Shatef شاتف Er 10600 Pomadasys commersonnii Smallspotted grunter Koko كوكو Su 5601 Nakem ناكم SA 1602 Pomadasys kaakan Javelin grunter Sobaity سوبيتى Er 11603 Getran جيتران Er 11604 Pomadasys spp. Grunter Nakem ناكم Ye 3605 Abu hajar ابو هاجر Ye 3

Local names - Tesfamichael and Saeed 219

Table A1 continuedNo. Scientific name Common name Local name Arabic name Country Source606 Pomadasys striatus Striped grunter Ibin skab ابن سكاب Su 5607 Pomadasys stridens Striped piggy Khushrum خشروم Aq 14608 Shukrum شخروم Eg 12609 Pomocentrus trichourus Paletail damsel Kharayeh خاراية Aq 14610 Portunus pelagicus Flower crab Abu mekass ابو مقص Er 11611 Kaboriah كبوريا Su 5612 Hinkakre هنكاكار Er 11613 Abu galambo ابو جلمبو Su 5614 Priacanthidae Bigeyes or catalufas Sahla سهله Er 10615 Sahr سحر Er 10616 Sahr el Leil سحر الليل Er 10617 Priacanthus hamrur Moontail bullseye Hamaroon حمرون SA 1618 Fanas abu-ein فناس ابو عين Aq 14619 Batel بطل Su 6,7620 Prionace glauca Blue shark Gursh قرش SA 1621 Pristipomoides filamentosus Crimson jobfish Koreib كوريب Su 5,7622 Pristipomoides multidens Goldband jobfish Anteg عنتق Er 10623 Pristipomoides spp. Snappers Fars فرس SA 1624 Sarra’ ساره SA 1625 Pristis pectinata Sawfish Abu minshar ابو منشار SA 9626 Pristis spp. Sawfishes Gursh abu minshaar قرش ابو منشار SA 1627 Psettodes erumei Indian spiny turbot Kelb كلب Ye 2628 Muse موس Er 10629 Mousa موسى Er 10630 Biedhikabiela بيضكبيلة Er 11631 Kutian كتيان Er 10632 Pseudobalistes

flavimarginatusYellowmargin triggerfish Ajame عجامة Er 11

633 Pseudobalistes fuscus Yellow-spotted triggerfish Hijma هجمه Aq 14634 Ajame عجامة Er 11635 Pseudorhombus arsius Largetooth flounder Shebet al bahir شيبت البحر Er 11636 Pterocaesio chrysozona Goldband fusilier Bagha باغة Aq 14637 Pterois miles Devil firefish Rana رنا Aq 14638 Pterois radiata Radial firefish Dujaaja al bahar دجاج البحر SA 1639 Rana رنا Aq 14640 Pterois volitans Red lionfish Dujaaja al bahar دجاج البحر SA 1641 Pygoplites diacanthus Regal angelfish Moscht مشط Aq 14642 Rachycentron canadum Cobia Shakan شكان Aq 14643 Sikin سيكين Er 10644 Fitle فيتل Er 10645 Sikla سيكلا Er 10646 Kuml nu’aakhr كمل نواخر SA 1647 Fatla فتلة Er 10648 Hutian حوتين Er 10649 Rachycentron spp. Cobia Sakhala سخاله Ye 3650 Rastrelliger kanagurta Indian mackerel Bagha باغة Er,SA,Su,Ye 1,2,5,10651 Scombry سقمبري Eg 13652 Sardina سردينه Aq 14653 Remora remora Shark sucker Qamlet alqersh قملة القرش Aq 14654 Rhabdosargus sarba Goldlined seabream Areedh عريض SA 1655 Eibad عيبد Su 5,6,7656 Haffar حفار Aq 14657 Rhincodon typus Whale shark Battan بطان Aq 14658 Gursh bitaan قرش بيتان SA 1659 Rhinecanthus assasi Picasso triggerfish Ajame عجامة Er 11660 Khanzeer خنزير SA 1661 Rhinobatos punctifer Spotted guitarfish Salfooh صلفوه Aq 14662 Rhinobatos spp. Guitarfishes Orab عراب SA 9663 Gursh abu halawa قرش ابو حلاوة SA 1664 Rhizoprionodon acutus Milk shark Autat عوتات Er 11665 Rhynchobatus djiddensis Giant guitarfish Bera بيرة Ye 2666 Bakhat باخات Ye 2

220Table A1 continued

No. Scientific name Common name Local name Arabic name Country Source667 Rhynchobatus djiddensis Giant guitarfish Fakhadoo فكهدو Ye 2668 Sarda orientalis Striped bonito Dirak ديرك Aq 14669 Sardinella gibbosa Goldstripe sardinella Sardin سردين Su 5670 Belem بليم Er 11671 Aida عيدة Er 11672 Sardinella jussieu Mauritian sardinella Sardina mofatar سردينه مفطر Eg 13673 Sardinella longiceps Indian oil sardine Sardin سردين Su 5674 Sardinella melanura Blacktip sardinella Toom توم Eg 13675 Sardin سردين SA,Su 1,5676 Sargocentron

caudimaculatumSilverspot squirrelfish Kheha خيها Aq 14

677 Sargocentron diadema Crown squirrelfish Fanas فانس Aq 14678 Sargocentron rubrum Redcoat Keha كهة Aq 14679 Gagaloom جاجالوم Su 6,7680 Sargocentron spiniferum Sabre squirrelfish Gehaya جحية Er 11681 Gagaloom جاجالوم Su 5,7682 Iyya kabeera اييا كبيرة SA 1683 Saurida gracilis Gracile lizardfish Macarona مكرونا Er 11684 Saurida macrolepis Haret حارت Eg 12685 Saurida tumbil Greater lizardfish Baram برم Ye 2686 Dab دب Aq 14687 Macarona مكرونا Er,SA,Su 5,9,11688 Harret حريت Eg,SA 9,12689 Saurida undosquamis Brushtooth lizardfish Macarona مكرونا Er,Su 5,11690 Dab دب Aq 14691 Scaridae Parrotfish Harida حريدا Er 10692 Scarus collana Red Sea parrotfish Harid حريد Aq 14693 Harida حريدا Er 11694 Scarus ferrugineus Rusty parrotfish Ghabban غبان Aq 14695 Scarus frenatus Bridled parrotfish Harida حريدا Er 11696 Scarus fuscopurpureus Purple-brown parrotfish Ghabban غابان Aq 14697 Scarus genazonatus Sinai parrotfish Ghabban غبان Aq 14698 Scarus ghobban Blue-barred parrotfish Harid حريد Aq,Er,Su 5,11,14699 Scarus gibbus Heavybeak parrotfish Ghabban غبان Aq 14700 Scarus niger Dusky parrotfish Ghabban غبان Aq 14701 Scarus psittacus Common parrotfish Ghabban غبان Aq 14702 Scolopsis ghanam Arabian monocle bream Fanas abiadh فانس ابيض Aq 14703 Scomber colias Atlantic chub mackerel Shak al-zoor شك الزور Eg 13704 Scomber japonicus Chub mackerel Scombla سكمبلا Aq 14705 Bagha باغة SA 1706 Scomber spp. Mackerels,tunas,bonitos Bagha باغة SA 9707 Scomberoides

commersonnianusTalang queenfish Durab دورب Er 11

708 Scomberoides lysan Doublespotted queenfish Todaf توداف SA 1709 Durab دورب Er,Ye 2,11710 Shrow شرو Su 5,7711 Lysan لسان SA,Ye 1,2712 Scomberomorus commerson Narrow-barred Spanish mackerel Shak abu Isnan شك ابو اسنان Aq 14713 Dirak ديرك Er,SA,Su,Ye 1,2,5,10714 Scomberomorus guttatus Indo-Pacific king mackerel Dirak ديرك Su 5715 Scombridae Mackerels,tunas,bonitos Tun تن Ye 2716 Scherwa شروة Ye 2717 Scorpaenopsis barbatus Bearded scorpionfish Abu al-Laban ابو اللبن Aq 14718 Scorpaenopsis diabolus False stonefish Abu al-Laban ابو اللبن Aq 14719 Scorpaenopsis gibbosa Humpbacked scorpionfish Agrab اجرب SA 1720 Scorpaenopsis spp. Scorpionfishes or rockfishes Agrab اجرب SA 1721 Scylla serrata Giant mud crab Hinkakre هنكاكار Er 11722 Abu mekass ابو مقص Er 11723 Sepia australis Southern cuttlefish Um el hibir ام الحبر Er 11724 Abu midad ابو مداد Er 11725 Sepia latimanus Broadclub cuttlefish Um el hibir ام الحبر Er 11726 Abu midad ابو مداد Er 11727 Sepia pharaonis Pharaoh cuttlefish Abu midad ابو مداد Er 11

Local names - Tesfamichael and Saeed 221

Table A1 continuedNo. Scientific name Common name Local name Arabic name Country Source728 Sepia pharaonis Pharaoh cuttlefish Um el hibir ام الحبر Er 11729 Sepia spp. Cuttlefishes Fakhd فكهد Ye 3730 Sepiidae Cuttlefishes Sebia سيبيا Su 5731 Seriola dumerili Greater amberjack Hea هيا Aq 14732 Seriola rivoliana Longfin yellowtail Beyad بياد Er 10733 Seriola spp. Jacks and pompanos Nazkha نزخة SA 1734 Seriolina nigrofasciata Blackbanded trevally Beyad بياد Er 10735 Serranidae Sea basses: groupers and fairy

bassletsKushar كشر Er,Ye 2,10

736 Tauwina طوينا Ye 3737 Siganus argenteus Streamlined spinefoot Sigan سجان Er 11738 Sigan khudhary سيجان خضاري Aq 14739 Siganus lineatus Golden-lined spinefoot Sigan سجان Su 6740 Siganus luridus Dusky spinefoot Sigan harafi سيجان حرفي Aq 14741 Siganus rivulatus Marbled spinefoot Sigan biady سجان بيادي Aq 14742 Sigan سجان Er,SA,Su 9,11,15743 Siganus sp. Rabitfishes Sigan سجان Su 5744 Siganus stellatus Brown-spotted spinefoot Sigan سجان Aq 14745 Sigan al baha سجان الباحا SA 1746 Sillago sihama Silver sillago Rakad راكاد SA 9747 Sillago spp. Smelt-whitings Al makhfi المخفي Ye 3748 Al ankood العنقود Ye 3749 Soleichthys heterorhinos Black-tip sole Tabaq طبق Aq 14750 Sparidae Porgies Abyad ابيض Er 10751 Fafal فافل Er 10752 Afsh عفش Ye 4753 Sparus aurata Gilthead seabream Danees دنس Aq 14754 Sphyraena barracuda Great barracuda Iqama عقامه Aq 14755 Agam عقام Er,SA,Su,Ye 3,5,9,10756 Todaf توداف Er 11757 Sphyraena flavicauda Yellowtail barracuda Malleeta مليتة Aq 14758 Sphyraena forsteri Bigeye barracuda Todaf توداف Er 10759 Agam عقام Er 10760 Sphyraena jello Pickhandle barracuda Agam عقام Er,SA 1,10761 Todaf توداف Er,Ye 2,10762 Agous اجوس Su 5,6763 Khod خد Ye 2764 Sphyraena obtusata Obtuse barracuda Zreighan زريغان SA,Su 1,5,6765 Todaf توداف Er 11766 Agam عقام Er 11767 Sphyraena putnamiae Sawtooth barracuda Iqama عقامه Aq 14768 Sphyraena spp. Barracudas Khod خد Ye 3769 Agam عقام Ye 3770 Sphyraenidae Barracudas Todaf توداف Er 10771 Mekazel مكازل Er 10772 Zuran زوران Er 10773 Agam عقام Er 10774 Zuria زوريا Er 10775 Sphyrna lewini Scalloped hammerhead Gurna قرن Er 11776 Gursh abu burnetta قرش ابو برنيطة Aq 14777 Gurur جرور Er 11778 Sphyrna zygaena Smooth hammerhead Gursh gurna قرش قرنا SA 1779 Stolephorus indicus Indian anchovy Figayma فيجيمة SA 1780 Stolephorus spp. Anchovies Fagima فقيمة Su 5781 Stromateus spp. Butterfishes Abu gurz ابو جرز SA 9782 Sufflamen albicaudatum Bluethroat triggerfish Ajame عجامة Er 11783 Um qaren ام قرن Aq 14784 Synanceia verrucosa Stonefish Agrab اجرب SA 1785 Abu al-Laban ابو اللبن Aq 14786 Synodontidae Lizardfishes Macarona مكرونا Er 10787 Haret حارت Er 10788 Synodus hoshinonis Blackear lizardfish Dab دب Aq 14

222

Table A1 continuedNo. Scientific name Common name Local name Arabic name Country Source789 Synodus variegatus Variegated lizardfish Dab دب Aq 14790 Tachysurus spp. Sea catfishes Kumal كومل SA 1791 Taeniura lymma Ribbontail stingray Halali هلالى Er 11792 Abromis ابروميس Er 11793 Rugtia saghirah روجتيه صغيرة SA 1794 Um qurbal ام كربل Aq 14795 Terapon jarbua Jarbua terapon Shukrum شخروم Er,Su 5,10796 Tetraodon spp. Tetraodontidae Arradh عراض SA 9797 Tetraodontidae Puffers Morjan مرجان Er 10798 Tetrosomus gibbosus Humpback turretfish Sanduk al-bahar صندوق البحر Aq 14799 Thalassoma klunzingeri Klunzinger’s wrasse Muesy ميسي Aq 14800 Thalassoma lunare Moon wrasse Muesy ميسي Aq 14801 Thalassoma spp. Wrasses Deek ديك SA 1802 Thamnaconus modestoides Modest filefish Um qaren ام قرن Aq 14803 Thenus orientalis Flathead lobster Langus لانجس Er 11804 Sharkha شركا Er 10805 Stacoza استاكوزا Er 10806 Therapon jarbua Jarbua terapon Henw هنو Aq 14807 Therapon spp. Therapon Shukrum شخروم SA 9808 Jaabul جبول Ye 3809 Thryssa baelama Baelama anchovy Belem بليم Er 11810 Aida عيدة Er 11811 Thunnus alalunga Albacore Tuna تونة Su 5812 Shak شك Aq 14813 Thunnus albacares Yellowfin tuna Shak zoor شك زور Aq 14814 Tuna تونة Su 5815 Thumad ثمد SA 1816 Thunnus obesus Bigeye tuna Zeinub زينوب Ye 3817 Thunnus tonggol Longtail tuna Sherwi شروي Er 11818 Tuna تونة Er,Su 5,11819 Shak Abu thiel شك ابو ذيل Aq 14820 Tomad تمد Er 10821 Thyrsitoides jordanus Black snoek Saif سيف Aq 14822 Torpedo panthera Panther electric ray Rugtia kaharabiyyah روجتيه كهربائية SA 1823 Khadala ramlya خداله رمليه Aq 14824 Torquigener flavimaculatus Hadhroom حضروم Aq 14825 Trachinocephalus myops Snakefish Dab دب Aq 14826 Haret حارت Eg 12827 Trachinotus baillonii Smallspotted dart Teiman طيمان Su 5,6828 Trachinotus blochii Subnose pompano Beyad بياد Er 10829 Pompano بمبانو Er 11830 Teiman طيمان SA,Su 1,5,6,7831 Trachurus indicus Arabian scad Sardina aredha سردينه عريضة Aq 14832 Bagha باغة Su 5833 Trachyrhamphus bicoarctatus Double-ended pipefish Masas ماساس Aq 14834 Triaenodon obesus Whitetip reef shark Sweida سويدا Er 11835 Trichiurus lepturus Largehead hairtail Saif سيف Aq 14836 Trichiurus spp. Cutlassfishes Homalan هوملان Ye 4837 Abu saif ابو سيف SA,Ye 3,9838 Trochidae Trochus shell Kokian كوكيان Er 10839 Tylosurus crocodilus

crocodilusHound needlefish Kharam خرم Er 11

840 Kombir كومبير SA,Su 1,5,6,7841 Ulua mentalis Longrakered trevally Beyad بياد Er 10842 Upeneus moluccensis Goldband goatfish Sabalan سبلان Aq 14843 Abu digin ابو دجن Er 10844 Barbuni بربونى Er 10845 Abu sheneb ابو شنب Er 10846 Upeneus spp. Goatfishes Abu sheneb ابو شنب Su 5,7847 Barbuni بربونى SA 9848 Upeneus subvitatus Deep-water goatfish Sabalan سبلان Aq 14849 Upeneus sulphureus Sulphur goatfish Abu sheneb ابو شنب Su 6

Local names - Tesfamichael and Saeed 223

Table A1 continuedNo. Scientific name Common name Local name Arabic name Country Source850 Upeneus tragula Freckled goatfish Barbuni بربونى Eg 12851 Upeneus vittatus Yellowstriped goatfish Barbuni بربونى Eg 12852 Abu sheneb ابو شنب Er 11853 Uroteuthis duvauceli Indian squid Abu midad ابو مداد Er 11854 Valamugil cunnesius Longarm mullet Arabi عربي Er 10855 Valamugil seheli Bluespot mullet Arabi عربي Er,Su 5,10856 Valamugil spp. Mullet Arabi عربي SA 1857 Variola louti Yellow-edged lyretail Abu sherif ابو شريف SA 9858 Boosia بوسيا Aq 14859 Louti لوطى Er,SA,Su 1,5,6,7,10860 Rishal ريشال Er,Su 5,6,7,10861 Xiphias gladius Swordfish Faras al Bahr فارس البحر SA 1862 Abu seif ابو سيف Su 5,6,7863 Xiphiidae Swordfish Damriah دامريه Ye 2864 Xyrichtys melanopus Yellowpatch razorfish Far al-Bahar فار البحر Aq 14865 Xyrichtys pavo Peacock wrasse Far al-Bahar فار البحر Aq 14866 Zebrasoma velifer Sailfin tang Zizan زيزان Er 11867 Dajaje el baher دجاج البحر Er 11868 Zebrasoma xanthurum Yellowtail tang Zizan زيزان Er 11869 Juneh جنه Aq 14870 Gahm جهم Er 11

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Appendix Table A2: Common names of Red Sea fish and invertebrates sorted by local names in Arabic.Sourceb Countrya Common name Scientific name Local name Arabic name ID11 Er Honeycomb stingray Himantura uarnak Abromis ابروميس 111 Er Ribbontail stingray Taeniura lymma 25,6,7 Su Common bluestripe snapper Lutjanus kasmira Ableen asfar ابلين عصفر 35 Su Striped grunter Pomadasys striatus Ibin skab ابن سكاب 414 Aq Bearded scorpionfish Scorpaenopsis barbatus Abu al-Laban ابو اللبن 514 Aq False stonefish Scorpaenopsis diabolus 614 Aq Stonefish Synanceia verrucosa 711 Er Picnic seabream Acanthopagrus berda Abu berite ابو بريت 811 Er Twobar seabream Acanthopagrus bifasciatus 99 SA Mojarras Gerres spp. Abu gurz ابو جرز 101 SA Slimys,slipmouths,or ponyfishes Leiognathus spp. 119 SA Butterfishes Stromateus spp. 121 SA Heavybeak parrot fish Chlorurus gibbus Abu greeyan ابو جريان 131,5,6 SA,Su Bluespine unicornfish Naso unicornis Abu garin ابو جرين 145 Su Flower crab Portunus pelagicus Abu galambo ابو جلمبو 155,6,7 Su Humphead wrasse Cheilinus undulatus Abu jibba ابو جيبا 165,6,7 Su Kawakawa Euthynnus affinis Abu dam ابو دجن 1710 Er Goatfishes Mullidae Abu digin ابو دجن 185 Su Yellowstripe goatfish Mulloidichthys flavolineatus 191 SA Red Sea goatfish Parupeneus forsskali 2010 Er Rosy goatfish Parupeneus rubescens 2110 Er Goldband goatfish Upeneus moluccensis 2211 Er Bluestripe herring Herklotsichthys quadrimaculatus Abu ras ابو راس 2315 Ye Stingrays Dasyatidae Abu remis ابو راميز 245 Su Stingrays Dasyatis spp. Abu soot ابو سوط 251,5,6 SA,Su Dorab wolf-herring Chirocentrus dorab Abu seif ابو سيف 263,9 SA,Ye Cutlassfishes Trichiurus spp. 275,6,7 Su Swordfish Xiphias gladius 285,6 Su Indo-Pacific sailfish Istiophorus platypterus Abu shirah ابو شراع 2914 Aq Sixblotch hind Cephalopholis sexmaculata Abu shirni ابو شرني 309 SA Yellow-edged lyretail Variola louti Abu sherif ابو شريف 319 SA Sea catfishes Arius spp. Abu sheneb ابو شنب 3210 Er Goatfishes Mullidae 3311 Er Cinnabar goatfish Parupeneus heptacanthus 3410 Er Rosy goatfish Parupeneus rubescens 355 Su Goatfishes Parupeneus spp. 3610 Er Goldband goatfish Upeneus moluccensis 375,7 Su Goatfishes Upeneus spp. 386 Su Sulphur goatfish Upeneus sulphureus 3911 Er Yellowstriped goatfish Upeneus vittatus 409 SA Filefishes Monacanthus spp. Abu shaukah ابو شوكة 411,6 SA,Su Yellow boxfish Ostracion cubicus Abu sandoug ابو صندوق 429 SA Boxfishes Ostracion spp. 4311 Er Areolate grouper Epinephelus areolatus Abu ades ابو عدس 4411 Er Indo-Pacific sailfish Istiophorus platypterus Abu feres ابو فيراس 459 SA Shrimps Peneaus spp. Abu gobgab ابو قبقاب 4611 Er Spotted unicornfish Naso brevirostris Abu karn ابو قرن 478 Su Surgeonfishes,tangs,unicornfishes Naso spp. 486 Su Picnic seabream Acanthopagrus berda Abu kuhul ابو كحل 495,7,10 Er,Su Twobar seabream Acanthopagrus bifasciatus 5011 Er Veined squid Loligo forbesii Abu midad ابو مداد 5111 Er Southern cuttlefish Sepia australis 5211 Er Broadclub cuttlefish Sepia latimanus 5311 Er Pharaoh cuttlefish Sepia pharaonis 5411 Er Indian squid Uroteuthis duvauceli 552,3 Ye Crab Brachyura Abu mokas ابو مقص 56a Aq = Aquaba (mainly Jordan), Eg = Egypt, Er = Eritrea, SA = Saudi Arabia, Su = Sudan, Ye = Yemenb 1 Barrania et al. (1980), 2 Walczak and Gudmundsson (1975), 3 Walczak (1977), 4 Bonfiglioli and Hariri (2004), 5 MEPI (1993), 6 Abu-Gideiri (1984), 7 Reed (1964), 8 FHAS (1984), 9 El-Saby and Farina (1954), 10 MOF (2012), 11 Tesfamichael and Sebahtu (2006), 12 Bayoumi (1972), 13 Rafail (1972), 14 Khalaf and Disi (1997), 15 Interview.

Local names - Tesfamichael and Saeed 225

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID11 Er Flower crab Portunus pelagicus Abu mekass ابو مقص 5711 Er Giant mud crab Scylla serrata 581 SA Tripletail wrasse Cheilinus trilobatus Abu mulees ابو مليس 591 SA Cheeklined wrasse Oxycheilinus diagramma 609 SA Sawfish Pristis pectinata Abu minshar ابو منشار 6110 Er Tiger shark Galeocerdo cuvier Abu nebir ابو نبير 625,10 Er,Su Thumbprint emperor Lethrinus harak Abu nugta ابو نقطة 6311 Er Atlantic tripletail Lobotes surinamensis Abu hajar ابو هاجر 643 Ye Grunter Pomadasys spp. 6510 Er Twobar seabream Acanthopagrus bifasciatus Abyad ابيض 6610 Er King soldierbream Argyrops spinifer 6710 Er Porgies Sparidae 681 SA Humpbacked scorpionfish Scorpaenopsis gibbosa Agrab اجرب 691 SA Scorpionfishes or rockfishes Scorpaenopsis spp. 701 SA Stonefish Synanceia verrucosa 715,6 Su Pickhandle barracuda Sphyraena jello Agous اجوس 7211 Er Coral hind Cephalopholis miniata Ahmer احمر 7311 Er Sandbird octopus Octopus aegina Akhtebut اخطبوط 7411 Er Big blue octopus Octopus cyanea 7511 Er Common octopus Octopus vulgaris 765 Su Rainbow runner Elagatis bipinnulata Adad اداد 7714 Aq Painted sweetlips Diagramma pictum Istaf استاف 7814 Aq Minstrel sweetlip Plectorhinchus schotaf 795 Su Spiny lobsters Panulirus spp. Estakoza استاكوزا 8010 Er Flathead lobster Thenus orientalis Stacoza استاكوزا 8114 Aq Summan grouper Epinephelus summana Aqshar اقشر 8214 Aq Greasy grouper Epinephelus tauvina 8311 Er Black pomfret Parastromateus niger Alsa السا 843 Ye Smelt-whitings Sillago spp. Al ankood العنقود 853 Ye Smelt-whitings Sillago spp. Al makhfi المخفي 8614 Aq Silver-cheeked toadfish Lagocephalus sceleratus Alnaguem الناقم 8711 Er Southern cuttlefish Sepia australis Um el hibir ام الحبر 8811 Er Broadclub cuttlefish Sepia latimanus 8911 Er Pharaoh cuttlefish Sepia pharaonis 9014 Aq Twoband anemonefish Amphiprion bicinctus Om Al dukhan ام الدخان 912 Ye Spiny lobsters Palinuridae Um ruban ام ربان 9214 Aq False moorish idol Heniochus diphreutes Um shiraa ام شراع 9314 Aq Red Sea bannerfish Heniochus intermedius 941,5,7 SA,Su Common dolphinfish Coryphaena hippurus Um falloos ام فلوس 9514 Aq Unicorn leatherjacket filefish Aluterus monoceros Um qaren ام قرن 9614 Aq Broom filefish Amanses scopas 9714 Aq Orange-lined triggerfish Balistapus undulatus 9814 Aq Honeycomb filefish Cantherhines pardalis 9914 Aq Faintstripe filefish Paramonacanthus pusillus 10014 Aq Pervagor randalli 10114 Aq Bluethroat triggerfish Sufflamen albicaudatus 10214 Aq Modest filefish Thamnaconus modestoides 10314 Aq Ribbontail stingray Taeniura lymma Um qurbal ام كربل 1042 Ye Goatfishes Mullidae Ambir امبير 10511 Er Sandbird octopus Octopus aegina Amfesis امفيسيس 10611 Er Big blue octopus Octopus cyanea 10711 Er Common octopus Octopus vulgaris 10814 Aq Mackerel scad Decapterus macarellus Amia اميه 1091 SA Pinecone soldierfish Myripristis murdjan Iyya sagheera اييا صغيرة 1101 SA Sammara squirrelfish Neoniphon sammara 1111 SA Sabre squirrelfish Sargocentron spiniferum Iyya kabeera اييا كبيرة 1122 Ye Stingrays Dasyatidae Bakhat باخات 1132 Ye Giant guitarfish Rhynchobatus djiddensis 11414 Aq Lunar fusilier Caesio lunaris Bagha باغة 11514 Aq Suez fusilier Caesio suevica 1165 Su Japanise scad Decapterus maruadsi 117

226

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID13 Eg Round scad Decapterus punctatus Bagha باغة 11813 Eg Indian scad Decapterus russelli 11914 Aq Goldband fusilier Pterocaesio chrysozona 1201,2,5,10 Er,SA,Su,Ye Indian mackerel Rastrelliger kanagurta 1211 SA Chub mackerel Scomber japonicus 1229 SA Mackerels,tunas,bonitos Scomber spp. 1235 Su Arabian scad Trachurus indicus 12414 Aq Variable-lined fusilier Caesio varilineata Bagha hamra باغة حمراء 1252 Ye Golden trevally Gnathanodon speciosus Bagesh بجيش 12610 Er Goatfishes Mullidae Barbuni بربونى 12710 Er Rosy goatfish Parupeneus rubescens 12810 Er Goldband goatfish Upeneus moluccensis 1299 SA Goatfishes Upeneus spp. 13012 Eg Freckled goatfish Upeneus tragula 13112 Eg Yellowstriped goatfish Upeneus vittatus 1322 Ye Greater lizardfish Saurida tumbil Baram برم 13314 Aq Whale shark Rhincodon typus Battan بطان 1346,7 Su Moontail bullseye Priacanthus hamrur Batel بطل 13511 Er Twobar seabream Acanthopagrus bifasciatus Butel hammed بطل حماد 13611 Er Spotted sardinella Amblygaster sirm Belem بليم 13714 Aq Hardyhead silverside Atherinomorus lacunosus 13811 Er Rainbow sardine Dussumieria acuta 13911 Er Shorthead anchovy Encrasicholina heteroloba 14011 Er Bluestripe herring Herklotsichthys quadrimaculatus 14111 Er Goldstripe sardinella Sardinella gibbosa 14211 Er Baelama anchovy Thryssa baelama 14311 Er African pompano Alectis ciliaris Pompano بمبانو 14411 Er Subnose pompano Trachinotus blochii 14514 Aq Slender emperor Lethrinus variegatus Bunqus khermawi بنقوس خرماوي 1461,5,6,7 SA,Su Bonefish Albula vulpes Bounouk بو نوك 14714 Aq Yellow-edged lyretail Variola louti Boosia بوسيا 14810 Er Slimys, slipmouths, or ponyfishes Leiognathidae Botatos بوطاطوس 14914 Aq Starry flying gurnard Dactyloptena peterseni Boomet al-Bahar بومة البحر 1505,6,7 Su Milkfish Chanos chanos Bunji بونجي 15110 Er Snappers Lutjanidae Bohar بوهر 1521,2,5,7,9,10 Aq,Er,SA,Su,Ye Two-spot red snapper Lutjanus bohar 15310 Er Humpback red snapper Lutjanus gibbus 15410 Er Common bluestripe snapper Lutjanus kasmira 15510 Er Malabar blood snapper Lutjanus malabaricus 15610 Er African pompano Alectis ciliaris Beyad بياد 15711 Er Shrimp scad Alepes djedaba 1581,11 Er,SA Yellowtail scad Atule mate 15911 Er Longfin trevally Carangoides armatus 1605,10 Er,Su Orangespotted trevally Carangoides bajad 16111 Er Blue trevally Carangoides ferdau 16210 Er Bludger Carangoides gymnostethus 16311 Er Malabar trevally Carangoides malabaricus 1641,5,10 Er,SA,Su Giant trevally Caranx ignobilis 1651,5,10 Er,SA,Su Bigeye trevally Caranx sexfasciatus 1663,7,9,10 Er,SA,Su,Ye Jacks and pompanos Caranx spp. 16710 Er Rainbow runner Elagatis bipinnulata 1685,11 Er,Su Golden trevally Gnathanodon speciosus 16910 Er Longfin yellowtail Seriola rivoliana 17010 Er Blackbanded trevally Seriolina nigrofasciata 17110 Er Subnose pompano Trachinotus blochii 17210 Er Longrakered trevally Ulua mentalis 1731 SA Indian threadfish Alectis indicus Beyad abu tabag بياد ابو تابج 1741 SA Yellowspotted trevally Carangoides fulvoguttatus Beyad gaz بياد جاز 1751 SA Golden trevally Gnathanodon speciosus 1769 SA Orangespotted trevally Carangoides bajad Beyad gazza بياد جازة 1779 SA Coachwhip trevally Carangoides oblongus Beyad girm بياد جريم 178

Local names - Tesfamichael and Saeed 227

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID1,10 Er,SA Bluefin trevally Caranx melampygus Beyad girm بياد جريم 1796,10 Er,Su Coastal trevally Carangoides coeruleopinnatus Beyad goutar بياد جوتر 1805,11 Er,Su Yellowspotted trevally Carangoides fulvoguttatus 1811 SA Torpdeo scad Megalaspis cordyla Beyad turfa بياد طرفه 1822 Ye Giant guitarfish Rhynchobatus djiddensis Bera بيرة 18311 Er Indian spiny turbot Psettodes erumei Biedhikabiela بيضكبيلة 1841 SA Blue seachub Kyphosus cinerascens Tahmal تحمل 1856 Su Freckled tilefish Branchiostegus sawakinensis Theena تحينا 1867 Su Mullets Mugil spp. Tadab تدب 18710 Er Emperors or scavengers Lethrinidae Terhani ترهاني 1887 Su Jacks and pompanos Caranx spp. Tak’oi تكاوي 1895,6,7 Su Minstrel sweetlip Plectorhinchus schotaf Telham تلهام 1905 Su Dogtooth tuna Gymnosarda unicolor Tomad تمد 19110 Er Longtail tuna Thunnus tonggol 1922 Ye Kawakawa Euthynnus affinis Tun تن 1932 Ye Mackerels,tunas,bonitos Scombridae 1941 SA Doublespotted queenfish Scomberoides lysan Todaf توداف 19511 Er Great barracuda Sphyraena barracuda 19610 Er Bigeye barracuda Sphyraena forsteri 1972,10 Er,Ye Pickhandle barracuda Sphyraena jello 19811 Er Obtuse barracuda Sphyraena obtusata 19910 Er Barracudas Sphyraenidae 20013 Eg Blacktip sardinella Sardinella melanura Toom توم 2017 Su Greasy grouper Epinephelus tauvina Toona تونا 2025 Su Frigate tuna Auxis thazard thazard Tuna تونة 2035 Su Skipjack tuna Katsuwonus pelamis 2045 Su Albacore Thunnus alalunga 2055 Su Yellowfin tuna Thunnus albacares 2065,11 Er,Su Longtail tuna Thunnus tonggol 20711 Er Kawakawa Euthynnus affinis Tonno تونو 2081 SA Humphead wrasse Cheilinus undulatus Terbaany تيرباني 2091 SA Yellowfin tuna Thunnus albacares Thumad ثمد 2101,7,11 Er,SA,Su Blackspotted rubberlip Plectorhinchus gaterinus Gaterin جاترين 2113 Ye Sweetlips Plectorhinchus spp. 2126,7 Su Redcoat Sargocentron rubrum Gagaloom جاجالوم 2135,7 Su Sabre squirrelfish Sargocentron spiniferum 2143 Ye Therapon Therapon spp. Jaabul جبول 21511 Er Sabre squirrelfish Sargocentron spiniferum Gehaya جحية 2167 Su Blackspotted rubberlip Plectorhinchus gaterinus Gadreneb جدرينيب 2177 Su Two-spot red snapper Lutjanus bohar Garabganat جرابجانت 2181 SA Blackspotted hawkfish Cristacirrhitus punctatus Jarbua جربوعه 21914 Aq Soldierbream Argyrops filamentosus Jarbeeden جربيدن 2205,7 Su Hardyhead silverside Atherinomorus lacunosus Gurgush جرجوش 2211 SA Flyingfishes Paraexocoetus spp. Jiraad al bahr جرده البحر 22211 Er Scalloped hammerhead Sphyrna lewini Gurur جرور 2231 SA Threadfin butterflyfish Chaetodon auriga Gringish جرينجش 2241 SA Pennant coralfish Heniochus acuminatus 2251 SA Samoan silverside Hypoatherina temminckii Gashgoosha جشجوشه 22614 Aq Barred flagtail Kuhlia mugil Ghlaimeh جليمه 22711 Er Indian white prawn Fenneropenaeus indicus Gamberi جمبري 22811 Er Kuruma prawn Marsupenaeus japonicus 22911 Er Western king prawn Melicertus latisulcatus 23011 Er Speckled shrimp Metapenaeus monoceros 23111 Er Giant tiger prawn Penaeus monodon 23211 Er Green tiger prawn Penaeus semisulcatus 2332,5 Su,Ye Shrimps Penaeus spp. 2341 SA Live sharksucker Echeneis naucrates Gamla جمله 23514 Aq Brown surgeonfish Acanthurus nigrofuscus Juneh جنه 23614 Aq Striated surgeonfish Ctenochaetus striatus 23714 Aq Yellowtail tang Zebrasoma xanthurum 2385 Su Sea basses: groupers and fairy

bassletsCephalopholis spp. Gahlab جهلب 239

228

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID11 Er Ringtail surgeonfish Acanthurus blochii Gahm جهم 2401 SA Black surgeonfish Acanthurus gahhm 24111 Er Epaulette surgeonfish Acanthurus nigricauda 24211 Er Sohal surgeonfish Acanthurus sohal 24311 Er Yellowfin surgeonfish Acanthurus xanthopterus 24411 Er Yellowtail tang Zebrasoma xanthurum 2456 Su Peacock hind Cephalopholis argus Ghohlab جو هلاب 2466 Su Coral hind Cephalopholis miniata 2477 Su Jacks and pompanos Caranx spp. Goareit جواريت 24810 Er Slimys, slipmouths, or ponyfishes Leiognathidae Gutat جوتات 2495 Su Yellowspotted trevally Carangoides fulvoguttatus Gutur جوتر 25010 Er Grunts Haemulidae Getran جيتران 25110 Er Silver grunt Pomadasys argenteus 25211 Er Javelin grunter Pomadasys kaakan 2535 Su Giant trevally Caranx ignobilis Girim جيريم 2547 Su Jacks and pompanos Caranx spp. 2555 Su Brownspotted grouper Epinephelus chlorostigma Gishir جيشر 2565 Su Camouflage grouper Epinephelus polyphekadion 2575 Su Summan grouper Epinephelus summana 2585,6,7 Su Greasy grouper Epinephelus tauvina Gishir tauwina جيشر توينه 2595,6,7 Su Areolate grouper Epinephelus areolatus Gishir shooni جيشر شونى 2607 Su Mullets Mugil spp. Jilan جيلان 26110 Er Malabar blood snapper Lutjanus malabaricus Gehab جيهاب 26212 Eg Saurida macrolepis Haret حارت 26310 Er Lizardfishes Synodontidae 26412 Eg Snakefish Trachinocephalus myops 26514 Aq Blackspot snapper Lutjanus ehrenbergii Hebra حبرا 2669,12 Eg,SA Greater lizardfish Saurida tumbil Harret حريت 2671 SA Daisy parrotfish Cholorurus sordidus Hareeth حريث 2681 SA Marbled parrotfish Leptoscarus vaigiensis 2695,7 Su Parrotfishes Callyodon spp. Harid حريد 2705,14 Aq,Su Candelamoa parrotfish Hipposcarus harid 27114 Aq Red Sea parrotfish Scarus collana 2725,11,14 Aq,Er,Su Blue-barred parrotfish Scarus ghobban 27311 Er Green humphead parrotfish Bolbometopon muricatum Harida حريدا 27411 Er Bicolour parrotfish Cetoscarus bicolor 27510 Er Parrotfish Scaridae 27611 Er Red Sea parrotfish Scarus collana 27711 Er Bridled parrotfish Scarus frenatus 2781 SA Leopard flounder Bothus Pantherinus Hisan al-Bahar حصان البحر 2791 SA Fourlined tonguesole Cynoglossus bilineatus 28014 Aq Thorny seahorse Hippocampus histrix 28114 Aq Spotted seahorse Hippocampus kuda 2821 SA Soles Pardachirus spp. 28314 Aq Masked puffer Arothron diadematus Hadhroom حضروم 28414 Aq White-spotted puffer Arothron hispidus 28514 Aq Stellate puffer Arothron stellatus 28614 Aq Crowned puffer Canthigaster coronata 28714 Aq Pufferfish Canthigaster margaritata 28814 Aq Torquigener flavimaculatus 28914 Aq Spotbase burrfish Chilomycterus spilostylus Hadhroom abu

shoukaحضروم ابو شوكة 290

14 Aq Spot-fin porcupinefish Diodon hystrix 2919 SA Porgies Chrysoblephus spp. Haffar حفار 2921 SA Karenteen seabream Crenidens crenidens 29314 Aq Goldlined seabream Rhabdosargus sarba 29411 Er Malabar blood snapper Lutjanus malabaricus Hamari حماري 2955,7 Su Ruby snapper Etelis carbunculus Hamaroon حمرون 2961 SA Moontail bullseye Priacanthus hamrur 2971 SA Longfin African conger Conger cinereus Hanish silab حنيش سيلاب 2989 SA Greasy grouper Epinephelus tauvina Hubog حوبج 2991 SA Dory snapper Lutjanus fulviflamma Hubr حوبر)حبر( 300

Local names - Tesfamichael and Saeed 229

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID1 SA John’s snapper Lutjanus johnii Hubr حوبر)حبر( 3011 SA Russell’s snapper Lutjanus russellii 30210 Er Snappers Lutjanidae Huberi حوبيري 30310 Er Humpback red snapper Lutjanus gibbus 3041,10 Er,SA Common bluestripe snapper Lutjanus kasmira 30510 Er Cobia Rachycentron canadum Hutian حوتين 3062 Ye Japanese threadfin bream Nemipterus japonicus Homiara حوميره 30715 Er Sea cucumber Holothuriidae Hidra حيدره 30814 Aq Clown coris Coris aygula Heqab حيقب 3091 SA Silver moony Monodactylus argenteus Haymaan حيمان 31014 Aq Threespot dascyllus Dascyllus trimaculatus Kharayeh خاراية 31114 Aq Paletail damsel Pomocentrus trichourus 3121 SA Tenpounder Elops machnata Khanny خاني 3132 Ye Pickhandle barracuda Sphyraena jello Khod خد 3143 Ye Barracudas Sphyraena spp. 31514 Aq Elat electric ray Narcine bentuviai Khadala خداله 31614 Aq Panther electric ray Torpedo panthera Khadala ramlya خداله رمليه 3175,6,7 Su Torpdeo scad Megalaspis cordyla Khurtum خرطوم 31811 Er Hound needlefish Tylosurus crocodilus crocodilus Kharam خرم 3191 SA Cornetfishes Fistularia spp. Khurm al baaha خرم الباحه 32014 Aq Striped piggy Pomadasys stridens Khushrum خشروم 3211 SA Orange-lined triggerfish Balistapus undulatus Khanzeer خنزير 3221 SA Picasso triggerfish Rhinecanthus assasi 3234 Ye Sea cucumber Holothuriidae Kheiar albahr خيار البحر 32414 Aq Sammara squirrelfish Neoniphon sammara Kheha خيها 32514 Aq Ostichthys hypsipterygion 32614 Aq Silverspot squirrelfish Sargocentron caudimaculatum 3272 Ye Swordfish Xiphiidae Damriah دامريه 32814 Aq Somali sandperch Parapercis somaliensis Dab دب 32914 Aq Greater lizardfish Saurida tumbil 33014 Aq Brushtooth lizardfish Saurida undosquamis 33114 Aq Blackear lizardfish Synodus hoshinonis 33214 Aq Variegated lizardfish Synodus variegatus 33314 Aq Snakefish Trachinocephalus myops 33414 Aq Speckled sandperch Parapercis hexophtalma Dab ramly دب رملي 3351 SA Radial firefish Pterois radiata Dujaaja al bahar دجاج البحر 3361 SA Red lionfish Pterois volitans 33711 Er Sailfin tang Zebrasoma velifer 3383 Ye Shrimp scad Alepes djedaba Djebbada دجبدة 3391 SA White-spotted puffer Arothron hispidus Drimma دريما 3401 SA Immaculate puffer Arothron immaculatus 3411 SA Stellate puffer Arothron stellatus 3421 SA Spot-fin porcupinefish Diodon hystrix 34314 Aq Blacktip grouper Epinephelus fasciatus Daghma دغمة 34414 Aq Comet grouper Epinephelus morrhua 34514 Aq Oblique-banded grouper Epinephelus radiatus 34614 Aq Gilthead seabream Sparus aurata Danees دنس 34711 Er Talang queenfish Scomberoides commersonnianus Durab دورب 3482,11 Er,Ye Doublespotted queenfish Scomberoides lysan 34914 Aq Striped bonito Sarda orientalis Dirak ديرك 3501,2,5,10 Er,SA,Su,Ye Narrow-barred Spanish mackerel Scomberomorus commerson 3515 Su Indo-Pacific king mackerel Scomberomorus guttatus 3521 SA Axilspot hogfish Bodianus axillaris Deek ديك 3531 SA Checkerboard wrasse Halichoeres hortulanus 3541 SA Wrasses Thalassoma spp. 3559 SA Silver sillago Sillago sihama Rakad راكاد 3561,14 Aq,SA Twobar seabream Acanthopagrus bifasciatus Rabaag رباج 35714 Aq Cheilinus abudjubbe Rabadi ربادي 35814 Aq Broomtail wrasse Cheilinus lunulatus 35914 Aq Orangespine unicornfish Naso lituratus Rahu رحو 36014 Aq Bluespine unicornfish Naso unicornis 361

230

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID14 Aq Devil firefish Pterois miles Rana رنا 36214 Aq Radial firefish Pterois radiata 36314 Aq Shortfin turkeyfish Dendrochirus brachypterus Rani, Abu al-Laban رنى- ابو اللبن 36410 Er Flathead Platycephalidae Ruad رواد 3652 Ye Shrimps Penaeus spp. Rubean روبين 3661 SA Redmouth grouper Aethaloperca rogaa Ruga روجا 3679 SA Atlantic tripletail Lobotes surinamensis Rougaah روجاه 3681 SA Stingrays Dasyatis spp. Rugtia روجتيه 3691 SA Eagle and manta rays Mobula spp. 3701 SA Ribbontail stingray Taeniura lymma Rugtia saghirah روجتيه صغيرة 3711 SA Panther electric ray Torpedo panthera Rugtia kaharabiyyah روجتيه كهربائية 3721 SA Crocodile flathead Cociella crocodilus Rugud روجود 3731 SA Eagle and manta rays Manta spp. Rugia milla روجي ميله 37410 Er Flathead Platycephalidae Ro’ed رويد 3755,6,7,10 Er,Su Yellow-edged lyretail Variola louti Rishal ريشال 37614 Aq Common silver-biddy Gerres oyena Rishan ريشان 37714 Aq Yellowspotted trevally Carangoides fulvoguttatus Reem ريم 37814 Aq Orangespotted trevally Carangoides bajad Reema safra ريم سفره 3799 SA Serranidae Anthias spp. Zargh زرغ 3801,5,6 SA,Su Obtuse barracuda Sphyraena obtusata Zreighan زريغان 38111 Er Blacktip reef shark Carcharhinus melanopterus Zingi زنجى 38211 Er Sicklefin lemon shark Negaprion acutidens 38310 Er Barracudas Sphyraenidae Zuran زوران 38410 Er Barracudas Sphyraenidae Zuria زوريا 3851 SA Dussimier’s halfbeak Hyporhamphus dussumieri Zirgaan زيرجان 38611 Er Ringtail surgeonfish Acanthurus blochii Zizan زيزان 38711 Er Epaulette surgeonfish Acanthurus nigricauda 38811 Er Sohal surgeonfish Acanthurus sohal 38911 Er Yellowfin surgeonfish Acanthurus xanthopterus 39011 Er Sailfin tang Zebrasoma velifer 39111 Er Yellowtail tang Zebrasoma xanthurum 3922 Ye Kawakawa Euthynnus affinis Zainub زينب 3932 Ye Shrimps Penaeus spp. Zinga زينجا 39411 Er Skipjack tuna Katsuwonus pelamis Zeinub زينوب 3953 Ye Bigeye tuna Thunnus obesus 39610 Er Threadfin breams Nemipteridae Sare سار 39712 Eg Japanese threadfin bream Nemipterus japonicus 3981 SA Yellowtail blue snapper Paracaesio xanthura Sarra’ ساره 3991 SA Snappers Pristipomoides spp. 40014 Aq Yellowstripe goatfish Mulloidichthys flavolineatus Sabalan سبلان 40114 Aq Yellowfin goatfish Mulloidichthys vanicolensis 40214 Aq Cinnabar goatfish Parupeneus heptacanthus 40314 Aq Rosy goatfish Parupeneus rubescens 40414 Aq Goldband goatfish Upeneus moluccensis 40514 Aq Deep-water goatfish Upeneus subvitatus 40614 Aq Red Sea goatfish Parupeneus forsskali Sabalan abu nocta سبلان ابو نقطة 40714 Aq Long-barbel goatfish Parupeneus macronemus Sabalan ahmar سبلان احمر 40814 Aq Gold-saddle goatfish Parupeneus cyclostomus Sabalan asfar سبلان اصفر 40911 Er Streamlined spinefoot Siganus argenteus Sigan سجان 4106 Su Golden-lined spinefoot Siganus lineatus 4119,11,15 Er,SA,Su Marbled spinefoot Siganus rivulatus 4125 Su Rabitfishes Siganus sp. 41314 Aq Brown-spotted spinefoot Siganus stellatus 4141 SA Brown-spotted spinefoot Siganus stellatus Sigan al baha سجان الباحا 41514 Aq Marbled spinefoot Siganus rivulatus Sigan biady سجان بيادي 41610 Er Bigeyes or catalufas Priacanthidae Sahr سحر 41710 Er Bigeyes or catalufas Priacanthidae Sahr el Leil سحر الليل 4183 Ye Cobia Rachycentron spp. Sakhala سخاله 4193 Ye Herrings,shads,sardines,menhadens Clupeidae Sardin سردين 4205 Su Red-eye round herring Etrumeus teres 4215 Su Goldstripe sardinella Sardinella gibbosa 422

Local names - Tesfamichael and Saeed 231

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID5 Su Indian oil sardine Sardinella longiceps Sardin سردين 4231,5 SA,Su Blacktip sardinella Sardinella melanura 42414 Aq Shortfin scad Decapterus macrosoma Sardina سردينه 42514 Aq Bluestripe herring Herklotsichthys quadrimaculatus 42614 Aq Indian mackerel Rastrelliger kanagurta 42714 Aq Indian scad Decapterus russelli Sardina aredha سردينه عريضة 42814 Aq Arabian scad Trachurus indicus 42913 Eg Spotted sardinella Amblygaster sirm Sardina marboum سردينه مبروم 43014 Aq Red-eye round herring Etrumeus teres Sardina masreya سردينه مصرية 43113 Eg Mauritian sardinella Sardinella jussieu Sardina mofatar سردينه مفطر 4327 Su Jacks and pompanos Caranx spp. Safloh سفلوح 4335,6,7 Su Mangrove red snapper Lutjanus argentimaculatus Safin سفين 43413 Eg Indian mackerel Rastrelliger kanagurta Scombry سقمبري 43514 Aq Chub mackerel Scomber japonicus Scombla سكمبلا 4363 Ye Marine tutles Chelonioidea Sulhafa سلحافه 4371,3,5,6,7,11 Er,SA,Su,Ye Milkfish Chanos chanos Salmani سلماني 4389 SA Pacific ladyfish Elops affinis 43911 Er Brownspotted grouper Epinephelus chlorostigma Samman سمن 44014 Aq Sohal surgeonfish Acanthurus sohal Sahla سهله 44110 Er Bigeyes or catalufas Priacanthidae 44211 Er Painted sweetlips Diagramma pictum Sobaity سوبيتى 44310 Er Grunts Haemulidae 44411 Er Blackspotted rubberlip Plectorhinchus gaterinus 44511 Er Minstrel sweetlip Plectorhinchus schotaf 44610 Er Silver grunt Pomadasys argenteus 44711 Er Javelin grunter Pomadasys kaakan 4481 SA Sohal surgeonfish Acanthurus sohal Suhal سوهل 44911 Er Whitetip reef shark Triaenodon obesus Sweida سويدا 4505 Su Cuttlefishes Sepiidae Sebia سيبيا 4517 Su Areolate grouper Epinephelus areolatus Seetiati سيتياتي 45214 Aq Dusky spinefoot Siganus luridus Sigan harafi سيجان حرفي 45314 Aq Streamlined spinefoot Siganus argenteus Sigan khudhary سيجان خضاري 45410 Er Threadfin breams Nemipteridae Ser’a سيره 45514 Aq Common dolphinfish Coryphaena hippurus Saif سيف 45614 Aq Black snoek Thyrsitoides jordanus 45714 Aq Largehead hairtail Trichiurus lepturus 45810 Er Cobia Rachycentron canadum Sikla سيكلا 45910 Er Cobia Rachycentron canadum Sikin سيكين 4606 Su Dussimier’s halfbeak Hyporhamphus dussumieri Silinti سيلنتي 4615,7 Su Yellowspotted trevally Carangoides fulvoguttatus Seleikh سيليخ 4627 Su Jacks and pompanos Caranx spp. 4635 Su Halfbeaks Hemiramphus spp. Selenti سيلينتى 46410 Er Grunts Haemulidae Shatef شاتف 46510 Er Silver grunt Pomadasys argenteus 4665,6,7 Su Indian threadfish Alectis indicus Shawish شاويش 46714 Aq Scissortail sergeant Abudefduf sexfasciatus Shabbar شبار 46814 Aq Blackspot sergeant Abudefduf sordidus 46914 Aq Indo-Pacific sergeant Abudefduf vaigiensis 4705,6,7 Su Tenpounder Elops machnata Shagool شجول 4715 Su Spotback herring Herklotsichthys punctatus 4725 Su Bigeye snapper Lutjanus lutjanus Shukrum شخروم 47312 Eg Striped piggy Pomadasys stridens 4745,10 Er,Su Jarbua terapon Terapon jarbua 4759 SA Therapon Therapon spp. 4765,6,7 Su Indian scad Decapterus russelli Shadba شدبا 4771 SA Jacks and pompanos Decapterus spp. Shaduba شدوبا 47810 Er Spiny lobsters Palinuridae Sharkha شركا 47911 Er Scalloped spiny lobster Panulirus homarus 48010 Er Ornate spiny lobster Panulirus ornatus 48110 Er Pronghorn spiny lobster Panulirus penicillatus 48210 Er Painted spiny lobster Panulirus versicolor 483

232

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID10 Er Flathead lobster Thenus orientalis Sharkha شركا 4845,7 Su Doublespotted queenfish Scomberoides lysan Shrow شرو 4852,11 Er,Ye Kawakawa Euthynnus affinis Sherwa شروة 4862 Ye Mackerels,tunas,bonitos Scombridae Scherwa شروة 48714 Aq Red-toothed triggerfish Odonus niger Shuroma شرومة 4881 SA Frigate tuna Auxis thazard thazard Sherwi شروي 48911 Er Skipjack tuna Katsuwonus pelamis 49011 Er Torpdeo scad Megalaspis cordyla 49111 Er Longtail tuna Thunnus tonggol 4921 SA Moray eels Gymnothorax spp. Shaaga شعاجه 4931 SA Undulated moray Gymnothorax undulatus 4948,7 Su Mullets Mugil spp. Sha'aboi شعبوي 49510 Er Snappers Lutjanidae Shaefen شعفن 4961,11 Er,SA Mangrove red snapper Lutjanus argentimaculatus 49711 Er Blackspot snapper Lutjanus ehrenbergii 49811 Er Dory snapper Lutjanus fulviflamma 49911 Er Blubberlip snapper Lutjanus rivulatus 50011 Er Black and white snapper Macolor niger 5018,10 Er,Su Emperors or scavengers Lethrinidae Shu'ur شعور 5025,10 Er,Su Thumbprint emperor Lethrinus harak 5035,10 Er,Su Pink ear emperor Lethrinus lentjan 5045,10 Er,Su Sky emperor Lethrinus mahsena 50510 Er Smalltooth emperor Lethrinus microdon 5065,10,14 Aq,Er,Su Spangled emperor Lethrinus nebulosus 5075,7,9 SA,Su Emperors or scavengers Lethrinus spp. 50810 Er Spotted coralgrouper Plectropomus maculatus 5091 SA Emperors or scavengers Lethrinus spp. Shu'ur abu zahwa شعور ابو زهوه 5101 SA Humpnose big-eye bream Monotaxis grandoculis Shu'ur abu'ayn شعور ابو عين 5111 SA Emperors or scavengers Lethrinus spp. Shu'ur khirmiya شعور خرمية 5129 SA Trumpet emperor Lethrinus miniatus Shu'ur dibi شعور دبي 5131 SA Emperors or scavengers Lethrinus spp. Shu'ur deeb شعور ديب 5149 SA Spangled emperor Lethrinus nebulosus Shu'ur ramaka شعور رامكا 5151 SA Emperors or scavengers Lethrinus spp. 5161 SA Spangled emperor Lethrinus nebulosus Shu'ur mehseny شعور محيسنى 51714 Aq Albacore Thunnus alalunga Shak شك 51814 Aq Narrow-barred Spanish mackerel Scomberomorus commerson Shak abu Isnan شك ابو اسنان 51914 Aq Longtail tuna Thunnus tonggol Shak Abu thiel شك ابو ذيل 52014 Aq Dogtooth tuna Gymnosarda unicolor Shak abu ein شك ابو عين 52113 Eg Atlantic chub mackerel Scomber colias Shak al-zoor شك الزور 52214 Aq Yellowfin tuna Thunnus albacares Shak zoor شك زور 52314 Aq Cobia Rachycentron canadum Shakan شكان 5245,6,7 Su Painted sweetlips Diagramma pictum Shakfa شكفا 5252,11 Er,Ye Painted sweetlips Diagramma pictum Shutaf شوطاف 5269 SA Haemulidae Diagramma spp. 5271 SA Minstrel sweetlip Plectorhinchus schotaf 5287 Su Mullets Mugil spp. Shole شول 52911 Er Leopard flounder Bothus pantherinus Shebet al bahir شيبت البحر 53011 Er Largetooth flounder Pseudorhombus arsius 53110 Er Snappers Lutjanidae Sheik ali شيخ على 5329 SA Triggerfishes Balistes spp. Schiyram shiram شيرام شيرام 53314 Aq Coral hind Cephalopholis miniata Shirni شيرنى 53410 Er Grunts Haemulidae Shefsh شيفش 53510 Er Silver grunt Pomadasys argenteus 53610 Er Giant seacatfish Netuma thalassina Shilan شيلان 53714 Aq Areolate grouper Epinephelus areolatus Shelwa شيلوة 53815 Ye Yellowtail scad Atule mate Saibariya صعباريا 5393 Ye Whitefin trevally Carangoides equula Subaria صعباريا 54014 Aq Spotted guitarfish Rhinobatos punctifer Salfooh صلفوه 54114 Aq Yellow boxfish Ostracion cubicus Sanduk al-bahar صندوق البحر 54214 Aq Bluetail trunkfish Ostracion cyanurus 54314 Aq Humpback turretfish Tetrosomus gibbosus 544

Local names - Tesfamichael and Saeed 233

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID11 Er Pink ear emperor Lethrinus lentjan Suli صولي 54510 Er Smalltooth emperor Lethrinus microdon 54611 Er Spangled emperor Lethrinus nebulosus 54710 Er Flathead Platycephalidae Sumar صومر 5482 Ye Requiem sharks Carcharhinidae Dohoosh طاهوش 54914 Aq Leopard flounder Bothus pantherinus Tabaq طبق 55014 Aq Finless sole Pardachirus marmoratus 55114 Aq Black-tip sole Soleichthys heterorhinos 5525,6,7,11 Er,Su Greasy grouper Epinephelus tauvina Tauwina طوينا 5533 Ye Sea basses: groupers and fairy

bassletsSerranidae 554

3 Ye Stingrays Dasyatidae Taira طيرة 5555,6 Su Smallspotted dart Trachinotus baillonii Teiman طيمان 5561,5,6,7 SA,Su Subnose pompano Trachinotus blochii 55711 Er Orange-lined triggerfish Balistapus undulatus Ajame عجامة 55811 Er Titan triggerfish Balistoides viridescens 55911 Er Yellowmargin triggerfish Pseudobalistes flavimarginatus 56011 Er Yellow-spotted triggerfish Pseudobalistes fuscus 56111 Er Picasso triggerfish Rhinecanthus assasi 56211 Er Bluethroat triggerfish Sufflamen albicaudatum 5639 SA Guitarfishes Rhinobatos spp. Orab عراب 5649 SA Tetraodontidae Tetraodon spp. Arradh عراض 56514 Aq Fringelip mullet Crenimugil crenilabis Arabi عربي 5661,10 Er,SA Mullet Crenimugil spp. 5671,11 Er,SA Largescale mullet Liza macrolepis 56810 Er Squaretail mullet Liza vaigiensis 5691,10 Er,SA Flathead grey mullet Mugil cephalus 5705,7,8 Su Mullets Mugil spp. 57110,15 Er,Ye Mullets Mugilidae 57210 Er Hornlip mullet Oedalechilus labiosus 57310 Er Longarm mullet Valamugil cunnesius 5745,10 Er,Su Bluespot mullet Valamugil seheli 5751 SA Mullet Valamugil spp. 57614 Aq Leopard blenny Exallias brevis Arfaj عرفج 57714 Aq Rippled rockskipper Istiblennius edentulus 57811 Er Abudjubbe wrass Cheilinus abudjubbe Arousset el baher عروسة البحر 57911 Er Humphead wrasse Cheilinus undulatus 5805 Su Slimys,slipmouths,or ponyfishes Leiognathus spp. Arian عريان 5811 SA Goldlined seabream Rhabdosargus sarba Areedh عريض 58211 Er Abudjubbe wrass Cheilinus abudjubbe Esha mer'e عش ميري 58311 Er Humphead wrasse Cheilinus undulatus 5845,6,11 Er,Su Humpback red snapper Lutjanus gibbus Asmoot عصموت 5858 Su Snappers Lutjanus spp. 5861 SA Humpback red snapper Lutjanus gibbus Asmoodi عصمودي 5879 SA Mojarras Gerres spp. Afs عفس 58810 Er Slimys, slipmouths, or ponyfishes Leiognathidae Afsh عفش 5892 Ye Emperors or scavengers Lethrinidae 5902 Ye Spangled emperor Lethrinus nebulosus 5913 Ye Emperors or scavengers Lethrinus spp. 5924 Ye Porgies Sparidae 5933,5,9,10 Er,SA,Su,Ye Great barracuda Sphyraena barracuda Agam عقام 59410 Er Bigeye barracuda Sphyraena forsteri 5951,10 Er,SA Pickhandle barracuda Sphyraena jello 59611 Er Obtuse barracuda Sphyraena obtusata 5973 Ye Barracudas Sphyraena spp. 59810 Er Barracudas Sphyraenidae 59914 Aq Great barracuda Sphyraena barracuda Iqama عقامه 60014 Aq Sawtooth barracuda Sphyraena putnamiae 6011 SA Orangespine unicornfish Naso lituratus Akra abu garn عكرا ايبو جرم 60212 Eg Red Sea goatfish Parupeneus forsskali Inber baladi عنبر بلدي 60310 Er Small toothed jobfish Aphareus furca Anteg عنتق 60410 Er Snappers Lutjanidae 605

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID10 Er Flathead lobster Thenus orientalis Sharkha شركا 4845,7 Su Doublespotted queenfish Scomberoides lysan Shrow شرو 4852,11 Er,Ye Kawakawa Euthynnus affinis Sherwa شروة 4862 Ye Mackerels,tunas,bonitos Scombridae Scherwa شروة 48714 Aq Red-toothed triggerfish Odonus niger Shuroma شرومة 4881 SA Frigate tuna Auxis thazard thazard Sherwi شروي 48911 Er Skipjack tuna Katsuwonus pelamis 49011 Er Torpdeo scad Megalaspis cordyla 49111 Er Longtail tuna Thunnus tonggol 4921 SA Moray eels Gymnothorax spp. Shaaga شعاجه 4931 SA Undulated moray Gymnothorax undulatus 4948,7 Su Mullets Mugil spp. Sha'aboi شعبوي 49510 Er Snappers Lutjanidae Shaefen شعفن 4961,11 Er,SA Mangrove red snapper Lutjanus argentimaculatus 49711 Er Blackspot snapper Lutjanus ehrenbergii 49811 Er Dory snapper Lutjanus fulviflamma 49911 Er Blubberlip snapper Lutjanus rivulatus 50011 Er Black and white snapper Macolor niger 5018,10 Er,Su Emperors or scavengers Lethrinidae Shu'ur شعور 5025,10 Er,Su Thumbprint emperor Lethrinus harak 5035,10 Er,Su Pink ear emperor Lethrinus lentjan 5045,10 Er,Su Sky emperor Lethrinus mahsena 50510 Er Smalltooth emperor Lethrinus microdon 5065,10,14 Aq,Er,Su Spangled emperor Lethrinus nebulosus 5075,7,9 SA,Su Emperors or scavengers Lethrinus spp. 50810 Er Spotted coralgrouper Plectropomus maculatus 5091 SA Emperors or scavengers Lethrinus spp. Shu'ur abu zahwa شعور ابو زهوه 5101 SA Humpnose big-eye bream Monotaxis grandoculis Shu'ur abu'ayn شعور ابو عين 5111 SA Emperors or scavengers Lethrinus spp. Shu'ur khirmiya شعور خرمية 5129 SA Trumpet emperor Lethrinus miniatus Shu'ur dibi شعور دبي 5131 SA Emperors or scavengers Lethrinus spp. Shu'ur deeb شعور ديب 5149 SA Spangled emperor Lethrinus nebulosus Shu'ur ramaka شعور رامكا 5151 SA Emperors or scavengers Lethrinus spp. 5161 SA Spangled emperor Lethrinus nebulosus Shu'ur mehseny شعور محيسنى 51714 Aq Albacore Thunnus alalunga Shak شك 51814 Aq Narrow-barred Spanish mackerel Scomberomorus commerson Shak abu Isnan شك ابو اسنان 51914 Aq Longtail tuna Thunnus tonggol Shak Abu thiel شك ابو ذيل 52014 Aq Dogtooth tuna Gymnosarda unicolor Shak abu ein شك ابو عين 52113 Eg Atlantic chub mackerel Scomber colias Shak al-zoor شك الزور 52214 Aq Yellowfin tuna Thunnus albacares Shak zoor شك زور 52314 Aq Cobia Rachycentron canadum Shakan شكان 5245,6,7 Su Painted sweetlips Diagramma pictum Shakfa شكفا 5252,11 Er,Ye Painted sweetlips Diagramma pictum Shutaf شوطاف 5269 SA Haemulidae Diagramma spp. 5271 SA Minstrel sweetlip Plectorhinchus schotaf 5287 Su Mullets Mugil spp. Shole شول 52911 Er Leopard flounder Bothus pantherinus Shebet al bahir شيبت البحر 53011 Er Largetooth flounder Pseudorhombus arsius 53110 Er Snappers Lutjanidae Sheik ali شيخ على 5329 SA Triggerfishes Balistes spp. Schiyram shiram شيرام شيرام 53314 Aq Coral hind Cephalopholis miniata Shirni شيرنى 53410 Er Grunts Haemulidae Shefsh شيفش 53510 Er Silver grunt Pomadasys argenteus 53610 Er Giant seacatfish Netuma thalassina Shilan شيلان 53714 Aq Areolate grouper Epinephelus areolatus Shelwa شيلوة 53815 Ye Yellowtail scad Atule mate Saibariya صعباريا 5393 Ye Whitefin trevally Carangoides equula Subaria صعباريا 54014 Aq Spotted guitarfish Rhinobatos punctifer Salfooh صلفوه 54114 Aq Yellow boxfish Ostracion cubicus Sanduk al-bahar صندوق البحر 54214 Aq Bluetail trunkfish Ostracion cyanurus 54314 Aq Humpback turretfish Tetrosomus gibbosus 544

234Table A2 continued

Source Country Common name Scientific name Local name Arabic name ID10 Er Goldband jobfish Pristipomoides multidens Anteg عنتق 60615 Ye Smallscaled grouper Epinephelus polylepis Angar عنقر 60710 Er Requiem sharks Carcharhinidae Autat عوتات 60811 Er Blacktip shark Carcharhinus limbatus 60911 Er Blacktip reef shark Carcharhinus melanopterus 61011 Er Sandbar shark Carcharhinus plumbeus 61111 Er Sicklefin lemon shark Negaprion acutidens 61211 Er Milk shark Rhizoprionodon acutus 61311 Er Halavi ray Glaucostegus halavi O’ud عود 6145,6,7 Su Goldlined seabream Rhabdosargus sarba Eibad عيبد 61511 Er Spotted sardinella Amblygaster sirm Aida عيدة 6163 Ye Herrings,shads,sardines,menhadens Clupeidae 61711 Er Rainbow sardine Dussumieria acuta 61811 Er Shorthead anchovy Encrasicholina heteroloba 61911 Er Bluestripe herring Herklotsichthys quadrimaculatus 62011 Er Goldstripe sardinella Sardinella gibbosa 62111 Er Baelama anchovy Thryssa baelama 62214 Aq Purple-brown parrotfish Scarus fuscopurpureus Ghabban غابان 62314 Aq Viridescent parrotfish Calotomus viridescens 62414 Aq Bicolour parrotfish Cetoscarus bicolor 62514 Aq Daisy parrotfish Chlorurus sordidus 62614 Aq Rusty parrotfish Scarus ferrugineus 62714 Aq Sinai parrotfish Scarus genazonatus 62814 Aq Heavybeak parrotfish Scarus gibbus 62914 Aq Dusky parrotfish Scarus niger 63014 Aq Common parrotfish Scarus psittacus 63111 Er Red Sea halfbeak Hyporhamphus gamberur Far فار 63214 Aq Robust tuskfish Choerodon robustus Far al-Bahar فار البحر 63314 Aq Fivefinger wrasse Iniistius pentadactylus 63414 Aq Yellowpatch razorfish Xyrichtys melanopus 63514 Aq Peacock wrasse Xyrichtys pavo 63614 Aq Indo-Pacific sailfish Istiophorus platypterus Faras فارس 63712 Eg Red filament threadfin bream Nemipterus marginatus 6381 SA Black marlin Istiompax indica Faras al Bahr فارس البحر 6391,5,6 SA,Su Indo-Pacific sailfish Istiophorus platypterus 6401 SA Blue marlin Makaira nigricans 6411 SA Swordfish Xiphias gladius 6425,7 Su Snappers Aprion spp. Farsi فارسي 6436 Su Green jobfish Aprion virescens 6448 Su Snappers Lutjanidae 6451 SA Pipefishes and seahorses Hippocampus spp. Fara al bahr فاره البحر 6467 Su Mullets Mugil spp. Fasekh فاسخ 64710 Er Porgies Sparidae Fafal فافل 6485,7 Su Titan triggerfish Balistoides viridescens Faki sharam فاكي شرام 64914 Aq Ring-tailed cardinalfish Apogon aureus Fanas فانس 65014 Aq Twobelt cardinal Apogon bifasciatus 65114 Aq Yellowstriped cardinalfish Apogon cyanosoma 65214 Aq Narrowstripe cardinalfish Apogon exostigma 65314 Aq Iridescent cardinalfish Apogon kallopterus 65414 Aq Blackstripe cardinalfish Apogon nigrofasciatus 65514 Aq Cheilodipterus lachneri 65614 Aq Large toothed cardinalfish Cheilodipterus macrodon 65714 Aq Indian Ocean twospot cardinalfish Cheilodipterus novemstriatus 65814 Aq Pinecone soldierfish Myripristis murdjan 65914 Aq Eightspine cardinalfish Neamia octospina 66014 Aq Vanikoro sweeper Pempheris vanicolensis 66114 Aq Crown squirrelfish Sargocentron diadema 66214 Aq Arabian monocle bream Scolopsis ghanam Fanas abiadh فانس ابيض 6635,6,7 Su Painted sweetlips Diagramma pictum Fataleeta فتاليتا 66414 Aq Kawakawa Euthynnus affinis Fatla فتلة 66510 Er Cobia Rachycentron canadum 666

Local names - Tesfamichael and Saeed 235Table A2 continued

Source Country Common name Scientific name Local name Arabic name ID14 Aq Skipjack tuna Katsuwonus pelamis Fatleh فتله 66714 Aq Sailfin flyingfish Parexocoetus brachypterus Farash فراش 6681 SA Snappers Pristipomoides spp. Fars فرس 66914 Aq Blueskin seabream Polysteganus coeruleopunctatus Fareedin فريدين 67011 Er Coral hind Cephalopholis miniata Ferek فريق 6715,7 Su Anchovies Anchoviella spp. Fagima فقيمة 6725 Su Anchovies Stolephorus spp. 6733 Ye Cuttlefishes Sepia spp. Fakhd فكهد 6742 Ye Giant guitarfish Rhynchobatus djiddensis Fakhadoo فكهدو 67514 Aq Moontail bullseye Priacanthus hamrur Fanas abu-ein فناس ابو عين 6762 Ye Stingrays Dasyatidae Fahodoo فهودو 6775 Su Twobar seabream Acanthopagrus bifasciatus Fogil فوجيل 6785,7,10 Er,Su King soldierbream Argyrops spinifer Fofal فوفل 67910 Er Cobia Rachycentron canadum Fitle فيتل 6801 SA Indian anchovy Stolephorus indicus Figayma فيجيمة 6812 Ye Billfishes Istiophoridae Feraz فيرز 68214 Aq Snubnose emperor Lethrinus borbonicus Qeda قدة 68314 Aq Sky emperor Lethrinus mahsena 68414 Aq Sandbar shark Carcharhinus plumbeus Gursh قرش 6851 SA Great white shark Carcharodon carcharias 68614 Aq Tiger shark Galeocerdo cuvieri 68714 Aq Arabian smooth-hound Mustelus mosis 6881 SA Blue shark Prionace glauca 68914 Aq Scalloped hammerhead Sphyrna lewini Gursh abu burnetta قرش ابو برنيطة 6901 SA Guitarfishes Rhinobatos spp. Gursh abu halawa قرش ابو حلاوة 6911 SA Sawfishes Pristis spp. Gursh abu minshaar قرش ابو منشار 6921 SA Grey reef shark Carcharhinus amblyrhynchos Gursh al baba قرش البابا 6931 SA Blacktip shark Carcharhinus limbatus Gursh al sahl قرش السهل 6941 SA Whale shark Rhincodon typus Gursh bitaan قرش بيتان 6951 SA Thintail thresher Alopias vulpinus Gursh husseni قرش حصينى 6961 SA Mackerel sharks or white shark Isurus spp. Gursh deeba قرش ديبا 6971 SA Smooth hammerhead Sphyrna zygaena Gursh gurna قرش قرنا 6981 SA Tawny nurse shark Nebrius ferrugineus Gursh massassa قرش مصاصا 6991 SA Tiger shark Galeocerdo cuvier Gursh nimrany قرش نمراني 7005 Su Giant seacatfish Netuma thalassina Garmout قرموط 70111 Er Scalloped hammerhead Sphyrna lewini Gurna قرن 70211 Er Spotted unicornfish Naso brevirostris Kurnjal قرنجل 70311 Er Bluespine unicornfish Naso unicornis 7045,8,9 SA,Su Requiem sharks Carcharhinidae Girish قريش 7059 SA Mojarras Gerres spp. Gash قش 7063 Ye Emperors or scavengers Lethrinus spp. 7076 Su Honeycomb grouper Epinephelus merra Ghoshar قشار 7082 Ye Painted sweetlips Diagramma pictum Caterin قطرين 70914 Aq Blackspotted rubberlip Plectorhinchus gaterinus Qatran, staff قطرين, ستاف 71014 Aq Blue-lined large-eye bream Gymnocranius grandoculis Qamar قمر 71114 Aq Humpnose big-eye bream Monotaxis grandoculis Qamar Abu ein قمر ابو عين 7129 SA Remoras Echeneis spp. Kamlet al darfil قملة الدرفيل 71314 Aq Live sharksucker Echeneis naucrates Qamlet alqersh قملة القرش 71414 Aq Shark sucker Remora remora 71514 Aq Whitespotted moray Gymnothorax johnsoni Qmum قموم 71614 Aq Starry moray Gymnothorax nudivomer 71714 Aq Snowflake moray Echidna nebulosa Qmum muraqata قموم مرقطة 7185,7 Su Jacks and pompanos Caranx spp. Goutar قوتر 71911 Er Red Sea halfbeak Hyporhamphus gamberur Korom قورم 7207 Su Mullets Mugil spp. Ka’oi كاوي 7215 Su Flower crab Portunus pelagicus Kaboriah كبوريا 7227 Su Black and white snapper Macolor niger Kut كت 7235,7 Su Redmouth grouper Aethaloperca rogaa Katarban كتربان 72410 Er Indian spiny turbot Psettodes erumei Kutian كتيان 7257 Su Areolate grouper Epinephelus areolatus Kodad كداد 72611 Er Striated fusilier Caesio striata Kourab el bahr كراب البحر 727

236Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID11 Er Suez fusilier Caesio suevica Kourab el bahr كراب البحر 7285,7 Su Jacks and pompanos Caranx spp. Karb كرب 72910 Er Redmouth grouper Aethaloperca rogaa Karban كربان 7301,6,7,11 Er,SA,Su Common silver-biddy Gerres oyena Kass كس 73114 Aq Bluespotted cornetfish Fistularia commersonii Qasaba كسبا 7325 Su Black and white snapper Macolor niger Kust كست 7332 Ye Slimys,slipmouths,or ponyfishes Leiognathidae Kash كش 73411 Er Redmouth grouper Aethaloperca rogaa Kushar كشر 7351 SA Coral hind Cephalopholis miniata 7368 Su Sea basses: groupers and fairy basslets Epinephelus spp. 73711 Er Blacktip grouper Epinephelus fasciatus 73811 Er Brown-marbled grouper Epinephelus fuscoguttatus 73911 Er Camouflage grouper Epinephelus polyphekadion 7409,10 Er,SA Sea basses: groupers and fairy basslets Epinephelus spp. 7412,11 Er,Ye Greasy grouper Epinephelus tauvina 74211 Er Spotted coralgrouper Plectropomus maculatus 7432,10 Er,Ye Sea basses: groupers and fairy basslets Serranidae 7441,11 Er,SA Peacock hind Cephalopholis argus Kushar abu blaha كشر ابو بلحة 7459 SA Coral hind Cephalopholis miniata Kushar abu adas كشر ابو عداس 7461 SA Sea basses: groupers and fairy basslets Grammistes spp. 7471 SA Comet grouper Epinephelus morrhua Kushar abu lulu كشر ابو لولو 7481,12 Eg,SA Greasy grouper Epinephelus tauvina Kushar tauwina كشر توينه 7499 SA Giant grouper Epinephelus lanceolatus Kushar twini كشر طويني 7509,10 Er,SA Malabar grouper Epinephelus malabaricus 7511,11 Er,SA Summan grouper Epinephelus summana Kushar mubal’at كشر موبالات 7529,11 Er,SA Areolate grouper Epinephelus areolatus Kushar nagel كشر ناجل 7535 Su Squids Loliginidae Kalamari كلاماري 7542 Ye Indian spiny turbot Psettodes erumei Kelb كلب 7551 SA Cobia Rachycentron canadum Kuml nu’aakhr كمل نواخر 7565,7 Su Orbicular batfish Platax orbicularis Kanaf كناف 7571 SA Dusky batfish Platax pinnatus 75810 Er Triggerfishes Balistes spp. Canzir كنزير 75914 Aq Redcoat Sargocentron rubrum Keha كهة 7600 Su Scribbled leatherjacket filefish Aluterus scriptus Kotub كوتب 7615,7 Su Crimson jobfish Pristipomoides filamentosus Koreib كوريب 76210 Er Grunts Haemulidae Koko كوكو 7635,10 Er,Su Silver grunt Pomadasys argenteus 7645 Su Smallspotted grunter Pomadasys commersonnii 76510 Er Trochus shell Trochidae Kokian كوكيان 7661,5,6,7 SA,Su Hound needlefish Tylosurus crocodilus crocodilus Kombir كومبير 76711 Er Giant seacatfish Netuma thalassina Kumal كومل 7682 Ye Blacktip catfish Plicofollis dussumieri 7691 SA Sea catfishes Tachysurus spp. 7705,7 Su Black surgeonfish Acanthurus gahhm Kohom كوهم 77111 Er Scalloped spiny lobster Panulirus homarus Langus لانجس 77211 Er Ornate spiny lobster Panulirus ornatus 77311 Er Painted spiny lobster Panulirus versicolor 77411 Er Flathead lobster Thenus orientalis 7757 Su Jacks and pompanos Caranx spp. Lamenab لايمناب 7765 Su Drums or croakers Otolithes spp. Lut لت 7772 Ye Requiem sharks Carcharhinidae Lokhem لخام 7781,2 SA,Ye Doublespotted queenfish Scomberoides lysan Lysan لسان 7797 Su Two-spot red snapper Lutjanus bohar Lolab لو لاب 7801,5,6,7,10 Er,SA,Su Yellow-edged lyretail Variola louti Louti لوطى 7817 Su Humphead wrasse Cheilinus undulatus Limalima ليما ليما 78214 Aq Double-ended pipefish Trachyrhamphus bicoarctatus Masas ماساس 7831,5,6,7,10 Er,SA,Su Kawakawa Euthynnus affinis Ma’agab ماعجب 7841 SA Skipjack tuna Katsuwonus pelamis 78511 Er Sky emperor Lethrinus mahsena Mahsena محسنه 78611 Er Dorab wolf-herring Chirocentrus dorab Mekhlef مخلف 7877,12 Eg,Su King soldierbream Argyrops spinifer Morjan مرجان 788

Local names - Tesfamichael and Saeed 237

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID2 Ye Humphead snapper Lutjanus sanguineus Morjan مرجان 7899 SA Japanese threadfin bream Nemipterus japonicus 7909 SA Threadfin breams Nemipterus spp. 79110 Er Puffers Tetraodontidae 79214 Aq Network pipefish Corythoichthys flavofasciatus Masas ramli مساس رملي 79314 Aq Schultz’s pipefish Corythoichthys schultzi 7941,11 Er,SA Rainbow runner Elagatis bipinnulata Muslabah مسلابه 79514 Aq Pomfret Ariomma brevimanus Maslimani مسلمانى 79614 Aq Yellow-ear angelfish Apolemichthys xanthotis Moscht مشط 79714 Aq Dusky angelfish Centropyge multispinus 79814 Aq Threadfin butterflyfish Chaetodon auriga 79914 Aq Blacktail butterflyfish Chaetodon austriacus 80014 Aq Diagonal butterflyfish Chaetodon fasciatus 80114 Aq Blackback butterflyfish Chaetodon melannotus 80214 Aq Eritrean butterflyfish Chaetodon paucifasciatus 80314 Aq Bluecheek butterflyfish Chaetodon semilarvatus 80414 Aq Chevron butterflyfish Chaetodon trifascialis 80514 Aq Zebra angelfish Genicanthus caudovittatus 80614 Aq Emperor angelfish Pomacanthus imperator 80714 Aq Yellowbar angelfish Pomacanthus maculosus 80814 Aq Regal angelfish Pygoplites diacanthus 80911 Er Strongspine silver-biddy Gerres longirostris Mukeresh مكارش 81010 Er Barracudas Sphyraenidae Mekazel مكازل 81111 Er Gracile lizardfish Saurida gracilis Macarona مكرونا 8125,9,11 Er,SA,Su Greater lizardfish Saurida tumbil 8135,11 Er,Su Brushtooth lizardfish Saurida undosquamis 81410 Er Lizardfishes Synodontidae 81514 Aq Yellowtail barracuda Sphyraena flavicauda Malleeta مليتة 81615 Ye Common silver-biddy Gerres oyena Mehara مهارا 81713 Eg Smooth-belly sardinella Amblygaster leiogaster Moza موزة 81810 Er Indian spiny turbot Psettodes erumei Muse موس 81910 Er Indian spiny turbot Psettodes erumei Mousa موسى 82014 Aq Yellowfin hind Cephalopholis hemistiktos Mumen مومان 82114 Aq Bluespotted wrasse Anampses caeruleopunctatus Muesy ميسي 82214 Aq Lined wrasse Anampses lineatus 82314 Aq Spotted wrasse Anampses meleagrides 82414 Aq Yellowbreasted wrasse Anampses twistii 82514 Aq Lyretail hogfish Bodianus anthioides 82614 Aq Mental wrasse Cheilinus mentalis 82714 Aq Spottail coris Coris caudimacula 82814 Aq Dapple coris Coris variegata 82914 Aq Green birdmouth wrasse Gomphosus caeruleus 83014 Aq Checkerboard wrasse Halichoeres hortulanus 83114 Aq Zigzag wrasse Halichoeres scapularis 83214 Aq Klunzinger’s wrasse Thalassoma klunzingeri 83314 Aq Moon wrasse Thalassoma lunare 8341 SA Molas or Ocean Sunfishes Mola spp. Milla ميله 8351,5,7,10 Er,SA,Su Spotted coralgrouper Plectropomus maculatus Najil ناجل 83614 Aq Roving coralgrouper Plectropomus pessuliferus 8378 Su Sea basses: groupers and fairy

bassletsPlectropomus spp. 838

2 Ye Grunts Haemulidae Nakem ناكم 8391 SA Smallspotted grunter Pomadasys commersonnii 8403 Ye Grunter Pomadasys spp. 84111 Er Tiger shark Galeocerdo cuvier Nebrawi نبراوي 8421,9 SA King soldierbream Argyrops spinifer Najar نجار 84314 Aq King soldier bream Argyrops spinifer 8441 SA Jacks and pompanos Seriola spp. Nazkha نزخة 8453 Ye Dorab wolf-herring Chirocentrus dorab Nakanaf نكاناف 8463 Ye Tiger shark Galeocerdo cuvier Numrani نمراني 8479 SA Threadfin breams Nemipterus spp. Nofrah نوفره 84814 Aq Red Sea seabream Diplodus noct Noct نوكت 849

238

Table A2 continuedSource Country Common name Scientific name Local name Arabic name ID2 Ye Humphead snapper Lutjanus sanguineus Nirjan نيرجان 85010 Er Snappers Lutjanidae Naisarah نيصاره 8515,7 Su Yellowtail scad Atule mate Haboot هابوت 8527 Su Jacks and pompanos Caranx spp. 8535,6,7 Su Dory snapper Lutjanus fulviflamma Habair هبير 85414 Aq Starry triggerfish Abalistes stellatus Hijma هجمه 85514 Aq Yellow-spotted triggerfish Pseudobalistes fuscus 85611 Er Honeycomb stingray Himantura uarnak Halali هلالى 85711 Er Ribbontail stingray Taeniura lymma 85811 Er Flower crab Portunus pelagicus Hinkakre هنكاكار 85911 Er Giant mud crab Scylla serrata 86014 Aq Jarbua terapon Therapon jarbua Henw هنو 8619 SA Dory snapper Lutjanus fulviflamma Hobara هوبارا 8629 SA Snappers Lutjanus spp. 8634 Ye Cutlassfishes Trichiurus spp. Homalan هوملان 86414 Aq Greater amberjack Seriola dumerili Hea هيا 86511 Er Humpback red snapper Lutjanus gibbus Himbuk هيمبوك 86611 Er Emperor red snapper Lutjanus sebae 8675,7 Su Karenteen seabream Crenidens crenidens Hindook هيندوك 8682 Ye Herrings,shads,sardines,menhadens Clupeidae Wasif وزف 86911 Er Shorthead anchovy Encrasicholina heteroloba 870

Appendix - Tesfamichael 239

appendix - reConstruCting the fishing effort of red sea fisheries, 1950-20101

Dawit Tesfamichaela,b

aSea Around Us, Fisheries Centre, University of British Columbia,2202 Main Mall, Vancouver, BC, V6T 1Z4, Canada

bDepartment of Marine Sciences, University of Asmara, Asmara, Eritread.tesfamichael @fisheries.ubc.ca

Fishing effort is any activity or device deployed to catch fish, and which can be quantified. Thus, the number of nets of a certain type deployed in a set period is a measure of effort, as is the amount of fuel used by a fishing fleet. Another measure of fishing effort is the cumulative engine power of the engine deployed in fisheries that are motorized. Fishing effort is an important requirement for fishery stock assessment; however, it is not usually readily available; indeed, its availability is usually worse than that of catch data. The Red Sea fisheries are divided into two major sectors: industrial and artisanal. The industrial fishery has generally better records than the non-industrial, i.e., artisanal and subsistence fisheries. The effort data for the industrial fishery (trawl and purse seine) of the Red Sea was obtained from the database of the Sea Around Us (Anticamara et al. 2011). This consisted of total effort by gear from 1950 to 2006 for whole Red Sea, but without disaggregation by the countries bordering the Red Sea. Thus only the total by gear for the whole Red Sea is presented in the result below. These data were extended from 2007 to 2010 by assuming the annual rate of change in effort to be the average annual change from 2000 to 2006 for purse seiners and from 2000 to 2005 for trawlers. (Note that the trawler data for 2006 jumped by order of magnitude from the previous years; thus, to keep our rate of change on the conservative side, the 2006 data were omitted).

The artisanal and subsistence fisheries do not have an effort recording system and thus the time series of effort for the Red Sea fisheries was derived mainly on the basis of demographic information (i.e., number of fishers), or boat counts. Table (1) lists the references from which the effort data were obtained for each country. For Yemen, the available data were total number of boats; Egypt has a database from which the effort data was reconstructed and for Eritrea, there were two different data types to perform the analysis for two periods, before and after 1991, when Eritrea became an independent country. Jordan and Israel have very small fishing operation in the Red Sea, hence their effort estimation is not included here.

Except for Egypt and Eritrea after 1991, the effort reconstruction procedure was the same. First, an exponential function was fitted to the available effort, which was then used to predict effort for years it was missing. The exponential function fitted had the form y = a * eb; where a and b are parameters to be estimated, and presented in Table (2) for each country.1 Cite as: Tesfamichael, D. (2012) Reconstructing the fishing effort of Red Sea fisheries, 1950-2010. pp. 239-244. In: Tesfamichael, D. and Pauly, D. (eds.) Catch reconstruction for the Red Sea large marine ecosysytem by countries (1950-2010). Fisheries Centre Research Reports 20(1). Fisheries Centre, University of British Columbia [ISSN 1198-6727].

Table 1. Sources used for the reconstruction of effort of the Red Sea fisheries.Effort data Motorization data

Country Year Data* Source Year % SourceSudan 1955 200 Kristjonsson (1956) 1956 1.93 Kristjonsson (1956)

1976 418 ODA (1983) 1979 22.57 Barrania (1979)1979 437 Barrania (1979) 1982 61.98 Chakraborty (1983)1981 664 ODA (1983) 2006 95.00 FA (2007)1982 605 Chakraborty (1983)2001 743 FA (2007)2006 967 FA (2007)

Eritrea 1964 3543 Grofit (1971) 1960 1.00 Grofit (1971)1968 4167 Grofit (1971) 1963 2.20 Grofit (1971)1969 3022 Grofit (1971 1964 3.72 Grofit (19711970 3000 Giudicelli (1984) 1969 42.10 Grofit (19711981 875 Giudicelli (1984) 1974 75.00 Giudicelli (1984)1984 250 Giudicelli (1984)

Yeman 1972 1000 Agger (1976) 1972 10.00 Agger (1976)1975 1066 Walczak (1977) 1975 26.45 Walczak (1977)1976 1071 Campleman (1977) 1978 60.66 Campleman (1977)1978 1597 Campleman (1977) 2006 96.00 MoFW (2010)1992 1771 Herrera and Lepere (2005)1997 2686 Brodie et al., (1999)1998 3390 FAO (2002)2000 1781 MoFW (2010)2001 2254 MoFW (2010)2002 2562 MoFW (2010)2003 2737 MoFW (2010)2004 4510 MoFW (2010)2005 5000 MoFW (2010)2006 5727 MoFW (2010)

Saudi Arabia

1954 2500 Neve and Al-Aiidy (1973) 1955 0.20 Ferrer (1958)1971 3250 Neve and Al-Aiidy (1973) 1965 30.77 Neve and Al-Aiidy (1973)1980 3678 Barrania et al., (1980) 1969 41.43 Neve and Al-Aiidy (1973)1984 2408 Kedidi et al., (1984) 1991 97.00 Sakurai (1998)1991 2993 MAW (2008)1992 3443 MAW (2008)1993 3907 MAW (2008)1994 4063 MAW (2008)1995 4316 MAW (2008)1996 4212 MAW (2008)1997 4145 MAW (2008)1998 4209 MAW (2008)1999 4764 MAW (2008)2000 5037 MAW (2008)2001 6116 MAW (2008)2002 6389 MAW (2008)2003 6927 MAW (2008)2004 7266 MAW (2008)2005 6880 MAW (2008)2006 7533 MAW (2008)

* All effort data are number of fishers except for Yemen, which is number of boats.

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Motorization of the fishing vessels affects how effort is calculated significantly, and thus the process was considered explicitly. The rate at which motorization took place in the Red Sea countries was fitted to the logistic curve equation:

y = 1

1 + e (ln a - bx)

where ln a and b are parameters to be estimated, and whose values are presented in Table (2) for each country

Using the logistic curve fitting results, the total effort was divided into motorized and non-motorized. For the non-motorized effort, number of fishers were converted to horsepower (hp) assuming that the muscle power extend by a healthy man corresponds to 0.18 hp (Dalzell et al. 1987). For Egypt, Sudan, Eritrea and Saudi Arabia, the total effort was given in number of fishers. The total number of boats in the non-motorized category for Yemen was converted to total number of fishers by the average number of fishers per boat (n = 5).

For the motorized part of the fishery, the horsepower equivalent for each fisher in the motorized boats was first calculated for at least two years in the time series. A minimum of two points are needed to account for the change in the power of the engines installed in the boats over time. Using those points, a time series of hp/fisher was established, which was used to calculate the total hp by multiplying its values for specific years by the total number of fishers. For Yemen, since the total boats were given instead of total number of fishers, a time series of hp/boat was calculated as a multiplier of the total number of boats. Then the cumulative hp from the non-motorized and that of the motorized effort were added to get the overall total hp for each country.With regard to Egypt, the fisheries included in the analysis are referred by the Egyptian authorities as ‘semi-industrial’ (or launch) and ‘traditional’ fisheries, which are referred here as artisanal and subsistence fisheries, respectively. For the artisanal fishery, effort, expressed as total number of trips, was available from 1980 – 2006 (GAFRD 2010) for the main landing site of Suez. First, the number of trips was converted to hp using the average hp/trip calculated from data given in Sanders et al., (1984). A linear function (a = 1.34*104, b = 2.58*107), was then fitted and used to estimate the effort from 1950 to 2010. The effort from Suez was scaled up to the whole Red Sea using the Suez effort ratio in the whole Red Sea, which was calculated to be 47.7 % (Sanders et al. 1984). For the subsistence fishery, only one data point for 1983 was available (Chakraborty et al. 1983; Chakraborty 1984) and population numbers (all population data used in this report are based on UN population data available at esa.un.org/unpd/wpp/Excel-Data/population.htm) were used as a proxy to calculate effort from 1950 to 2010. Once the total effort for the non-industrial fishery of Egypt was calculated, it was further divided into gears. Handline and gillnet are the dominant gears and were allocated 63% and 27%, respectively based on information from fisheries experts in Egypt.

The effort data for Eritrea after 1991 was calculated using data available from the Ministry of Fishery (MOF 2007), which divides it by gear and boat type from 1996 – 2006. The effort data for 2005 and 2006 were unreasonably low compared to the previous years (so much that the catch per unit of effort for 2005 and 2006 were more than 40 times the previous years, although no major changes occurred during that time). Thus, we did not use the effort data for 2005 and 2006. Instead the average catch/effort from 1996 to 2004 were used to calculate the effort from 2005 to 2010. For 1992 – 1995, interpolation was used to fill the gap.

Subsequently, all efforts were re-expressed in kilowatt-hours. Thus, it was assumed that boats operate 2/3 (243 days) of the year, while for the rest of the year, they are docked for maintenance and/or the fishers are selling their catch or performing other land-based activities. Based on interviews with fishers, an average of 10 hours/day was used to calculate hp∙hours from hp∙days. Horsepower was converted to watts using the conversion ratio of 1 hp = 745.7 watt.

All the major gear used by artisanal and subsistence fishers are included in this analysis, but there are minor gears which are not. Thus, only 90% of the total effort calculated was used in dividing the total effort to the major gears. The remaining 10% were allocated to the minor gears labeled as ‘others’. Three major gears, which reflect the ecosystem and behaviour of the fish were identified, namely, beach seine for small pelagic, gillnet for large pelagic, and handlining for coral reef-associated fishes. These are not exhaustive gears, but representative and major ones in each habitat. This is helpful for ecosystem based management. The final stage of the effort reconstruction is dividing total effort into gears. This was done using effort information from the sources presented in Table (1). For Sudan,

Table 2. Parameters of exponential and logistic fitting of effort reconstruction.Exponential fitting Logistic fitting

a b R2 ln a b R2

Sudan 1.00E-22 0.0287 0.89 281.50 0.1419 0.97Eritrea* 5.00E+106 -0.1210 0.92 861.09 0.4369 0.98Yemen 4.00E-32 0.0400 0.78 277.36 0.1399 0.89Saudi Arabia 9.00E-16 0.0220 0.64 487.04 0.2467 0.88* only until 1991.

Appendix - Tesfamichael 241

90% of the effort was allocated to handlining, because it is pretty much the only gear used by the artisanal and subsistence fishers, and the 10% was allocated to ‘others’. For Yemen, the effort for the least important of the major fisheries, beach seine, was first dealt with, by allocating it 10% of the effort in 1950. The effort for the rest of the time was estimated using population size as a proxy and the 1950 data. This is reasonable because beach seine is carried out by people in their localities mainly for their own consumption; it is the least commercialized fishery. So, I assumed, as the population grows, more and more people are involved in the fishery. The remaining effort was divided 70% for gillnet and 30% for handline. Yemen has a dominant gillnet fishery whereas the other countries are dominated by handlining. For Saudi Arabia, the effort was divided 70% handlining and 30% gillnet. For Eritrea, the composition changed over time from beach seine being dominant in the early years to handlining being dominant in the later years (Figure 1). The total non-industrial effort for each country is given in Table (3). The total effort for the whole Red Sea by gear type was calculated by adding total efforts of the same gear from all the Red Sea countries (Table 4).

aCknowledgements

I thank Dr. R. Watson for the data in Table 1 and the Sea Around Us, a scientific collaboration between the University of British Columbia and The Pew Charitable Trust.

Figure 1. Ratios of beach seine (full line), handlining (broken line) and gillnet (line with circles) fisheries in the Eritrean artisanal and subsistence fisheries effort allocation from 1950 to 1991.

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Table 3. Non-industrial fisheries effort (mega-watt hours) of the Red Sea countries, 1950-2010Year Yemen Saudi Arabia Egypt Sudan Eritrea

1950 683 576 6,924 66 4,1811951 717 589 7,092 68 4,1811952 753 602 7,265 70 4,1811953 791 615 7,442 72 4,1811954 833 628 7,624 74 4,1811955 878 668 7,810 76 4,1811956 927 689 8,000 85 4,1811957 981 714 8,193 89 3,7061958 1,039 741 8,390 92 3,2841959 1,104 773 8,591 97 2,9101960 1,175 810 8,794 101 2,5791961 1,254 854 8,999 106 2,2861962 1,342 906 9,207 112 2,0261963 1,440 969 9,417 117 1,9091964 1,549 1,044 9,628 124 1,8971965 1,672 1,136 9,841 131 2,0231966 1,810 1,246 10,055 140 2,3251967 1,965 1,379 10,271 149 2,8441968 2,140 1,537 10,486 159 3,6031969 2,337 1,725 10,700 170 4,5871970 2,559 1,944 10,911 183 5,7241971 2,809 2,403 11,120 197 6,8871972 3,090 4,110 11,326 213 7,9261973 3,405 6,365 11,532 231 8,7221974 3,757 9,218 11,739 251 9,2201975 4,150 12,694 11,949 273 9,4271976 4,586 16,786 12,164 297 9,3921977 6,755 21,462 12,382 323 9,1761978 9,454 26,666 12,604 585 8,8371979 12,762 32,331 12,830 831 8,4191980 16,754 38,387 13,061 1,130 7,9581981 21,508 44,773 13,297 1,487 7,4761982 27,100 51,435 13,537 1,907 6,9921983 33,598 58,334 13,781 2,396 6,5141984 41,070 65,444 14,031 2,957 6,0511985 49,572 72,749 14,285 3,595 5,6061986 59,157 80,243 14,545 4,311 5,1831987 69,868 87,929 14,810 5,108 4,7831988 81,744 95,814 15,075 5,987 4,4061989 94,817 103,907 15,335 6,947 4,0531990 109,114 112,223 15,586 7,989 3,7231991 124,662 120,775 15,826 9,111 3,4151992 141,486 129,578 16,058 10,312 4,8411993 159,610 138,648 16,283 11,592 6,2671994 179,062 148,001 16,507 12,949 7,6921995 199,875 157,650 16,732 14,381 9,1181996 222,082 167,613 16,960 15,889 10,5441997 245,727 177,902 17,190 17,471 17,7571998 270,855 188,534 17,422 19,129 19,4231999 297,522 199,521 17,658 20,861 26,5662000 325,786 210,879 17,897 22,669 31,5432001 355,718 222,621 18,139 24,555 23,7632002 387,390 234,762 18,386 26,519 27,5602003 420,886 247,316 18,637 28,564 10,1112004 456,294 260,296 18,892 30,693 19,6692005 493,712 273,717 19,151 32,908 11,0112006 533,242 287,594 19,413 35,212 12,5962007 574,995 301,940 19,678 37,609 14,4312008 619,091 316,772 19,947 40,102 16,9852009 665,654 332,104 20,218 42,696 19,6252010 714,817 347,951 20,492 45,394 17,899

Appendix - Tesfamichael 243

Table 4. Effort (mega-watt hours) of Red Sea fisheries by gear, 1950-2010.Year Gillnet Handlining Trawl Beach Seine Purse seine Others1950 2,412 5,515 1,685 3,260 122 1,243 1951 2,482 5,639 2,010 3,261 153 1,265 1952 2,554 5,768 2,396 3,262 152 1,287 1953 2,629 5,900 2,487 3,262 153 1,310 1954 2,707 6,035 2,634 3,264 190 1,334 1955 2,796 6,191 2,753 3,265 185 1,361 1956 2,883 6,345 2,843 3,266 185 1,388 1957 2,975 6,436 2,625 2,903 201 1,368 1958 3,071 6,539 2,772 2,582 208 1,355 1959 3,173 6,656 2,677 2,298 238 1,347 1960 3,282 6,785 1,542 2,046 132 1,346 1961 3,398 6,928 1,617 1,824 137 1,350 1962 3,522 7,084 1,635 1,627 133 1,359 1963 3,656 7,271 1,874 1,539 146 1,385 1964 3,801 7,485 1,859 1,532 146 1,424 1965 3,959 7,733 2,276 1,631 376 1,480 1966 4,132 8,022 2,409 1,864 429 1,558 1967 4,322 8,936 2,402 1,689 419 1,661 1968 4,531 10,357 2,977 1,244 479 1,792 1969 4,762 10,744 2,244 2,061 291 1,952 1970 5,017 10,549 2,469 3,623 283 2,132 1971 5,353 11,175 2,525 4,546 254 2,342 1972 6,045 13,575 2,509 4,379 300 2,667 1973 6,906 16,820 2,511 3,503 310 3,025 1974 7,952 20,496 3,260 2,317 476 3,418 1975 9,193 24,494 3,195 956 415 3,849 1976 10,628 28,062 3,339 213 487 4,323 1977 14,944 29,929 3,902 215 791 5,010 1978 18,046 34,068 2,922 217 333 5,815 1979 21,641 38,594 4,367 220 782 6,717 1980 25,769 43,575 3,498 217 534 7,729 1981 30,463 49,010 5,165 215 993 8,8541982 35,759 54,902 2,875 213 305 10,0971983 41,692 61,258 3,462 211 213 11,4621984 48,299 68,088 3,723 210 297 12,955 1985 55,613 75,404 3,740 209 295 14,581 1986 63,666 83,222 3,340 209 313 16,344 1987 72,485 91,557 3,320 208 341 18,250 1988 82,095 100,421 3,635 208 564 20,303 1989 92,517 109,827 3,305 209 729 22,506 1990 103,773 119,787 3,516 211 727 24,863 1991 115,878 130,309 3,712 223 723 27,379 1992 129,588 142,223 3,930 237 910 30,227 1993 143,888 155,021 4,382 251 839 33,240 1994 159,100 168,425 6,669 265 696 36,421 1995 175,251 182,452 6,345 278 724 39,776 1996 191,554 197,936 8,640 290 820 43,309 1997 212,045 216,096 8,731 301 1,110 47,605 1998 230,874 232,641 10,096 312 1,426 51,536 1999 252,358 253,234 13,446 323 2,103 56,213 2000 274,425 273,137 12,964 334 1,993 60,877 2001 292,899 287,072 14,137 346 2,494 64,480 2002 316,250 308,547 14,396 358 2,816 69,462 2003 340,333 312,259 14,079 371 2,526 72,551 2004 366,471 340,405 15,941 384 2,964 78,584 2005 396,431 350,622 16,653 396 3,032 83,050 2006 423,869 374,973 26,875 409 3,727 88,806 2007 455,669 397,698 27,612 422 4,016 94,865 2008 494,756 416,418 28,350 435 4,305 101,290 2009 530,136 441,684 29,088 448 4,594 108,030 2010 564,994 466,442 29,826 461 4,883 114,655

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referenCes

Agger P (1976) Yemen Arab Republic–Stock Assessment FI: DP YEM/74/003/3, FAO, Rome. 1-42 p.Anticamara JA, Watson R, Gelchu A and Pauly D (2011) Global fishing effort (1950–2010): Trends, gaps, and

implications. Fisheries Research 107(1–3): 131-136.Barrania A, Bringi MR and Saleh M (1980) Socio-economic aspects of the Saudi Arabian fisheries in the Red Sea. FAO/

UNDP Proj. for Development of Fisheries in Areas of the Red Sea and Gulf of Aden, Suez, Egypt.Barrania AA (1979) The exploratory socio-economic survey of the Sudanese Red Sea fisheries. FAO/UNDP Proj. for

Development of Fisheries in Areas of the Red Sea and Gulf of Aden, Rome.Brodie J, M., Al-Sorimi and Turak E (1999) Fish and fisheries of Yemen’s Red Sea. In DouAbul A, Rouphael TS and

Marchant R (eds.), Ecosystems of the Red Sea coast of Yemen. Protection of Marine Ecosystems of the Red Sea Coast of Yemen. Hassell & Assoc., AMSAT and UNOPS.

Campleman G (1977) Fisheries and Marketing in YAR FAO, Rome.Chakraborty D (1983) Marine fisheries statistics in Sudan - an expanded plan of development. FAO, Rome. 39 p.Chakraborty D (1984) Fishery statistics in the Egyptian Red Sea coast an expanded plan. FAO/UNDP, Suez (Egypt).Chakraborty D, Moharram M and Waheed A (1983) An account of basic fisheries information of the South Sinai

Governorate in Egypt. Development of Fisheries in Areas of the Red Sea and Gulf of Aden, United Nations Development Programme (UNDP) and Food and Agriculture Organization (FAO) of the United Nations, Cairo (Egypt). 26 p.

Dalzell P, Corpuz P, Ganaden R and Pauly D (1987) Estimation of maximum sustainable yield and maximum economic rent from the Philippine small pelagic fisheries. Bureau of Fisheries and Aquatic Resources Tech Pap Ser 10(3), 23 p.

FA (2007) Fishery statistics of Sudan: based on the files of Fisheries Administration office in Port Sudan. Fisheries Administration, Khartoum.

FAO (2002) Information on Fisheries Management in the Republic of Yemen, February 2002. www.fao.orgFerrer GG (1958) Report to the government of Saudi Arabia on exploration and commercial fishing operations in the

Red Sea. FAO, Rome.GAFRD (2010) General Authority for Fisheries Resources Development database. Suez.Giudicelli M (1984) The Ethiopian fisheries: situation, development needs and opportunities. A report prepared for the

Fishing Planning and Development Project., FAO, Rome. 157 p.Grofit E (1971) The Red-Sea fisheries of Ethiopia (1966 - 1969). Min. of Foreign Affairs, Dep. for International

cooperation, Jerusalem. 82 p.Herrera M and Lepere L (2005) Revised catch estimates for tuna and tuna-like species caught by artisinal boats in

Yemen Indian Ocean Tuna Commitee (IOTC) 15 p.Kedidi SM, Abushusha T and Allam K (1984) Description of the artisanal fishery at Tuwwal, Saudi Arabia: catches,

efforts and catches per unit effort survey conducted during 1981–1982. FAO, Rome.Kristjonsson H (1956) A brief survey of the Sudanese red sea fisheries - Report to the government. FAO, Rome.MAW (2008) Statistical indications about fisheries in the Kingdom of Saudi arabia 2007. Ministry of Agriculture and

water, Department of Marine Fisheries. Kingdom of Saudi Arabia.MOF (2007) Eritrean Fisheries Database System. Ministry of Fisheries, Massawa, EritreaMoFW (2010) Catch Statistics Yemen 1990-2007. Ministry of Fish Wealth, General Department for Planning and

Statistic.Neve P and Al-Aiidy H (1973) The Red Sea Fisheries of Saudi Arabia. Bull.Mar.Res.Cent.Saudi Arabia 3: 32.ODA (1983) Report on project activities in Sudan. Overseas Development Agency, U.K.Sakurai T (1998) Fisheries of Saudi Arabia. Ministry of Agriculture and water, Department of Marine Fisheries and

Japan International Cooperation Agency.Sanders MJ, Kedidi SM and Hegazy MR (1984) Catches, fishing efforts, catches per fishing effort, and fishing locations

for the Gulf of Suez and Egyptian Red Sea fishery for reef associated fish during 1979 to 1982. FAO/UNDP, Suez (Egypt).

Walczak P (1977) The Yemen Arab Republic. A study of the marine resources of the Yemen ArabRepublic. A report prepared for the Fisheries Development Project. FAO, Rome. 67 p.