BAHIR DAR UNIVERSITY

COLLEGE OF AGRICULTURE AND ENVIRONMENTAL SCIENCES

GRADUATE PROGRAM

ASSESSMENT OF DIVERSITY AND STRUCTURE OF WOODY PLANT SPECIES AND

LAND COVER CHANGES OF SINKO COMMUNITY FOREST, FOGERA DISTRICT,

NORTH WESTERN ETHIOPIA

M.Sc Research Thesis

By

Abeje Zewdie

October 2013

Bahir Dar

BAHIR DAR UNIVERSITY

COLLEGE OF AGRICULTURE AND ENVIRONMENTAL SCIENCES

GRADUATE PROGRAM

ASSESSMENT OF DIVERSITY AND STRUCTURE OF WOODY PLANT SPECIES and

LAND COVER CHANGES OF SINKO COMMUNITY FOREST, FOGERA DISTRICT,

NORTH WESTERN ETHIOPIA

M.Sc Research Thesis

By

Abeje Zewdie

Major Advisor: Belayneh Ayele (PhD)

SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE

DEGREE OF MASTER OF SCIENCE (MSc.) IN LAND RESOURCE ANAGEMENT

October 2013

Bahir Dar

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THESIS APPROVAL SHEET As member of the Board of Examiners of the Master of Sciences (M.Sc.) thesis open defense examination, we have read and evaluated this thesis prepared by Mr Abeje Zewdie entitled Assessment of Diversity and Structure of Woody Plant species and Land cover changes of Sinko Community Forest, Fogera district, North western Ethiopia. We hereby certify that, the thesis is accepted for fulfilling the requirements for the award of the degree of Master of Sciences (M.Sc.) in Land Resource Management.

Board of Examiners

Yeshanew Ashagrie (PhD) _______________ _______________

Name of External Examiner Signature Date

Berehanu Abraha (PhD) _________________ _______________

Name of Internal Examiner Signature Date

Getachew Fisseha (PhD) _________________ _______________

Name of Chairman Signature Date

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DECLARATION This is to certify that this thesis entitled Assessment of Diversity and Structure of Woody Plant species and Land cover changes of Sinko Community Forest, Fogera district, North western Ethiopia Submitted in partial fulfillment of the requirements for the award of the degree of Master of Science in Land Resource Management to the Graduate Program of College of Agriculture and Environmental Sciences, Bahir Dar University by Mr. Abeje Zewdie (ID. No. k315/2003 is an authentic work carried out by him under my guidance. The matter embodied in this project work has not been submitted earlier for award of any degree or diploma to the best of my knowledge and belief. Name of the Student

Abeje Zewdie Signature & date _____________________

Name of the Supervisors

1) Belayneh Ayele (PhD) (Major Supervisor)

Signature & date _____________________

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Contents Pages LIST OF TABLES...vii LIST OF FIGURESviii APPENDICES...ix ABBREVIATIONS /ACRONYMS...x ACKNOWLEDGMENTS.xi DEDICATION.xii ABSTRACT....xiii 1. INTRODUCTION.1

1. 1 Background and Justification .......................................................................................1 1.2 Statement of the Problem ..............................................................................................3 1.3 Objectives of the Study .................................................................................................4 1.4 Research Questions .......................................................................................................5

2. LITERATURE REVIEW..6 2.1 Concepts of Biodiversity ...............................................................................................6 2.2 Floristic Diversity of Ethiopia .......................................................................................7 2.3 Threats on Plant Biodiversity in Ethiopia ......................................................................8 2.4 Diversity measurements ................................................................................................9 2.5 Classification of Plant Communities ........................................................................... 10 2.6 Plant population Structure ........................................................................................... 11 2.7 Land use /land Cover .................................................................................................. 12

2.7.1 Land use /land Cover Dynamics ........................................................................... 12

2.7.2 Why is studying LULC need? ............................................................................... 14

2.7.3 Satellite images for LULC .................................................................................... 15

2.8 Forest Management and Administration ...................................................................... 16 2.8.1Participatory Forest Management (PFM) ............................................................... 17 2.8.2 Common resource management ............................................................................ 19

3. MATERIALS AND METHODS..19 3.1 Description of the Study Area ..................................................................................... 19

3.1.1 Geographical location ........................................................................................... 19

3.1.2 Vegetation ............................................................................................................ 20

3.1.3. Climate ................................................................................................................ 21

3.1.4 Topography and soils ............................................................................................ 21

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( continued) 3.1.5 Population ............................................................................................................ 22

3.1.6 Livelihoods of the surrounding community ........................................................... 23

3.2 Methods of Data Collection ........................................................................................ 23 3.3 Methods of Data Analysis....................................................................................... 24

3.3.1 Diversity and evenness of species ......................................................................... 24

3.3.2 Measurement of similarity and dissimilarity.......................................................... 25

3.3.3 Classification of Community types ....................................................................... 25

3.3.4 Structural analysis................................................................................................. 25

3.3.5 Analysis of land cover changes ............................................................................. 27

3.4 Socio-Economic Data Analysis ................................................................................... 29 4. RESULTS AND DISCUSSION.30

4.1Woody Plant Species Diversity of Sinko community Forest ......................................... 30 4.2 Endemism ................................................................................................................... 32 4.3 Classification of Plant Communities in Siniko community forest ................................ 32

4.3.1 Riverine community type ...................................................................................... 33

4.3.2. Artificial Forest Community type ........................................................................ 34

4.3.3 Pterolobium stellautm- Carissa edulis community type ........................................ 34

4.3.4 Dodonaea viscosa- Osyris quadripartite community type ..................................... 35

4.4 Species richness, Diversity and Evenness of the Plant Community Types ................... 36 4.4.1 Similarity among the plant communities ............................................................... 37

4.4.2 Floristic comparison of Sinko community forest with other forests in Ethiopia ..... 38

4.5 Vegetation Structure ................................................................................................... 39 4.5.1 Tree and Shrub Density ........................................................................................ 40

4.5.2. DBH distribution ................................................................................................. 41

4.5.3 Height distribution ................................................................................................ 42

4.5.4 Vertical structure .................................................................................................. 43

4.5.5 Frequency ............................................................................................................. 44

4.5.6 Basal Area ............................................................................................................ 44

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( continued) 4.5.7 Importance Value Index (IVI) ............................................................................... 46

4.6 Land use /land cover changes in the study area ........................................................... 47 4.6.1Rate of land use and land cover changes in the study area ...................................... 52

4.7 Management Practices and Threats to Sinko Cmmunity Forest ................................... 53 5. CONCLUSION AND RECOMMENDATION56

5.1 Conclusion .................................................................................................................. 56 5.2 Recommendation ........................................................................................................ 57

6. REFERENCE59

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LIST OF TABLES

Table 3.1 Villages that surround the community forest ......................................................... 22

Table 3.2 Summery of data sources and material ................................................................ 27

Table 3.3 Description of land covers categories for change detection between 1985 to 2010 for the study area .................................................................................................................. 29

Table 4.1 Family, Genera and Species distribution of woody plants in Sinko community forest ............................................................................................................................................. 30

Table 4.2 Endemic species in Sinko community Forest ......................................................... 32

Table 4.3 Number of plots in each community of Sinko Community forest........................... 33

Table 4.4 ShannonWiener indices, Species richness and evenness of the plant Communities ............................................................................................................................................. 36

Table 4.5 Sorensons Similarity coefficient (%) among the four communities. ..................... 37

Table 4.6 the floristic Comparison of Sinko community Forest with other similar Forest in Ethiopia ................................................................................................................................ 38

Table 4.7 Tree density of Sinko community forest and other dry afromontane forests ........... 40

Table 4.8 vertical structure of Sinko Community Forest. ...................................................... 43

Table 4.9 Basl area contributions of species in Sinko community forest................................ 45

Table 4.10 Comparison of the Basal area of Sinko community Forest with area of other Forests in Ethiopia ................................................................................................................ 46

Table 4.11 Summary of overall classification accuracy and kappa coefficient ....................... 47

Table 4.12Land use land cover classes and rate of change between 1985 through 2010....52

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LIST OF FIGURES

Figure 3.1 Map of the study area20

Figure 3.2 Climadiagram at Debre-Tabor Station (based on 10 years data; from 1997-2006) 21

Figure 3.3. Flowchart............................................................................................................ 28

Fig 4.1Dendrogram of Sinko community forest using Ward Method and Euclidean distance 33

Figure 4.2 Artificial forest type in Sinko community forest ................................................... 34

Figure 4.3 Dodonaea viscosa- Osyris quadripartite community type in Sinko community

forest .................................................................................................................................... 35

Fig 4.4 Plant growth forms of Sinko community forest ......................................................... 40

Figure 4.5 DBH class distribution of woody species in Sinko community forest ................... 41

Figure 4.6 Measurment of DBH in sinko community forest .................................................. 42

Figure 4.7 Percentage distributions of trees in height classes in Sinko Community forest...... 43

Figure 4.8 Trends in land use land cover changes of Sinko Community forest from 1985 to 2010 ..................................................................................................................................... 48

Figure 4.9 land use/ land cover map of 1985 ......................................................................... 49

Figure 4.10 Land use land cover map of 2005 ....................................................................... 50

Figure 4.11 Land use Land cover map of 2010 ..................................................................... 51

Fig 4.12 Land certificate of Sinko community forest in Alember zuria Kebele ...................... 54

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APPENDICES

Appendices 1. Questionnaire survey to investigate the socio-economy of sinko community forest ........................................................................................................................................ 67

Appendices 2. Lists of woody species recorded in Sinko community forest with

corresponding family, vernacular name and plant forms ........................................................... 73

Appendices 3. Location of Quadrats in Sinko community forest ............................................... 81

Appendix 4. Frequency distribution of tree/shrub species in sinko community forest ............... 84

Appindex 5 the IVI of species in Sinko community forest (RD, relative density, RF relative frequency, RDO relative dominance and IVI important value index) ........................................ 86

Appendix .6 Different ground control points for classification. ................................................. 88

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ABBREVIATIONS /ACRONYMS a.s.l Above sea level

ANRS Amhara national regional state BA Basal area

CSA Central Statistical Authority b.s.l Below sea level

DBH Diameter at Breast Height

EPA Environmental Protection Authority

EPI Epiphyte

FAO Food and Agricultural Organization GLCF Global Land Cover Facility GPS Global Positioning System Ha Hectare

IBC Institutes of Biodiversity Conservation IVI Important Value Index

LULC Land Use Land Cover Changes NMA National Meteorological Agency

PaDPA Parks Development and Protection Authority

PFM Participatory Forest Management

SGAZ South Gondar Administrative Zone RD Relative density

RDO Relative Dominance RF Relative Frequency

SH Shrubs T Tree

WC Woody Climber m.a.sl meter above sea level

m.b.sl meter below sea level

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ACKNOWLEDGMENTS First and foremost, I praise to the Merciful Almighty God who blessed and taking care of me. I would like to express my deepest gratitude and sincere thanks to my advisors to Dr. Belayneh Ayele for his support, constructive comments and devoting precious time in guiding, searching of data, reading, as well as correcting of this thesis.My deepest thanks goes to Ato Birhanu Gedif who guided me the land use land coverches part in my study and

commenting correcting of the document without him it was difficult to achieve this work. I am very much indebted to my wife Mastewal Alimaw and my daughter Mahider Abeje for their encouragements, wonderful advises and endless supports; without them this research would not be complete. I want to thank my parents my father ato Zewdie Tewlatu and my

mother Zeyene Alene for their motivation, and incredible love. I want to thank my brother Bayebegn Zewudie who bought a laptop for writing the research work and his continuous advice and for his motivation. I want to extend my thanks to ANRS Bureau of Culture, Tourism and Parks development for giving me the opportunity to attend my study and

providing me financial support for the whole study and members of wildlife study, development, protection and utilization process for their cooperation and assistance during my study especially I would like to extend my gratitude to ato Kenaw Abeje who prepares the land use land cover maps of the area without him it was difficult to process GIS and remote

sensing data. I express my deepest sense of gratitude and acknowledgement to Wubaye Worku for his help during the challenging field survey and arranging the respondents for interview I wish if I could list all individuals who stood by my side, but I simply forward my heartfelt thanks and appreciation.

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DEDICATION

The Author is dedicated this work for wildlife scouts who lost their life in the protection of

protected areas. May the almighty God rest their soul in heaven?

xiii

Assessment of Diversity and Structure of Woody Plant Species and Land Cover Changes Of Sinko Community Forest, Fogera District, North Western Ethiopia

By Abeje Zewdie Advisor Belayneh Ayele (PhD)

ABSTRACT

This study was conducted on Sinko Community Forest in Fogera District, North Western Ethiopia with the objective of determining woody plant species diversity and structure, assessing land use land cover changes of the community forest and assessing the forest management practices of the community. Systematic sampling method was used to collect vegetation data. Accordingly, 47 quadrats each with 400 m2 (20 m X 20 m) were used for collection of woody species data .The sampling plots were placed at every 100 m intervals along the transect lines laid at 400 m a part along the slope. The land use land cover changes of the community forest were assessed using supervised image classification of images taken in 1985, 2005 and 2010. A total of 115 woody plant species, representing 91 genera and 61 families were recorded. From the 115 woody plant species, 53 species (46.08%) were trees, 50 species (43.48%) were shrubs, 10 species (8.71%) were woody climbers and 2 (1.74%) were epiphytes. Of all the families, Fabaceae was the most dominant of which contributing 14 species (12.17%) of the total. The forest had the Shannon- Wiener diversity index (H`) of 2.847 and evenness of 0.631. Four plant communities were identified from hierarchical cluster analysis i.e. Riverine, Artificial forest, Pterolobium stellautm- Carissa edulis and Dodonaea viscosa- Osyris quadripartite are the dominant communities. A floristic comparison of Sinko Community Forest with other related forests in Ethiopia revealed relatively high floristic similarity with Bahir Dar Abay Millennium Park with Sorensens similarity coefficient of 65.88%. Concerning the floristic structure of the community forest, all trees and shrubs with diameter at breast height (DBH) >2 .5 cm were measured for height and diameter analysis. The analysis of the diameter at breast height distribution shows normal inverted J-shaped pattern indicating that most of the populations found in lower diameter class. The analysis of the height distribution shows normal inverted J-shaped pattern indicating that most of the populations found in lower diameter class.i.e the first two lower classes contribute 59.2%. The total basal area of all tree species in Sinko community Forest calculated from DBH data was 22.08m2ha-1. Cupressus lusitanica, Syzygium guineense, Ficus vasta, Mimusops kummel and Eucalyptus camaldulensis were the most dominant species in their basal area. The total important value index of Sinko community forest was 299.8 out of these Dodonaea viscosa (42.5), Cupressus lusitanica (34.22) and Syzygium guineense (15.75) had the highest IVI. Threats of Sinko community forest were identified from the analysis of the questionnaire survey and the main threats were firewood, cutting of thorny bushes for fencing and charcoal making. Farmland was expanded at a rate of 11.556 ha/year, grassland increases at a rate of 4.36 ha/year and forest and bush land were reduced at a rate of 15.92 ha/year.

Keywords / Phrases: Community forest, Sinko, floristic composition, plant community, population structure, threat and land use land cover changes.

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1. INTRODUCTION

1. 1 Background and Justification

Ethiopia is a country of geographical diversity with high and rugged mountains, flat-topped plateaus, deep gorges, incised river valley and rolling plains. It is often known as the roof of

Africa due to its mountainous nature (Nievergelt, 1981; Meseret Chane, 2010). The Ethiopian relief includes a range of altitudes from 116 m b.s.l to 4533 m. a.s.l, (Hurni and Ludi, 2000; Britannica academic editions, 2011) and the country consists of many peaks above 2500 m.a.s.l. These extensive plateaus are bisected by the central rift valley. Afework Bekele and Corti,

(1997) ; Yalden (1983) stated that Ethiopia is a mountainous country unique by extent of its highland and over 80% of African highland areas above 3000 m altitude are located in Ethiopia. Approximately 15% of Ethiopian highlands are above 3,000 m. The afro-tropical region covers more than 300,000 km2 of land 2000 m asl, 50.4% of which is in Ethiopia and more than 25,000 km2 of land is above 3000 m (Yalden and Largen, 1992; Meseret Chane, 2010).

The altitudinal variations within Ethiopia produce a range of climate, which affect every aspect of life in the country; plant and animal distribution , the concentration of people and the types of agriculture; while temperature, rainfall and vegetation play major roles in determining the distribution of fauna and flora including that of endemic mammals (Yalden and Largen, 1992). The flora of Ethiopia is very diverse with an estimated number between 6,500 and 7000 species of higher plants, of which 12 % are endemic to Ethiopia (Yalden and largen, 1992).

Reports on the forest resources of Ethiopia are dominated by the alarming deforestation that goes on unabated and at an accelerating rate. Nationally, the current deforestation rate of natural

forests is estimated at 150,000200,000 ha per annum (EPA, 1998; EFAP, 1994; Badege Bishaw and Abdu Abdelkadir, 2003; Shambel Alemu, 2011). Deforestation takes place in both natural forests and from woodlands and it is recognized as the most severe environmental problem in Ethiopia.

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Starting from the beginning of civilization, human-beings have deliberately managed and converted the landscape to utilize and exploit natural resources mainly to derive basic needs such as food, shelter, fresh water, and pharmaceutical products (Menale Wondie et al, 2011). However, the increase in population has proportionally increased the demand for resources for centuries; leading to the conversion of natural environmental conditions. Ecological processes and human interventions are facilitating ecosystem changes as a whole and land cover change in particular. In particular term, LULC is a dynamic phenomenon occurring within the interface

between human agricultural and ecological systems. In most parts of the world, agriculture is the primary driver of land use change. The main pressure is to convert forests to agricultural uses in order to meet the increasing demands caused by human population growth (Goldewijk and Ramankutty, 2004).

The physical, social and economic situations in Ethiopia have contributed to the degradation of resources. There are different types of land cover formed by both human activities and natural factors over the last centuries. Population pressure accompanied by sedentary agriculture,

extensive animal husbandry, settlement and socio-political instability have resulted in heavy deforestation, forest fragmentation, loss of biodiversity and undesirable changes in the natural ecosystem, including LULC(Menale Wondie et al, 2011).

It has been noted that optional and existence value of species that is not known for their direct economic benefit today may turnout to be economically important in the future (IBC, 2005; Abraham Marye, 2009). Hence the study of diversity and structure of woody species, land use and land cover changes is relevant because woody plants (trees and shrubs) are essential structural components of the ecosystems they occur in, and they cater essential resources for a host of smaller organisms. Plants (with few exceptions) are also primary producers and therefore fundamental to the productivity of almost all ecosystems. Thus, plant species monitoring believed to show changing in plant and ecosystem at what rate and with what result.

Sinko community forest has relic biodiversity with significant natural forest and mid -altitude grassland flora and fauna but the area is under continuous human pressure. The major objective of this study is therefore; to explore diversity and structure of woody species in different

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communities of Sinko community forest and to evaluate land use/ land cover changes of the study area.

1.2 Statement of the Problem

Sinko community forest was demarcated as a community forest in 1981. After one year the

forest was administered by Fogera Woreda Office of Agriculture as woreda owned state forest

and it was protected for 10 years in this category. After the down of the military gov`t, the forest

was renamed as community forest in 1992, during this time the forest was completely degraded

and only remnants were left. After 20 years (in 2012) the frost was re-demarcated and given to

Amhara Forestry Enterprise as plantation site. The site doesnt have enough protection even

though it is demarcated. It is being continuously exploited by the surrounding people for fuel

wood, charcoal production, agricultural land, cutting of thorny species for fencing and other

purposes. The firewood and charcoal supply for the nearby Alember town is mainly obtained

from this community forest. Moreover, little is known about the Community Forest as there is no

floristic and structural study of the forest conducted before.

The availability of accurate data on forest resources is an essential requirement for management and planning within the context of sustainable development (FAO, 2010). Assessments such as woody species diversity and structural studies are essential in understanding the extent of plant diversity in forest ecosystem (Shambel Alemu, 2011). Knowledge of floristic composition and structure of forest resources is also useful in identifying important elements of plant diversity, protecting threatened and economic species and monitoring the state of reference among others. Reduction in forest cover has a number of consequences including soil erosion and reduction capacity for carbon sequestration, loss of biodiversity and instability of ecosystems and reduced

availability of various wood and non-wood forest products and services (Shambel Batiwalu, 2010).

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Unmanaged land use resulted in ecological degradation and loss of unique ecosystems with their endemic components of biodiversity. So land use and land cover change is increasingly recognized as an important driver of environmental change on all spatial and temporal scales

(Behailu Assefa, 2010). Land use and land cover changes contribute significantly to earth atmosphere interactions, forest fragmentation and biodiversity loss. It has become one of the major issues for environmental change monitoring and natural resource management. Its impact on terrestrial ecosystems including forestry, agriculture, and biodiversity have been identified as high priority issues in global, national, and regional levels (Goldewijk and Ramankutty,2004).

This thesis work is very important to fill a knowledge and information gaps that provide detail information on biodiversity (plant species richness) and structure of the forest and land cover changes. The knowledge gained can be used by policy makers and the local community for resource conservation and use of resources in a sustainable way. In addition to filling the

information and knowledge gaps, it is important for pland replantation of the area since the study identifies the species that are under threat in the last 30 years

1.3 Objectives of the Study General Objective

The general objective of this study is to assess the Diversity and Structure of Woody Plant species and Land cover changes of Sinko Community Forest.

Specific Objectives

The specific objectives of the study are:

To evaluate woody plant species diversity and structure

To examine land cover changes of the forest

To assess the forest management practices of the community

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1.4 Research Questions

This study tried to address the following critical questions What does the diversity and structure of woody plant species in Sinko Community forest looks

like? What does the trend in land cover change of the area look like?

What kinds of management practices are being percieved?

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2. LITERATURE REVIEW

2.1 Concepts of Biodiversity

The debate over the concept of diversity and its measurement is not new. According to Hammond and Daniel, (1997) stated diversity is simply a synonym for variability, where as biodiversity encompasses all biotic components of ecosystems and includes the diversity of genes, species, plant and animal communities, ecosystems, and the interaction of these elements.

Or it is the variability among living organisms from all sources, including inter-alia, terrestrial, marine and other aquatic ecosystems and ecological complexes of which they are part; this includes diversity within species, between species and ecosystems (UNEP, 1992; Aleminew Alelign, 2001).

Ecologists investigating terrestrial systems often focus on species diversity of plant communities

since green plants usually account for an overwhelming proportion of the biomass in a given system. In forests, biological diversity allows species to evolve and dynamically adapt to changing environmental conditions (including climate), to maintain the potential for tree breeding and improvement (to meet human needs for goods and services, and changing end-use requirements) and to support their ecosystem functions (FAO, 2010).

Plant biodiversity is one of the major groups of biological diversity. Plant diversity can be affected by different biotic and abiotic factors. The plant communities and their component species are exposed to changes in the environmental, physical, biological, technological, economic or social factors (Frankel et al., 1995). Globally, patterns of plant species diversity are influenced by altitudinal and soil gradients apart from other factors. Locally, in mountainous

ecosystems at high rate of change in altitude, slope and moisture gradients, temperature, rainfall and drainage, the diversity of plants may also change within a short distance (Hammond and Daniel, 1997). The other factors that highly influence plant diversity are human beings, as destructive factor (Ababu Anage, 2009). So, the fate of plant communities in a given area can be determined by these and other different factors. In this case, diversity and distribution patterns of species should be studied to clarify the plant diversity in certain area and to determine major factors influencing the diversity.

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2.2 Floristic Diversity of Ethiopia

Ethiopia has a large natural and cultural diversity with a wide range of climate, which results

from its topography and altitudinal position. It has diverse vegetation types in which diverse flora and fauna exist. The great plains of Ethiopia occur on top of massive highland plateaus like slopes of the Simien Mountains National Park, Bale Mountains National Park and other mountain ranges, where as the lowlands are dividing the highlands and the whole country into

two by the Great Rift Valley. Many of these mountain ranges reach over 4000 m a.s.l. and are home to numerous endemic species of flora and fauna (Dinkisa Beche, 2011)

The differences in altitude have resulted in a wide variation of climate parameters i.e., rainfall, humidity, temperature and exposure to wind, etc. These differences along with edaphic variations form the basis for the wide biodiversity of the country. This geographical and ecological diversity of Ethiopia, with extraordinary range of terrestrial and aquatic ecosystems,

contributed to the high rate of endemism and diversity (Ministry of Natural Resources and Environmental Protection, 1993; Dinkisa Beche, 2011)

Ethiopia is one of the twelve known ancient countries for crop plant diversities in the world and has valuable reserves of crop genetic diversity, of which 7 cultivated crops have their centre of origin or primary gene center while 26 crops have secondary gene center or center of diversity in the country (IBC 2005; Birhanu Gebre et al, 2007 ; Abraham Marye, 2009). The extensive and unique conditions in the highlands of the country have contributed to the presence of a large number of endemic species.

The vegetation of the country is very heterogeneous. It varies from semi-desert to Afro-alpine vegetation type (Friis et al., 2010). There are more than 6500 to 7000 higher plant species in Ethiopia of which about 12 % are endemic .These species represent 104 families and 387 genera

(Vivero et al., 2005 and IBC, 2009). The country has also over 300 tree species of which a few are used for construction and industrial purpose. The total number of woody species of Ethiopia is estimated to be 1017, out of which 29 tree species, 93 shrub species and 2 liana species are

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endemic (IBC, 2009). The Forest and woody vegetation resources of Ethiopia for 2010 were estimated to cover greater than 11.13 % of the total land area of Ethiopia (FAO, 2010).

At present, the Ethiopian vegetation is broadly divided into nine major types of vegetation zones (Friis, 1986 ; Abate Ayalew, 2003); These are afroalpine and sub-afroalpine vegetation, the dry evergreen montane forest and grassland, moist evergreen montane forest, evergreen scrub, Combretum- Terminalia (broad-leaved) deciduous woodland, Acacia - Commiphora (small-leaved) deciduous woodland, lowland semi-evergreen forest, the desert and semi-desert scrubland, and riparian and swamp vegetation.

The Ethiopian highlands contribute large coverage of land area with Afromontane vegetation, of

which Dry Evergreen Afromontane Forests form the largest part. Dry Evergreen Afromontane

Forest and Grassland complex vegetation type is complex system of succession with grassland rich in legume shrub and small to large trees to closed forest with a canopy of several strata. It occurs in an altitudinal range of 1800-3000 m a.s.l with average annual temperature and rainfall of 14-250C and 700-1100 mm, respectively (Abate Ayalew, 2003 and Dinkisa Beche, 2011).About 460 species, subspecies and varieties of woody plants occur in this vegetation type, from these 128 (28%) are reported only from this vegetation zone. This indicates that this vegetation zone is rich with species composition (Friis et al., 2010).

2.3 Threats on Plant Biodiversity in Ethiopia

The rich biodiversity of the country is under serious threat from deforestation, land degradation, overexploitation, overgrazing, habitat loss and invasive species (EPA, 1998; EPA, 2003; IBC ,2005). In most cases, the major destructive factor of plant diversity is deforestation caused by agricultural land expansion and fuel wood scavenging.

In current situations, Ethiopia is in the track of high investment rate, agro-industry expansion and population migration to a fragile ecosystem like forests and related resources. However, almost

all of these huge activities were done without prior environmental impact assessment (Dinkisa Beche, 2011). As a result, many virgin and irreplaceable forests are cleared for different investment sectors like livestock ranching, coffee and tea plantations and other cash crops.

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The other threats to the plant biodiversity of the country are unsustainable utilization of natural resources, forest fires, land degradation, habitat loss and fragmentation, extensive replacement of farmer's /local varieties/ breeds by improved ones, invasive species, wetland destruction ,

resettlement programs which cleared forest in the green belt areas of the country and climate change. But all these are related to the root causes of poverty, which are lack of alternative viable livelihoods, increasing population pressure and inadequate awareness of the threats (EPA, 1998; IBC, 2005). These different threats are in rapid progress threatening the conservation status of Ethiopia's plant diversity. The challenges to conserve and sustainable use of Ethiopias biodiversity are very complicated and interlinked (Dinkisa Beche, 2011)

2.4 Diversity measurements

Biological diversity can be quantified in different ways. A diversity index is a mathematical

measure of species diversity in a community. The two main factors taken into account when measuring diversity are richness and evenness. Species number was defined by Fisher et al. (1943), is simply the number of species found in a given community. Due to the implication that the exact number of species could be determined for a boundless community, the concept was

later referred to as species richness index, (Hammond and Daniel, 1997). Evenness, on the other hand, refers to the degree to which dominance is distributed among the species in a community. Evenness is highest if all species in the community are equally represented.

Species richness is a measure of the number of different species in a given site and can be expressed in a mathematical index to compare diversity between sites. A richness index may simply coincide with the number of species present in a community, but may also be a function

of the number of all the individuals in the community. The species richness of each community is simply the number of species present with at least one individual in a given area (Hammond and Daniel, 1997). The index is essential in assessing taxonomic and ecological values of a habitat.

The second factor, evenness, measures a relative abundance of different species. This refers to

the degree to which dominance is distributed among the species in a community (Hammond and Daniel, 1997 ; Dinkissa Beche, 2011). According to Frosini (2006), an evenness index is a

10

function of the frequencies or proportions pertaining to the species; such an index increases when the proportions tend to be equal or perfect homogeneity and decreases when one species tend to dominate all the others.

The interpretation of evenness is strictly dependent on the richness. Species diversity is the

product of species richness and evenness. Species diversity index provides information about species endemism, rarity and commonness (Frosini, 2006). Diversity indices also provide more information about community composition than simply species richness and relative abundances of different species (Kent and Coker, 1992; Frosini, 2006). The ability to quantify diversity in this way is an important tool for biologists trying to understand community structure. And also measuring diversity has been of historical significance due to the obvious declines in habitat diversity (Frosini, 2006). Among many species diversity indices the most widely used ones are Shannon-Wiener index, Simpsons index of Similarity and Sorenson`s index of similarity (Hammond and Daniel, 1997 ; Dinkisa Beche, 2011).

2.5 Classification of Plant Communities

A community, also known as biotic community or ecological community or biocoenosis, refers

to a group of co-existing and interacting populations in a given space and time (Mueller-

Dombois and Ellenberg, 1974; Kohli et al, 1999). A forest community is reflection of

coexistence and interactions of a variety of populations; the trees, shrubs, herbs, grasses, animals,

and microorganisms. In other words, it is the biological part of the ecosystem distinct from the

abiotic part. Each community has spatial limits or boundaries.

Community is a group of organisms representing multiple species living in a specified place and time .Each community should be named with two or more dominant species within a group (Shambel Bantiwalu, 2010). When an ecologist stands on a hilltop and surveys a landscape dominated by natural or semi -natural vegetation in any part of the world, the main differences in pattern visible in the landscape will be those of plant communities (Kent and Coker, 1992; Fekadu Gurmessa, 2010). Major distinction among plant communities will be conducted on the bases of physiognomy or the growth form of the vegetation. Plant communities are conceived as

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types of vegetation recognized by their floristic composition. The species compositions of communities better express their relationships to one another and environment than any other characteristic (Kent and Coker, 1992).

2.6 Plant population Structure

Population structure is defined as the distribution of individuals of each species in arbitrarily diameter-height size classes to provide the overall regeneration profile of the study of species

(Peters, 1996; Simon Shibru and Girma Balcha, 2004; Dereje Mekonnen, 2006; Semere Beyene, 2010). Information on population structure of a tree species indicates the history of the past disturbance to that species and the environment and hence, used to forecast the future trend of the population of that particular species (Peters, 1996). Population structure is extremely useful tool for orienting management activities and, perhaps most important for assessing both the potential of a given resources and the impact of resource extraction (Peters, 1996).

The population structure of a given species can be roughly grouped in to three types: Type I, II and III. Type I, shows the case in which diameter/height size class distribution of the species displays a greater number of smaller trees than big trees and almost constant reductions in number from one size class to the next (Peters, 1996; Simon Shibru and Girma Balcha, 2004; Abeje Eshete et al., 2005 Dereje Mekonnen, 2006; Semere Beyene, 2010). Such a pattern skewed to a reversed J-shape distribution in a forest are considered to have a favorable status of regeneration and recruitment and hence, stable and healthy population (Kindeya G/Hiwot, 2003).

Type II, is characteristic of species that show discontinuous, irregular and/or periodic recruitment. In this type, the frequency exhibited, for instance, in diameter /height size class

causes discontinuities in the structure of the population as the established seedlings and saplings grow in to larger size classes. Type III, reflects a species whose regeneration is severely limited for some reasons (Peters, 1996). Hence, knowledge about the category in which our study species fall is important issue before planning to utilize the resources.

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2.7 Land use /land Cover

2.7.1 Land use /land Cover Dynamics

Land is the major natural resource that economic, social, infrastructure and other human activities are undertaken on. Thus, changes in land-use have occurred at all times in the past, are

presently ongoing, and are likely to continue in the future (Lambin et al., 2003; Behailu Assefa 2010). These changes have beneficial or detrimental impacts, the latter being the principal causes of global concern as they impact on human well-being and safety. For instance, deforestation and agricultural intensification are so pervasive when they aggregate globally and significantly affect

key aspects of earth systems (Lambin et al., 2003).

Land use is the term that is used to describe human uses of the land (Lappiso Shamebo ,2010), or the social, economic, cultural, political or other value and function of land resources. Land use is

considered a central part of the functioning of the Earth system and reflects human interactions with the environment at scales from local to global (Lappiso Shamebo ,2010).

Land cover is a biophysical characteristic which refers to the cover of the surface of the earth,

whereas land use is the way in which humans exploit the land cover. Land use and land cover changes are caused by natural and human drivers, such as construction of human settlements, government policies, climate change or other biophysical drivers (Lambin et al., 2003; Behailu Assefa, 2010 ) or it is the attributes of the earths land surface captured in the distribution of vegetation, water, desert and ice and the immediate subsurface, including biota, soil, topography, surface and groundwater, and it also includes those structures created solely by human activities such as mine exposures and settlement (Lambin et al., 2003; Hussien Ali, 2009).

Changes in land cover involves both conversion and modification of cover (EU, 2001) and may be gradual or episodic (Lambin et al., 2003). Land cover change is associated with changes in biotic diversity, actual and potential primary productivity, soil quality, and runoff and sedimentation rates. Biodiversity is reduced when land is changed from relatively undisturbed state to more intensive uses like farming, livestock grazing, selective tree harvest, etc (Hiywot Menker and Rashid ., 2002).

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Land use and land cover change (LULC) is the human modification of the earths surface to expand production of many ecosystem services and economic benefits (Lovett, 1990). Currently the rate of land use change is causing undesirable effects on ecosystems observed at local,

regional and global scales. Land use and land cover change is responsible for global warming through the emission of greenhouse gases (Lambin et al., 2003; Hiywot Menker and Rashid, 2002). Land use affects land cover and changes in land cover affect land use. A change in either however is not necessarily the product of the other. Changes in land cover by land use do not

necessarily imply degradation of the land. However, many shifting land use patterns driven by a variety of social causes, result in land cover changes that affects biodiversity, water and radiation budgets, trace gas emissions and other processes that come together to affect climate and biosphere (Lappiso Shamebo ,2010).

Starting from the beginning of civilization, human-beings have deliberately managed and converted the landscape to utilize and exploit natural resources mainly to derive basic needs such as food, shelter, fresh water, and pharmaceutical products (Menale Wondie et al 2011). However, the increase in population has proportionally increased the demand for resources for centuries; leading to the conversion of natural environmental conditions. Ecological processes and human interventions are facilitating ecosystem changes as a whole and land cover change (LULC) in particular. In particular term, LULC is a dynamic phenomenon occurring within the interface between human agricultural and ecological systems (Agrawal et al, 2002). In most parts of the world, agriculture is the primary driver of land use change. The main pressure is to convert forests to agricultural uses in order to meet the increasing demands caused by human population growth (Goldewijk and Ramankutty, 2004).

A review of research on Ethiopian highlands showed that from 1860s to 1980s there had been decline in shrub land, woodlands and forestlands whereas cultivated land had increased considerably. This decline worsened between the 1980s and 2000s due to expansions in cultivated area especially on steep slopes and in marginal areas. In the highlands of Ethiopia land

use and cover change has reduced surface run-off and water retention capacity and stream flow leading to loss of wetlands and dying of lakes (Alemayehu Muluneh and Arnalds, 2011; Hiywot Menker and Rashid ., 2002).

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The physical, social and economic situations in Ethiopia have contributed to the degradation of resources. There are different types of land cover formed by both human activities and natural

factors over the last centuries. Population pressure accompanied by sedentary agriculture, extensive animal husbandry (livestock herding), settlement and socio-political instability have resulted in heavy deforestation, forest fragmentation, loss of biodiversity and undesirable changes in the natural ecosystem, including LULC (Menale Wondie et al 2011).

2.7.2 Why is studying LULC need?

The need for optimal use of the land resources and for balance of Land-Cover capability with anthropogenic stress is one of the mega-scale issues of mankind. The way people use the land

has become a source of widespread concern for the future of the world. The inability of many countries to balance environmental and production needs, as well as Land Cover capability and anthropogenic stress, emphasize these mega-scale issues. More than ever, therefore, the need for rational planning of land use/land cover development and optimal use of the land resources is

evident. Thats why precise and credible data on land use/land cover change and their trends are necessary for understanding global, regional and local environmental problems (Jensen, 2003; Netsanet Deneke, 2007; Behailu Assefa, 2010; Lappiso Shamebo ,2010). Land use data are also needed in the analysis of environmental processes and problems that must

be understood if living conditions and standards are to be improved or maintained at current levels. One of the prime prerequisites for better use of land is information on existing land use patterns and changes in land use through time (Anderson et al., 1976). Information on land use/land cover in the form of maps and statistical data is very vital for spatial planning,

management and utilization of land for agriculture, forestry, pasture, urban, industrial, environmental studies, economic production, etc. Today, with the growing population pressure, low land to man ratio and increasing land degradation, the need for optimum utilization of land assumes much greater relevance (Anderson et al., 1976; Kasay Berhe, 2004).

Documentation of the land use and land cover change provides information for the better understanding of historical land use practices, current land use patterns and future land use

trajectory. Land use/land cover change contributes significantly to earth atmosphere interactions,

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forest fragmentation, and biodiversity loss (Jansen and Gregoria, 2003). It has become one of the major issues for environmental change monitoring and natural resource management. Identifying, delineating and mapping of the types of land use and land cover are important

activities in support of sustainable natural resource management (Zhang et al, 2004).

2.7.3 Satellite images for LULC

Remote sensing and Geographic Information Systems (GIS) are providing new tools for advanced ecosystem management. The collection of remotely sensed data facilitates the synoptic analyses of earth-system function, patterning, and change at local, regional, and global scales

over time. Such data also provide a vital link between intensive, localized ecological research and the regional, national, and international conservation and management of biological diversity (Ernani and Gabriels, 2006; Behailu Assefa, 2010).

Remote Sensing is the science and art of obtaining information about an object, area, or phenomenon through the analysis of data (images) acquired by a device that is not in contact with object, area, or phenomenon under investigation (Lillesand et al, 2004). It provides a large variety and amount of data about the earth surface for detailed analysis and change detection

with the help of various space borne and airborne sensors ;For this research the researcher used data from space born sensors i.e. satellites . It presents powerful capabilities for understanding and managing earth resources. Remote Sensing has been proven to be a very useful tool for LULC change detection.

Change detection and monitoring involve the use of several multi-date images to evaluate the differences in LULC due to various environmental conditions and human actions between the acquisition dates of images (Singh, 1989 and Behailu Assefa, 2010). Successful use of satellite Remote Sensing for LULC change monitoring depends upon an adequate understanding of

landscape features, imaging systems, and methodology employed in relation to the aim of the analysis (Yang & Lo, 2002 and Behailu Assefa, 2010). With the availability of historical Remote Sensing data, the reduction in data cost and increased resolution from satellite platforms, Remote Sensing technology appears poised to make an even greater impact on monitoring land-cover and

land-use change (Rogan & Chen, 2004). In general, change detection of LULC involves the

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interpretation and analysis of multi-temporal and multi-source satellite images to identify temporal phenomenon or changes through a certain period of time.

Remote Sensing data are the primary source for change monitoring in recent decades and have made a greater impact for different planning agencies and land management initiatives (Yang and Lo, 2002; Behailu Assefa, 2010). Remotely sensed satellite images provide valuable datasets that can be used to analyze, evaluate, and monitor changes in ecosystems. One of the major hurdles of any satellite image analysis is how to accurately compensate for atmospheric effects. Several studies have investigated the ability of satellite imagery, including TM (thematic mapper) and TM+ (thematic mapper plus), to perform change analysis. The most commonly used remote sensing data for the extraction of earth surface feature for the classification of

LULC are: Landsat, SPOT, Radar, Aerial Photography, IKONOS, MODIS, AVHRR, etc (Lillesand et al, 2004)

2.8 Forest Management and Administration

The use of the forest resource depends on the way in which it is controlled. The nature of this control, in particular the form of ownership, provides the essential link between the forest

resource and its use (Chauhan, 2007). Regimes of control or ownership also have a strong influence on the condition of the resource. Whilst the relationship between control, use and condition of the resource is not constant, broad correlations exist between systems of control and patterns of use of natural resource. Political history determines the character of landownership in

general and the control of the forest resource in particular.

The Constitution of the Federal Democratic Republic of Ethiopia contains clauses relating to land ownership, and ultimately ownership of the natural resources contained on the land. Along

with the Constitution, the Federal Government has issued proclamations in support of land ownership rights. Article 40 of the Constitution proclaims that land is a common property of the Nations, Nationalities and Peoples of Ethiopia and is not subject to sale or other means of exchange.

Proclamation no. 456 /2005 authorizes communal ownership of forests, wherein rural land is given to local communities for livestock grazing, forestry and other social services. This

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proclamation sets a precedent for communal forestry. Other laws under the constitution do not recognize communal rights over land and forests as widely as the constitution. However, that does not mean that these laws prohibit the rights of communities to own and use forest resources

through their customary ways of management. But, based on the forest development, conservation and utilization proclamation No. 542/2007 of Ethiopian article 3 there are two types of forest ownership: i.e private forest and state forest. Based on the proclamation, community forests are grouped under private forests according to article 4 of sub-article 1 and 2 of the

proclamation. Private individuals, associations, governmental and non-governmental organizations and business organizations who want to develop forest shall have the right to obtain rural land in areas designated for forest development in accordance with regional land administration and utilization laws; The management plan shall be developed, with participation

of the local community, for forests that have not been designated as protected or productive state forests, and such forests shall be given to the community, associations or investors so that they conserve and utilize them in accordance with directives to be issued by the appropriate body; Proclamation no. 542 / 2007 (the Forest Proclamation) does not mention communal ownership of forests, only private and state ownership is mentioned.

2.8.1Participatory Forest Management (PFM)

Ethiopian Forest development, conservation and utilization proclamation No. 542/2007 and Forest Development, and the Conservation and Utilization Policy and Strategy of Ethiopia didnt directly state the application of Participatory Forest Management (PFM) but it was started by different NGO`S in collaboration with the government and local communities.

Participatory forest management is a strategy to achieve sustainable forest management by encouraging the management or co-management of forest and woodland resources by the communities living closest to them, supported by a range of other stakeholders drawn from local government, civil society and the private sector (Kerry et al, 2006). Participatory forest management incorporates two modes of management: i.e. Community-Based Forest Management and Joint Forest Management; A. Community-Based Forest Management refers to a forest management regime in which forest-

local communities are owner-managers of the Village Community Forest or Private Forests.

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B. Joint Forest Management refers to a forest management regime in which forest-local

communities are co-managers of Village Forest resources.Under Joint Forest Management Agreements with Ministry of agriculture or different levels of agricultural organizations.

The specific objectives of PFM are different in each country. Protection of national forest degradation and rural poverty alleviation were the main motivation behind leasehold forestry in

most countries. (Alemtsehay Jima, 2010). In Ethiopia PFM was recommended by NGO`s to solve the problem of forest degradation (Mustalahti, 2006). The motivation behind PFM program in Bale region was to conserve the unique biodiversity and ecological functions of the Greater Bale Mountains Ecoregion, whilst establishing and enhancing sustainable local community

livelihoods (Alemtsehay Jima, 2010). Sustainable forest management is not only a tool to improve livelihoods and conservation of forest resources but also is central to the achievement of many of the Millennium Development Goals (MDGs). Almost all MDGs are related to forests in one way or the other (Alemtsehay Jima, 2010).

Community forestry is contributing to livelihood promotion in many ways. These include fulfilling the basic needs of local communities, investing money in supporting income generation

activities of the poor people and providing access to the forestland for additional income or employment (Mustalahti, 2006). Participatory forest management can help for forestry based poverty alleviation which is defined as use of forest resources for the purpose of lessening deprivation of well-being on either a temporary or lasting basis, and when applied at household

level (Kerry et al, 2006), is divided into two types

Poverty mitigation or avoidance: the use of forest resources to meet household subsistence needs, to fulfill a safety net function in times of emergency, or to serve as a gap filler in

seasonal periods of low income, in order to lessen the degree of poverty experienced or to avoid falling into poverty; and Poverty elimination: the use of forest resources to help lift the household out of poverty by functioning as a source of savings, investment, accumulation, asset building, and lasting

increases in income and well-being. Forestbased poverty alleviation can be realized in four ways (Kerry et al, 2006): A. Converting forests to non-forest land uses such as permanent agriculture;

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B. Assuring access to forest resources and achieving this either by protecting the existing benefits that forests provide forest-local people, or by redistributing access to, and benefits from, forest resources;

C. Making transfer payments to forest-local people who protect forests environmental services; and D. Increasing the value of forest production through technologies that increase physical forest output, higher prices for forest products, increased processing and forest-based value-adding

activities, and the development of new products. But PFM is incompatible with converting forest to non-forest land uses.

2.8.2 Common resource management

Common resource management requires collective action, which in turn requires member cooperation to manage their resource effectively (Brian, 1999; Alemtsehay Jima, 2010).The effort of commons in collective action is directed towards the achievements of common goals.

Participants in common resource management face the dilemma of how to increase their own share of profit and at the same time contribute their best to the management of forest resource to stop further degradation through collective action (Mustalahti, 2006).

This raises a question on how to alleviate the problem of common good when managed by collective action. (Wade, 1987) recommended that, resource users need to develop a set of coordinated strategy on how to change the overexploitation activities in managing common

resource and resolve their common dilemma. The coordinated strategy involves formulation of rules of restrained access to common pool resource and inspection of that rule (Wade, 1987). Developing a strategy to resolve the common good dilemma creates a public good from which everyone may get a benefit regardless of her/his contribution to the management (Alemtsehay Jima, 2010).

3. MATERIALS AND METHODS 3.1 Description of the Study Area

3.1.1 Geographical location

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The study was conducted at Sinko community forest which is one of the community forest of Fogera woreda. Sinko is situated between the uplands of Chalm-Mintura Kebele and low laying areas of Alember zuria Kebele. It is located about 75 km North of Bahir Dar and about 22 km west of Deber Tabor, capital of South Gondar Administrative Zone. The area is located 1105323.61 to 1105505.11N and 3704942.93 to 3705253.31E with the total area 1797.1 ha and altitude ranges from 2072 to 2370 m.a.s.l

Figure 3.1 Map of the study area

3.1.2 Vegetation

The natural vegetation of Sinko community forest represents Dry Evergreen Montane Forest and woodland complex (Abrham Marye, 2010). It represents a complex system of successions involving extensive evergreen upland and rivrine forests, shrubs and small to

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large-sized scattered trees; seasonal dense shrub lands with ground cover vegetation. The highest dry upland areas are dominated with Mountain chains at the edge of cultivated areas.

3.1.3. Climate

Agro ecologically, the study area is classified as Woina Dega (sub-humid). There is no metreological station in the study area but the rainfall and the temperature condition of the area was described based on the data collected from 1997-2006 by the National Meteorological Agency (NMA) from Debre-Tabor Station which is the nearest NMA station 22 k.m to the study area. According to the data from NMA, the average annual minimum, maximum and mean

temperatures were 9.540C, 22.110C and 15.80C, respectively. The rainfall pattern is unimodal, stretching from May to September. Annual rainfall ranges between 1097 and 1954 mm with a long term average of 1448 mm (Nigussie Amsalu, 2010).

Figure 3.2 Climadiagram at Debre-Tabor Station (based on 10 years data; from 1997-2006) Data Source: NMA

3.1.4 Topography and soils

The soils of the study area are mainly dominated by Eutric Nitosol but at the foot slops of the area it is covered by Orthic Luvisol (FOA, 2005). Topographically, Sinko community forest is generally characterized by undulating to steep topography and inclined towards to East and

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north. The slope of the study area ranges from 6 to 75%; and within altitudinal range of 2072 to 2370 m a.s.l.

3.1.5 Population

According to the Central Statistical Agency of Ethiopia (CSA, 2010) the 4 Kebeles that have direct influence on the community forest had an estimated total population of 31,094 of whom 15,753 were males and 15,341 were females. There are 6,951households in the surrounding Kebeles.

Based on the 2012 reports of Alember zuria and Chalma Mintura Agricultural office, the

community forest is directly bordered by 13 villages which harbor 354 households which are directly dependant upon the community forest (Table 3.1). From the villages, Bekilo Mankia is at the core area of the forest which separates the community forest into two.

Table 3.1 Villages that surround the community forest S/N Name of the village Number of households Remark

1 Bastekua 23 Alember zuria

2 Awusiraji 19 3 Girar Minch 22

4 Gib warka 22

5 Adamu 21

6 Lay mender 24

7 Bikat 21

8 Hurichi 39

9 Tid mender 35 Chalma and Mintura

10 Merina 31

11 Bekilo Manekiya 22

12 Kulinta 46

13 Kerete mariyam 29

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Total 354

3.1.6 Livelihoods of the surrounding community

It is difficult to directly measure the contribution of the forest to the livelihoods of the community living close to the forest but reports from Alem Ber Zuria office of Agriculture and Chalma Minitura Office of Agriculture indicated that the farming system of the surrounding

villagers are mixed farmers that grows field crops like millet, barley, teff, maize etc. and rear animals especially of cattele and goat are the major agricultural activities in the study area that support the local community. The report also indicated that before 2012 fuelwood and charcoal selling from the community forest was one of the important livelihood options of the area

especially for the poor households. Before 2012 the main source of animal feed was grazing in the community forest and now the area is the main source of hay which alleviates the deficiency in animal feed. In general the forest products that are of highest importance for household needs and income generation include firewood which is the most important forest product for household needs, closely followed by hay and construction wood.

3.2 Methods of Data Collection

It is important to know the size of the vegetation as well as the number of plots to be laid out per hectare before data collection (As Panwar and Bhardwaji, 2005 cited in Shamble Batiwalu, 2010). Therefore reconnaissance survey was conducted from January 20-27/ 2013 to be familiarized with vegetation communities, topography, floristic structure soils and other

environmental factors. During the survey lists of plant species were recorded by local names.

The vegetation data collection was made from February to March 2013. A total of 47 sample plots were established systematically in 11 transect lines following the Braun-Blanquet approach (Mueller-Dombois and Ellenberge, 1974; Kent and Coker, 1992). The plots were laid at every 100 m interval along the transect lines, which were laid at 400 m apart. The data of major vegetation attribute were measured for trees, shrubs and woody climbers and recorded using twenty by twenty (20 m x 20 m) size plots which were established along the transect. In each plot structural attributes: such as diameter and height were recorded. Diameter was measured for

all individual trees and shrubs having DBH (Diameter at Breast Height) greater than 2.5 cm

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using a caliper. If the tree branched at breast height or below, the diameter was measured separately for the branches and averaged. Trees and shrubs with DBH less than 2.5 cm were counted. Height was measured for individual tree and shrub with DBH greater than 2.5 cm using Clinometers. At aplace where topographic was difficult, visual estimation was undertaken.

Perception of the local community and socio economic Data were collected using questionnaire from 184 respondents from 13 villages that were selected randomly. Three group discussants were used to explore the data and 6 key informants were used to enrich the data. Images were downloaded from GLCF http://glcf.umiacs.umd.edu/ accssed in December 10/2013. For different dates the procedure followed in this study was presented using the flow chart. It shows the steps followed beginning from the acquisition and classification of multi temporal satellite image of the study area to the extraction of the required information both secondary and primary data to answer the research questions.

3.3 Methods of Data Analysis

3.3.1 Diversity and evenness of species

The quantitative indices of species diversity, richness and evenness were measured using diversity index formula by Shannon and Wiener (1949). The minimum value of H' is 0, which is the value for a community with a single species, and increases as species richness and evenness

increases (Shambel Alemu, 2011). The Shannon Diversity Index (H) was calculated using the following formula.

Where S= total number of species;

Pi abundance of the ith the proportion of each species (individuals) or the

i= is species expressed as proportion of total cover; and ln= log base n

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High values of Shannon- Wiener diversity index is a representative of more diverse communities (Frosini, 2006).

Shannons Equitability (EH) or Evenness is given by H`Hmax H/lnS

The value of EH is between 0 and 1 with 1 being complete evenness. If the species are evenly distributed then the H value would be high. So the H value allows us to know not only the number of species but how the abundance of the species is distributed among all the species in the community (Frosini, 2006, Dinkissa Beche 2011 and Shambel Alemu, 2011)

3.3.2 Measurement of similarity and dissimilarity

Similarity indices measure the degree to which the species composition of quadrats or samples is alike, whereas, dissimilarity coefficient assesses which two quadrats or samples differ in composition (Dinkissa Beche 2011; Shambel Alemu, 2011)

Sorensens similarity index was used to determine the pattern of species turnover among successive communities and to compare the forest with other similar forests in the country. It is described using the following formula (Kent and Coker, 1992).

Where c=number of species with common to both communities; a= number of species unique to community 1; and b = number of species unique to community 2

3.3.3 Classification of Community types

Hierarchical cluster analysis was performed using SPSS v16 to classify the vegetation into plant community types based on abundance data of the species in each quadrat and the Euclidean Distance measures using Wards method were used in the current study.

3.3.4 Structural analysis

The structure of the vegetation was described using frequency distributions of DBH, height and Importance Value Index (IVI). Tree or shrub density and basal area values were computed on hectare basis. Importance value indices (IVI) were computed for dominant woody species based

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on their relative density (RD), relative dominance (RDO) and relative frequency (RF) to determine their dominance, and also the species were classified into three forms (tree, shrub, woody climber and epiphytes).

Importance value index was used to determine the overall importance of each species in the

community structure. In calculating this index, the percentage values of the relative frequency, relative density and relative dominance were summed up together and this value is designated as the IVI of the species

(a) Relative density. Relative density is the study of numerical strength of a species in relation to the total number of

individuals of all the species and can be calculated as:

Relative density Number of individuals of the species Number of individuals of all species *X100 (b) Relative frequency. The degree of dispersion of individual species in an area in relation to the number of all the

species occurred.

Relative frequency Frequency of a species Total frequency of all species* X100

(c) Relative dominance. Dominance of a species was determined by the value of the basal cover. Relative dominance is the coverage value of a species with respect to the sum of coverage of the rest of

the species in the area.

Relative Dominance Total basal area of speciesTotal basal area of all species* X100 The total basal area will be calculated from the sum of the total diameter of immerging stems. In

trees, poles and saplings, the basal area will be measured at breast height (1.3m) and by the formula 2345678

9 or A=0.785DBH2 by using calipers.

So Importance value index = Relative density+ Relative frequency+ Relative dominance

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3.3.5 Analysis of land cover changes

ArcGIS 9.3 and ERDAS 9.1 software were used for satellite image analysis and mapping. Present and past information on land cover and land use change for the study area was generated

from remotely sensed data. The image data used for this study were Landsat Themathic Mapper 1985, ETM+ 2005 and ETM+ 2010 which was obtained from GLCF http://glcf.umiacs.umd.edu/ accssed in December 10/2013 (Table 3.2).

Table 3.2 Summery of data sources and material Satellite Image Data

Source

Image Type

Path and Row

Date of Acquisition

Resolution (meter)

Landsat-TM

169/52 09/11/1985 30X30 GLCF

Landsat-ETM+

169/52 23/10//2005 30X30 GLCF

Landsat-ETM+

169/52 16/12/2010 30X30 GLCF

The procedure followed in this study was presented using the flow chart (Figure 3.3). It shows the steps followed beginning from the acquisition and classification of multi temporal satellite image of the study area to the extraction of the required information both secondary and primary data to answer the research questions.

Satellite image Landsat (1985, 2005&2010)

Field Survey GPS Data

Data sources and collection

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Figure3.3. Flowchart

Image Enhancement and Interpretation

Satellite image contains a detailed record of features on the ground at the time of data acquisition. Lillesand et al (2004) suggested that image interpreters should have good power of observations coupled with imagination and it is important that the interpreters have a careful understanding of the phenomenon being studied as well as knowledge of the geographic region under study.

To do so, digital image enhancement and interpretation techniques were used in this study. To increase the visual interpretability of the satellite images and the amount of information that can be visually interpreted from the data both True Colour Composite (RGB 3, 2, 1) and False Colour Composite (RGB 4, 3, 2) were produced. Digital image enhancement techniques such as contrast stretching and histogram equalization were used.

Ground Truthing

The two primary reasons for visiting the area that is being mapped were to collect data that can be used to train the algorithm or the interpreter and to collect data that can be used to evaluate the land cover map and estimate the accuracy of the individual classes (a process called

Digital image Preprocessing

Image interpretation And classification (Supervised classification)

Land-use /land cover map 1985, 2005&2010

Classification Accuracy Assessment

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validation). The data was collected from the study area and used as ground control points during classification. Appendix 6 shows different ground control points for classification.

Description of land covers classes As there are some differences between the land classes in the historical land cover maps of 1985, 2005 and 2010 land cover classes, which can be discriminated from the satellite image, recoding was needed to create a common classification for change detection purposes. This section describes the land classes, which are only used for

land-cover mapping from satellite images (Table 3.3).

Table 3.3 Description of land covers categories for change detection between 1985 to 2010 for the study area

Land cover General description

Farmland Areas of land ploughed/prepared for growing rain fed or irrigated crops. This category includes, land currently under agricultural crops or temporarily unplanted land, excluding grassland areas

Forest and bush land Areas covered with trees and shrubs mainly the Riverine community type, Artificial forest Community type, Pterolobium stellautm- Carissa edulis community type and Dodonaea viscosa- Osyris quadripartite community type

Grassland All areas covered with mainly natural pasture, but also other small sized plant species

3.4 Socio-Economic Data Analysis

Data about the importance and impacts of the study area were collected by using semi-structured interview and tallied after it has been checked as filled properly. The local

communities perception data on the community forest were fed to Excel spread sheet and described in descriptive statistics

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4. RESULTS AND DISCUSSION

4.1Woody Plant Species Diversity of Sinko community Forest

A total of 115 woody plant species belonging to 91 genera and 61 families were recorded and identified from Sinko community forest (Appendix 2). Out of these, 53 species were trees, 50 species were shrubs, 10 species were woody climbers and 2 were epiphytes. Ninety one species were recorded in the study quadrats the rest were recorded along the transect line outside the study quadrats.

Of all the families, Fabaceae was the most dominant with each contributing 14 species to the total and followed by Euphorbiaceae, Moraceae and Verbenaceae with 6 species, 6 species and 5 respectively. Thirty eight families consisted of only 1 species each. The number of species and

genera for the rest of the families are given in (Table 4.1.) In addition, from the species data collected in the study area, 98.26 % were flowering plants out of which, 94.78% were dicots and the remaining 3.48% were monocots. The result agreed with the results obtained by Aleminew Alelign (2001) in Zegie peninsula he had got 113 woody plant species representing 52 families.

Even if there is a high level of disturbance in Sinko community forest it is possible to say that

woody species richness is high.The area is not only known by its species richness but also the number of families in the study area is diverse.Of all the total woody species recoreded in the study quadrats, trees constitute the highest number of species (46.08%) over the life forms.

Table 4.1 Family, Genera and Species distribution of woody plants in Sinko community forest

No Family Genera Species Number % Number %

1. Acanthaceae 2 2.20 3 2.61 2. Agavaceae 1 1.10 1 0.87 3. Anacardiaceae 1 1.10 2 1.74 4. Apiaceae 2 1.10 2 1.74 5. Apocynaceae 1 1.10 1 0.87 6. Araliaceae 1 2.20 1 0.87 7. Arecaceae 1 1.10 1 0.87 8. Asteraceae 1 1.10 4 3.48 9. Bignoniaceae 2 2.20 2 1.74 10. Boraginaceae 1 1.10 1 0.87

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No Family Genera Species Number % Number %

11. Buddlejaceae 1 1.10 1 0.87 12. Cactaceae 1 1.10 1 0.87 13. Caesalpiniaceae 2 2.20 2 1.74 14. Capparidaceae 1 1.10 1 0.87 15. Casuarinaceae 1 1.10 1 0.87 16. Celastraceae 1 1.10 2 1.74 17. Combretaceae 1 1.10 1 0.87 18. Cupressaceae 2 2.20 2 1.74 19. Ebenaceae 1 1.10 1 0.87 20. Euphorbiaceae 6 6.59 6 5.22 21. Fabaceae 7 7.69 14 12.17 22. Flacourtiaceae 1 1.10 1 0.87 23. Hypericaceae 1 1.10 1 0.87 24. Icacinaceae 1 1.10 1 0.87 25. Lamiaceae 2 2.20 3 2.61 26. Liliaceae 1 1.10 1 0.87 27. Longanaceae 1 1.10 1 0.87 28. Loranthaceae 2 2.20 2 1.74 29. Malvaceae 3 3.30 3 2.61 30. Meliaceae 1 1.10 1 0.87 31. Melianthaceae 1 1.10 1 0.87 32. Moraceae 1 1.10 6 5.22 33. Myricaceae 1 1.10 1 0.87 34. Myrsinaceae 3 3.30 3 2.61 35. Myrtaceae 2 2.20 3 2.61 36. Oleaceae 3 3.30 3 2.61 37. Oliniaceae 1 1.10 1 0.87 38. Papilionaceae 2 2.20 2 1.74 39. Phytolacaceae 1 1.10 1 0.87 40. Pittosporaceae 1 1.10 2 1.74 41. Poaceae 1 1.10 1 0.87 42. Polygonaceae 1 1.10 1 0.87 43. Proteaceae 1 1.10 1 0.87 44. Ranunculaceae 1 1.10 1 0.87 45. Rhamnaceae 1 1.10 2 1.74 46. Rhizophraceae 1 1.10 1 0.87 47. Rosaceae 2 2.20 2 1.74 48. Rubiaceae 1 1.10 1 0.87 49. Rutaceae 1 1.10 1 0.87 50. Santalaceae 1 1.10 1 0.87 51. Sapindaceae 1 1.10 1 0.87 52. Sapotaceae 1 1.10 1 0.87 53. Scrophulariaceae 1 1.10 1 0.87 54. Simaroubaceae 1 1.10 1 0.87 55. Solanaceae 1 1.10 2 1.74 56. Sterculiaceae 1 1.10 1 0.87 57. Tiliaceae 1 1.10 1 0.87 58. Ulmaceae 1 1.10 1 0.87 59. Urticaceae 1 1.10 1 0.87

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No Family Genera Species Number % Number %

60. Verbenaceae 4 4.40 5 4.35 61. Vitidaceae 1 1.10 1 0.87 Total 91 100.00 115 100.0

4.2 Endemism

Sinko community Forest contains a number of flowering plant species that are endemic to Ethiopia. Endemic plant species of Ethiopia and their level of threat have been given in Ensermu

Kelbessa et al. (1992) ;Vivero et al. (2005). Accordingly, (3.5%) endemic species, some of which are in the IUCN Red data list, were identified in Sinko community forest. Based on available literature (Vivero et al., 2005), the endemic species and their status are given in Table (4.2).The results of the study agrees with Dikissa Beche (2011) he identifies 9 endemic woody species this indicates that dry evergreen afromontane forests are not only the centers of diversity but also it harbors some endemic and threatened species that needs conservation

Table 4.2 Endemic species in Sinko community Forest

No. Scientific Name Family Local Name Status

1 Achanthus sennii Acanthaceae Sete kusheshilie NT

2 Clemanths longicauda Ranunculaceae Azo hareg NT

3 Milletia ferruginea. Fabaceae Birbira LC

4 Rhus glutinosa Anacardiaceae Embus VU

(EN= Endangered, LC= Least concerned, NT=near threatened, VU= Vulnerable, CR= critically endangered)

4.3 Classification of Plant Communities in Siniko community forest

Based on hierarchical cluster analysis using Wards method in SPSSv16 four clusters were identified in the study area. Communities were named based on the dominant species and nature of the community. The four plant communities identified were riverine (community I), artificial forest (community II), Pterolobium stellautm - Carissa edulis type (community III) and Dodonaea viscosa- Osyris quadripartite type (community IV). The number of plots in each community is located in table (4.3) and the Dendrogram of Sinko Community forest is attached in figure (4.1)

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Table 4.3 Number of plots in each community of Sinko Community forest s/n Community types Remark (Quadrats)

CI Riverine 1,2,13,15,22,40

CII Artificial forest 3,4,12,14,23,24

CIII Pterolobium stellautm- Carissa edulis type

5,7,8,11,16,18,26,28,29,30,35,37,38,41,42,43,44,46,47

CIV Dodonaea viscosa-

Osyris quadripartite type

6,9,10,17,19,20,21,25,27,31,32,33,34,36,39, 45,

4.3.1 Riverine community type

This community type was represented by 46 species. The altitudinal range of this community was from 2072 to 2187 m a.s.l and at a slope of 10 to 70%. Woody species (trees, shrub and woody climbers) associated with this community especially with large trees

Figure 4.1Dendrogram of Sinko community forest using Ward Method and Euclidean distance (C1= Community type 1, C2= Community type 2, C3= Community type 3 and C4= Community type 4) such as Syzygium guineense, Mimusops kummel, Rhus vulgaris from the shrubs and woody climbers Pterolobium stellautm, Carissa edulis, Hibiscus ludwigil, Capparis tomentosa,

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Achanthus sennii, Bersama abyssinica, Osyris quadripartite, Grewia ferruginea, Dombeya quinquesteta, Jasminum abyssinicum, Maytenus gracilipes, Embelia schmperi, Ficus sur and Ficus sycomorus are the dominant species of this community.

4.3.2. Artificial Forest Community type

This community comprised 23 species. The community is distributed between the altitudinal ranges of 2097 to 2186m a.s.l. and at a slope of 6 to 25% .As shown in (figure 4.2) this community is mostly dominated by Cupressus lusitanica and Eucalyptus camaldulensis in addition to these dominant specie the following species are of this community type Achanthus

eminens, Achanthus sennii, Vernonia auriculifera, Carissa edulis, Maesa lanceolata, Acacia nilotica, Ocimum lamiifolium, Premna schimperi, Rumex nervosus, Vernonia adoensis and Maytenus arbutifolia

Figure 4.2 Artificial forest type in Sinko community forest

4.3.3 Pterolobium stellautm- Carissa edulis community type

This community type was distributed and is situated at altitudinal ranges from 2008 to 2370 m a.s.l and at a slope of 12 to 60%. The community is comprised of 68 species. This community type is mainly comprised Pterolobium stellautm, Carissa edulis,Osyris quadripartite in addition

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to the above dominant species the community comprised Dodonaea viscosa , Achanthus sennii, Vernonia auriculifera, Capparis tomentosa, Bersa