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LIVELIHOOD VULNERABILITIES OF FISHING HOUSEHOLDS IN THE VOLTA BASIN, GHANA
Francis K.Y. Amevenku1, Alhassan W. Seini1, Yaw B. Osei-Asare1, John K. M. Kuwornu2, Henry Anim-Somuah1
1Department of Agricultural Economics and Agribusiness, School of Agriculture, Collegeof Basic and Applied Sciences, University of Ghana, Legon.
2Agribusiness Management/Agricultural Systems and Engineering, School ofEnvironment, Resources and Development, Asian Institute of Technology, Pathum Thani 12120, Thailand.
FISHADAPT A GLOBAL CONFERENCE ON CLIMATE CHANGE ADAPTATION FOR FISHERIES AND AQUACULTURE
8-10 AUGUST 2016 CENTARA GRAND LADPRAO, BANGKOK, THAILAND 1
OUTLINE OF PRESENTAION Introduction
Research Problem, Questions and Objectives
Methodology
Results
Conclusions & Policy Recommendations
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INTRODUCTION
The construction of Akosombo Dam on the Volta River in 1965 created one of the
largest man-made reservoirs in the world with 437 human settlements dotted
downstream (VRA, 2010).
Along with Kpong dam, approximately 25 km downstream, these dams provide
85-95% of the power for Ghana and 40 per cent of the power for the regional grid
system (Fiagbe and Obeng, 2006).3
INTRODUCTION
The creation of dams on the Volta River had created a productive fishery, that
contributes 16% of Ghana’s total fish output FAO (2005).
But have distorted the natural river flows by storing and releasing water in
rhythm with the patterns of electricity demand in the service area rather than the
seasonal patterns of rainfall and runoff in the catchment area (Kalitsi, 1999).
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INTRODUCTION
Resultant small scale fisheries now plagued with problemsof:
continually low and dwindling fish productivity; lowdiversity; prevalence of diseases;
weed infestation of the fishing grounds; loss of livelihoodopportunities (Tsikata, 2012).
5
Also, change in the water flow due to the dams has caused:
a drastic reduction in floodplain agriculture;
explosion of exotic weeds - choked off the once lucrative shell fishery;
increase in disease vectors of bilharzias;
the formation of a permanent sandbar at the estuary (VBRP, 2008).
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INTRODUCTION
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7
• This picture was taken at Kpong Beach to show the extent to which weedshave proliferated in the Lower Basin.
• A contributor in addition to other factors worsening fish catches and thereforethreatening livelihoods.
INTRODUCTION
INTRODUCTION
These negative environmental, social and economic impacts are
unfortunate and unnecessary and there is need to restore downstream
ecosystems and human livelihoods.
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INTRODUCTION
In addition, climate variability and uncertainty complicate the task of
identifying impact pathways and areas of vulnerability, as it affects:
The biological, chemical and physical processes in the ecosystem
resulting in changes in fish life cycles, habitats, species composition,
distributions or abundance
impact on livelihoods, food security and sustainable development.9
INTRODUCTION
The capacity of the Volta basin to produce fish does not depend only on its bio-physicalcharacteristics.
A substantial part of its productivity is influenced by the human (social, economic,institutional) dynamics of the activities which take place within the basin.
Households have had to devise some strategies for survival.
The extent to which livelihood diversification could reduce resultant vulnerabilities that hadevolved around parts of the Volta Basin in Ghana is subject of study.
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THE PROBLEM
Changes in the ecosystems of the Volta River diminished income andlivelihood opportunities resulting in impaired living standards.
Disparities apparent along sections of the basin - weakening security oflivelihoods rendering them potentially vulnerable yet the eradication oflivelihood vulnerabilities remain a major concern of the world (UN,2012).
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THE PROBLEM
Livelihood diversification remains the most important source of reducing
vulnerability and capacity to diversify livelihoods and income sources thus crucial for
the survival of households (e.g. Shepherd et al, 2011; Deressa et al, 2010;).
Despite the recognition of Livelihood diversification as an important element for
reducing vulnerability among fishing households, its attainment vary widely across
sections of the basin and appeared to be based on the fishery resource endowments
specific to an area.12
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THE PROBLEM
In the context of the Lower Volta Basin for instance, diversification through
depends on locally available resources (Ofori et al, 2008; VBRP, 2008; Tsikata,
2005).
This questions sustainability and resilience (Ofori et al., ibid; Tsikata, 2005).
Households cope with risks associated with fishing and embark on diversification
strategies out of desperation (Lay and Schuler, 2008).
Livelihood vulnerability persist amidst some form of diversification. 13
RESEARCH QUESTIONS
Questions central to this study include:
What level of vulnerability pertains in fishing households in the Volta Basin?
What is the extent of livelihood diversification and how does it affect their
vulnerabilities?
What accounts for the effects of diversification on vulnerabilities of livelihoods
across the Volta Basin ?
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RESEARCH OBJECTIVES
The broad objective: to examine livelihood vulnerabilities vis a vis diversification of
fishing households along the Volta Basin Area in Ghana.
The specific objectives are:
To determine and segregate fishing households in terms of vulnerability;
To estimate the effect of livelihood diversification on vulnerability of fishing households;
To assess the differences in the effects of diversification on vulnerabilities prevalent in
fishing households with respect to their locations.
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METHODOLOGY
Types and sources of data
Primary data collected through direct personal interview;
Secondary data (Time series data) form the Ghana Meteorological Service over
the period 2005 to 2014 (rainfall & temperature).
In addition, community based factors were identified through consultations with
local experts, focus group and key informant discussions.16
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Sampling Technique and Study Area
A multistage sampling technique: (Purposive and Simple Random Sampling)
First purposive: 4 Administrative Regions of Ghana known to be associated with the Volta
Basin fishery - Greater Accra, Volta, Eastern & Brong- Ahafo;
Second purposive: 7 districts associated with the fishery:
North, Central & South Tongu; Ada East, Asuogyaman, Lower Manya: designated as:
LV1, LV2 and LV3 for the purpose of this study (Figure 1); and
Stratum VII in the Pru district (Figure 2) in the Brong- Ahafo region of Ghana.17
9 °
8 °
7 °
6 °
5 °
1 ° 0 ° 1 °
0 1 0 0 K m .
II I
I I I
I V
V
V I
V I I
V I I I N
T H E V O L T A L A K E A N D I T S M A J O R T R I B U T R I E S I N G H A N A
18
6°00'N
6°30'N
Agotaga
0°00'
Kpong
Old Ningo
0°30'E
0 5
Akplabanya
Ada
Big Ada
Agave
1°00'E
10
WutiAtiteti
Anyanui Anloga
Agodome
Volivo
Akosombo
Amedeka
Kpong
Senchi
Asutsuare
Adomi
Gyakiti
Ajena
Bator
Sokpoe
Bakpo
Tefle
Adidome
Sogakope
LEGEND
River / Stream
Road
Town
Bridge
Sampling Point15 20km
Scale
Abotia
C O
T E
D'
I V
OI R
E
10°00'N
11°00'NB U R K I N A F A S O
0 20 80
SCALE
40 60
T O G
O
5°30'N
LOWERVOLTA
Mepe
(LV1)(LV2)
(LV3)
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Table 1: Characteristics of segments of the Study Areas
Segment Characteristics
Lower Volta Area IFormation of sandbar at the estuary limiting inflow of seawater into the river at high tide;Reduction of floodplain agriculture;Explosion of aquatic weeds that blocked fishing grounds;
Lower Volta Area II
Infestation of creeks, streams and main fishing channels by aquatic weeds;
Collapse of floodplain farming;Cessation of influx of seawater at high tide leading to collapse of shell fish fishery;
Lower Volta Area III
Trapped between the 2 Volta dams;Receives limited inflow of water; Experiences reduced water flow (speed) in the main channel;Collapsed flood plain agriculture;Weed-choked creeks, streams and main channel limiting extent of fishing;
Stratum VII
Constitutes the most riverine segment of the Volta Lake;Under the influence of large inflows thus, providing large volumes of water and fish; Constitutes the hub of fishery on the Volta Lake;Benefited from a number of national and international interventions aimed at improving livelihoods of households
Sourced from various reports including VBRP, 2008; IAB, 1995; Petr, 1974; Fisheries Department, 1995 and Henle and Eckert, 1970; FAO, 2008.
Third stage –Simple random sampling (using table of random number) of 5 fishingcommunities in each district
Fourth stage - Simple random sampling of respondents from each of the 5 communitiesselected.
Table 2: The list of sampled settlements/communities
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Region District Settlements
Greater Accra Ada East Big Ada, Hawuii, Pediatorkorpe, Alorwusede, Kpetsu Panya;
Brong Ahafo Pru Jaklaye No. 1; Jaklaye No.3, Fantekora, Dzrakraher, Abaiwaya,
Eastern Asuogyaman Akrade, Senchi, Atimpoku, Small London, Adomi
Lower Manya Kpong Zongo, Natriku, Ayipala, Asimekorpe, Ahundjo,
Volta North Tongu Blornu, Fodjoku, Mepe, Klamadoboe, Torgorme,
Central Tongu Duffour, Amedeka, Anagoto, Kamalo, Kewum
South Tongu Sokpoe, Agordome, Tefle, Kpekpo, Anyanui,
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ANALYSIS OF DATA Livelihood Vulnerability Scores from major components:
Livelihood Strategies Socio-demographics Profile Social Networks Food & Water Health; Income shocks and risk Natural Disaster and Climate Variability including rainfall & temperature (Hahn et al, 2009)
To incorporate concerns of climate effects, the IPCC’s Vulnerability Index was also computed(IPCC-LVI) (Hahn et al, ibid);
Multi-criteria Decision Analysis (MCDA) technique (Eakin & Bojorquez-Tapia, 2008; Janssen(1992); Pearce & Turner (1990) was employed to examine proportionality in vulnerability based on15 variables;
Simpson’s Index of Diversity and the Tobit Model
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Major component Sub components Lower Volta
Maxi in sub-component for combined study areas
Mini in sub-component for combined study areas Index for Lower Volta
Value for major components (Lower Volta)
Socio-demographic
profile
Mean dependency ratio 0.87 5 0 0.174
0.127
Percent of Female-headed households 13.79 100 0 0.138
Average age of female-head of households (1/years) 0.023 0.06 0.014 0.196Percent of households where head of household has not attended school 21 100 0 0.210Percent of households with orphans 9.32 100 0 0.093
Average of years of formal education of household head (1/years+1) 0.29 0.53 0.27 0.077Average of years of household heads' involvement in fishery activity (1/years+1) 0.06 0.07 0.06 0.000
Step 1(Repeat for all subcomponents indicator: (0.87 -0)/(5 - 0) = 0.174Step 2(Repeat for all subcomponents indicator: SDP = (0.174+0.138+0.196+0.210+0.093+0.077+0)/7=0.127Step 3 (Repeat for all study areas): LVI = (7*0.127)+(4*0.235)+(5*0.42)+(4*40)+(5*0.137)+(2*0.29)+(5*0.42)+(6*0.103)/39 22
TABLE 3: COMPUTATION OF LIVELIHOOD INDICATOR SCORE OF MAJOR COMPONENTS
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ContributingFactors Major components
Major component values for Lower Volta
Number of sub -components per major component Contributory factor values IPCC LVI
Adaptation Capacity
Socio-demographic profile
0.127 7
0.287
-0.015Livelihood strategies
0.419 5Social networks
0.411 4Sensitivity Health 0.137 5
0.201Food 0.291 2Water 0.235 4
Exposure
Natural Disaster & Climate Variability 0.428 6 0.214
Step 1(Calculate for all subcomponents indicators and major components, take inverse of the adaption capacity sub component indicators - SDP, LS & SN): (7*0.127)+(5*0.419)+(4*0.411)/16 Step 2(Repeat for all contributing factors: exposure, sensitivity & Adaptation capacity)Step 3 (Repeat for all study areas):IPCC LVI = (0.214 - 0.287)*0.201 = -0.015 23
TABLE 4: COMPUTATION OF THE IPCC-LVI INDICATOR SCORE
Decision criteria
The decision criteria Livelihood Indicator Score adopted:
LVI = 0 to 0.22 => household was not vulnerable;LVI = 0.23 to 0.5 implied household was vulnerable.
The IPCC LVI was scaled from -1(least vulnerable) to +1 (most vulnerable).
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MULTI-CRITERIA DECISION ANALYSIS (MCDA)
Socio-demographic: educational status, membership of a fishers association, whether or
not households had at least another member in fishery in addition to the head; whether or
not households had access to: (1) credit; (2) equipped fish landing site; (3) market all year
round and (4) grounds all year round.
Income sources: households were categorized as diversified or not; received remittances
or not; experienced unexpected demand on their income last in 2014 or not;
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Assets: possessed fishery assets or not;
Disaster: experienced destruction of asset due to extreme events in the past 6 years or not;
Ecological factors: improvement or not in water flow rate; weed infestation and the extent of influx of seawater during the past 6 years.
Decision criteria:Each given a score of +1 or -1 if => a factor/constraint to the household.
Scores: [–15] to [-4] = Vulnerable; [3] to [0] = Least exposed to risk; [+1] to [+ 15] = Capable of withstanding risk
Sperling et al. (2008); Eakin and Bojorquez-Tapia (2008).26
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SIMPSON’S INDEX OF DIVERSIFICATION
1 ∑ / / / / / / / / / / / ]Where Ywf = total income of household; Fishinc = income from fishing activities of household i; Foodcrpi = food crop income of the ith household,Cashcrpi = cash crop income of the ith household,Natresi = income from the exploitation of natural resource of the ith
household,27
Livi = income from sale of livestock of the ith household, Farmwagei = farm wage income of the ith household, Fishwagei = wage from fishing activities of the ith household, Selfi = self-employed or professional income of the ith household, Salaryi = salary income of the ith household, Remiti = remittance income of the ith household, Bonusi = bonus and other income of the ith household.
Decision criteria:SID = 0 – 0.22 => specialized,SID = 0.23 - 0.37 => low diversification,SID = 0.38 – 0.63 => medium diversification andSID = 0.64 implied high diversification
Saha and Bahal (2010); Tung Phung and Hermann (2009)28
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Table 5: Livelihood Vulnerability Scores of major components by location
Socidemographic Profile
Livelihood Strategies
Social Network Health Food Water
Natural Disaster &
Climate Variability
Income & Price Risks
Lower Volta I 0.3 0.5 0.77 0.19 0.3 0.38 0.37 0.15
Lower Volta II 0.09 0.44 0.76 0.11 0.33 0.38 0.34 0.08
Lower Volta III 0.13 0.35 0.35 0.12 0.26 0.04 0.31 0.11
Stratum VII 0.48 0.32 0.45 0.17 0.32 0.54 0.45 0.12
Lower Volta (combined) 0.13 0.42 0.4 0.14 0.29 0.24 0.43 0.129
LVI IPCC LVIAdaptation Capacity Sensitivity Exposure
Lower Volta I 0.36 -0.03 0.48 0.28 0.37
Lower Volta II 0.29 -0.01 0.37 0.25 0.34
Lower Volta III 0.2 0.01 0.25 0.12 0.31
Stratum VII 0.35 0.01 0.45 0.33 0.45
Lower Volta (combined) 0.24 0.03 0.29 0.2 0.4330
Table 6: Overall indicators of Livelihood and Adaptation
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Overall, the Livelihood vulnerability scores were of the order: Lower Volta I (0.36) > Stratum VII (0.35) > Lower Volta II (0.29) > Lower Volta III (0.20)
The overall LVI-IPCC scores were of the order: Lower Volta III (0.01) = Stratum VII (0.01) > Lower Volta II (-0.01) > Lower Volta I (-0.03)
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Table 7: Categorization of households with respect to level of Vulnerability
Category (percent)
Number
Vulnerable Least VulnerableCapable of withstanding risks
Study sites
Lower Volta I 71.5 26.7 1.8 165
Lower Volta II 53.0 43.2 3.7 162
Lower Volta III 77.1 21.8 1.1 188
Lower Volta (I+II+III) 67.6 30.0 2.1 516
Stratum VII 21.6 48.7 29.7 199
All 54.9 35.3 9.8 71432
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Table 8: Classification of households based on categories of Simpson's Index of Diversification
Category (percent)
Number
Specialized(0.0 - 0.22)
Low (0.23 - 0.37)
Medium (0.38 - 0.63)
High (0.64 - 1.0)
Study sites
Lower Volta I 34.6 19.4 37.6 8.5 165.0
Lower Volta II 27.2 21.0 45.1 6.8 162.0
Lower Volta III 33.5 18.6 45.7 2.1 188.0
Lower Volta (I+II+III) 31.8 19.6 42.9 5.6 515.0
Stratum VII 55.8 25.1 18.1 1.0 199.0
All 39.0 21.2 36.0 4.3 714.033
Table 9: Estimates of the effects of diversification on the vulnerability of fishing households in the Lower Volta I Study Area Dependent Variable: Livelihood Vulnerability Index (LVI)Independent Variables: Coef. (α) Std. ErrAge -0.0157 0.7311Education (5.0702)* 3.376Depdency ratio -0.2107 1.1672Distmkt 0.4420* 0.248Sid 7.6353** 3.5658Distfish 0.5924** 0.2321Watflo 4.5677** 1.526Weed 2.107 2.0205Swainflux -1.1128 1.5042remit 2.7667 2.1099vfassets (0.0001)* 0.0001finfrstr 3.4294 2.7606Goodness of fit indicators:
Number of observations = 159; F(12, 147) = 18.55; Prob> F 0.0000; Log pseudolikelihood = -562.44353; Pseudo R2 = 0.0374; 1 left-censored observation at LVI<= 0; 629 uncensored observations; 0 right-censored observation.
The marginal effects are defined by the dy/dx values. ***,**,* are significant at 1.0%, 5% and 10% respectively 34
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Table 10: Estimates of the effects of diversification on the vulnerability of fishing households in the Lower Volta Area II Study Area Dependent Variable: Livelihood Vulnerability Index (LVI)Independent Variables: Coef. (α) Std. ErrAge 0.0408 0.0662Education (3.2654)** 1.5783Depdency ratio (0.2445) 0.9692Credit (11.01)*** 1.7531Sid 6.2006 3.2503Distmkt (0.2639)* 0.1344Distfish 0.7021 0.2145Watflo (3.0532)* 1.9578Weed -5.0034 8.2049Swainflux (14.0849)*** 1.9636remit -1.6922 2.4159vfassets 0.0025 0.0005Goodness of fit indicators:
Number of observations = 150; F(12, 138) = 14.20 ; Prob> F 0.0000; Log pseudolikelihood = -542.8299; Pseudo R2 = 0.0361; 1 left-censored observation at LVI<= 4; 149 uncensored observations; 0 right-censored observation.
The marginal effects are defined by the dy/dx values. ***,**,* are significant at 1.0%, 5% and 10% respectively 35
Table 11: Estimates of the effects of diversification on the vulnerability of fishing households in the Lower Volta Area III Study Area Dependent Variable: Livelihood Vulnerability Index (LVI)Independent Variables: Coef. (α) Std. ErrAge 0.1667** 0.0651Education (4.9953)** 2.5021Depdency ratio 1.2977 0.6481Credit (6.7663)** 2.6412Sid 4.5382 3.1597Distmkt 0.0952 0.1085Distfish -0.365 0.3254Watflo 15.1487 2.3211Weed 2.2696 2.6233Finfrstr 1.4088 1.9587remit 2.5662 3.3833vfassets 0.0001 0.0001Goodness of fit indicators:
Number of observations = 168; F(12, 155) = 0 ; Prob> F 0.0000; Log pseudolikelihood = -581.00441; Pseudo R2 = 0.0430;
1 left-censored observation at LVI<= 7; 167 uncensored observations; 0 right-censored observation.
The marginal effects are defined by the dy/dx values. ***,**,* are significant at 1.0%, 5% and 10% respectively 36
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Table 12: Estimates of the effects of diversification on the vulnerability of fishing households in Stratum VII, Volta Lake Dependent Variable: Livelihood Vulnerability Index (LVI)Independent Variables: Coef. (α) Std. ErrAge 0.3932*** 0.0574Education 12.1479*** 1.2583Depdency ratio 3.7051*** 0.5811Dismkt 0.3783 1.8457Sid 6.4244 4.5579Fishbo 3.1342* 1.9061Distfish 2.069*** 0.6827Weed 0.328 2.2528remit 4.6129 5.5648vfassets 0.0002*** 0.0001extension 0.0606 0.2063finfrstr 3.4101 3.4249Goodness of fit indicators:
Number of observations = 151; F(11, 140) = 38.54 ; Prob> F 0.0000; Log pseudolikelihood = -510.5865; Pseudo R2 = 0.1422;
1 left-censored observation at LVI<= 0; 150 uncensored observations; 0 right-censored observation.
The marginal effects are defined by the dy/dx values. ***,**,* are significant at 1.0%, 5% and 10% respectively
37
Table 13: Estimates of the effects of diversification on the vulnerability of fishing households the entire Lower Volta Basin, Ghana Dependent Variable: Livelihood Vulnerability Index (LVI)Independent Variables: Coef. (α) Std. ErrAge 0.118** 0.0378Educ (3.6711)** 1.472Depra 0.7689 0.5026Credit (7.5716)*** 1.0874Sid 4.9074** 1.8634Fishbo 14.0841*** 1.4282Distfish 0.1484 0.139Watflo 1.6882 1.1823Weed 1.4561 1.7101Swainflux -0.3879 1.4746remit 1.672 1.5346vfassets -0.00002 0.0001extension -0.1816 1.9444finfrstr 1.5916 1.8114Goodness of fit indicators:
Number of observations = 479; F(14, 465) = 254.00 ; Prob> F 0.0000; Log pseudolikelihood = -1730.1143; Pseudo R2 = 0.0208;
1 left-censored observation at LVI<= 4; 478 uncensored observations; 0 right-censored observation.
The marginal effects are defined by the dy/dx values. ***,**,* are significant at 1.0%, 5% and 10% respectively38
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CONCLUSIONS
Fishing households in the Volta Basin are vulnerable with respect to 4 specific areas – Social
Network (0.55), Livelihood Strategies (0.41), Natural Disasters & Climate Variability (0.38)
& Water (0.32).
Using the IPCC standard, the households have low Adaptive Capacity (0.34) to withstand
extreme climate events although they were exposed (0.34) and were considerably living in
sensitive environments (0.22).
Majority (54.9 percent) were vulnerable with only (9.8 percent) being capable of withstanding
risks. 39
CONCLUSIONS
Comparisons based on the geographical locations revealed the
lower and upper extremes of the basin as the most vulnerable
with the intervening parts showing relatively low vulnerability.
40
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CONCLUSIONS In terms of income diversification, the majority were within the
low to medium category.
Thirty-nine (39) per cent of the households were specialized
in fishing and a few (4.3 per cent) were highly diversified
with the majority interspersed in between the two extremes; 41
CONCLUSIONS Fishery households in the basin were using livelihood diversification to reduce
their vulnerability.
The factors as revealed by the Tobit regression results included: the age,
education, dependency ratio, access to credit, membership of association;
possession of fishing asset and weed removal from fishing grounds. Other
factors that were important were income diversification and seawater inflow into
the estuary.42
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POLICY RECOMMENDATIONSInterventions needed (Policy):
Water Management practices
Early warning systems & community preparedness for extreme events
Food & Water storage techniques
Livelihood diversification & strengthening social networks
43
POLICY RECOMMENDATIONSInterventions needed (Policy):
Development of capacity of fishing households’ access to credit, provision
of needed infrastructure, cultivation of suitable fish species.
Enforcement of regulations and Management practices to enhance resource
base of the fishery.
44
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