Research Article
Barriers to Livelihood Diversification and Welfare Outcomes of Artisanal Fishing Households Along Shiroro and Kainji Dams, Nigeria
Yohanna John Alhassan*
,
Tsukutado Istifnus Isreal,
Cuba James
Issue:
Volume 11, Issue 3, September 2026
Pages:
41-50
Received:
10 March 2026
Accepted:
27 July 2026
Published:
17 August 2026
Abstract: This study examined the barriers to livelihood diversification and welfare outcomes of artisanal fishing households along Shiroro and Kainji dams, Nigeria and welfare outcomes of artisanal fishing households along Shiroro and Kainji dams. A cross-sectional survey of 300 fishers across 50 villages was conducted, with data analyzed using Exploratory Factor Analysis (EFA) and the Simpson Diversification Index (SDI). Economic constraints high cost of fishing gear (72.0%), limited access to credit (72.7%), and inadequate operating capital (71.0%) were the most severe factors affecting livelihoods. Institutional challenges, including limited extension services (52.7%) and inadequate training (49.0%), alongside environmental stressors such as seasonal water-level fluctuations (36.3%) and climate variability (36.3%), also influenced outcomes. EFA identified Economic Welfare (Factor 1), comprising fishing income (0.82), income from other activities (0.79), and household expenditure (0.75), as the most influential determinant of well-being. Access to services (Factor 2), Food Security (Factor 3), and Asset Ownership (Factor 4) further shaped household welfare. Livelihood diversification was high (SDI = 0.955), dominated by arable farming (59.3%), poultry (50.2%), and livestock (45.9%) and supplemented by petty trading, night guarding, and small-scale processing. The study concludes that diversified livelihoods help households mitigate risks from declining fish stocks and environmental variability. Policy interventions promoting financial inclusion, access to affordable inputs, institutional support, and market development are essential for sustaining welfare and fostering resilient artisanal fisheries.
Abstract: This study examined the barriers to livelihood diversification and welfare outcomes of artisanal fishing households along Shiroro and Kainji dams, Nigeria and welfare outcomes of artisanal fishing households along Shiroro and Kainji dams. A cross-sectional survey of 300 fishers across 50 villages was conducted, with data analyzed using Exploratory ...
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Research Article
Biomass Estimation Models for Combretum-Terminalia Woodlands of Western Ethiopia: Implications for Carbon Accounting, Climate-Change Mitigation, and Biodiversity Conservation
Issue:
Volume 11, Issue 3, September 2026
Pages:
51-61
Received:
27 May 2026
Accepted:
16 June 2026
Published:
18 August 2026
Abstract: Biomass models play a crucial role in accurately estimating carbon storage potential of forests and evaluate the contribution of forest ecosystem services. However, an allometric model which is specifically tailored to diverse tree species in Ethiopia is currently lacking. Therefore, establishing species-specific allometric models and determining the biomass expansion factor for dry woodland ecosystems is essential for comprehending the role in mitigating climate change impacts. This study tested and validated diffrent allometric models on six dominant tree species in the Combretum-Terminalia woodlands of the Benishangul-Gumuz region, which collectively account for approximately 69% of the total basal area. The study applied an explanatory research design method and data were collected through systematic sampling across 40 plots, involving the destructive sampling of 67 representative standing trees. The Allometric models were developed and tested using log-transformed data to satisfy the assumptions of linear regression and ensure statistical rigor. This is done by applying log-transformed data to develop the models to ensure high statistical accuracy. The models performance was validated using key metrics such as R2, RMSE, and Model Efficiency (EF) to ensure the reliability of the carbon storage and biomass estimations. The study demonstrated that aboveground biomass for all six species is highly predictable using species-specific allometric equations with coefficients of determination (R2) consistently exceeding 96%. The DBH-based model (M1) was the best fit for five species, notably achieving the highest R2 (0.985) for Terminalia laxiflora and the most stable performance for Lonchocarpus fruticosa (EF = 0.953). In contrast, Syzygium guineense required the inclusion of height (M2) to reach the study's highest precision (EF = 0.992, MAPE = 3.42%), while Combretum hartmannianum showed the greatest individual variability (EF = 69%). Biomass Expansion Factors (BEF) were statistically uniform across all taxa (P = 0.482), with a collective mean of 2.077 ± 0.343. These findings conclude that while DBH is a robust primary predictor for most woodland species, species-specific architecture particularly the vertical growth of Syzygium guineense and the high absolute residuals in Pterocarpus lucens necessitates tailored models and correction factors to ensure accurate regional carbon accounting and forest management in the Combretum-Terminalia woodlands. Utilizing these models (M1 & M2) can enhance the accuracy of biomass estimations, leading to more effective management practices and conservation strategies via biomass and carbon estimation.
Abstract: Biomass models play a crucial role in accurately estimating carbon storage potential of forests and evaluate the contribution of forest ecosystem services. However, an allometric model which is specifically tailored to diverse tree species in Ethiopia is currently lacking. Therefore, establishing species-specific allometric models and determining t...
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