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Agricultural livelihood resilience in the face of recurring droughts: Empirical evidence from northeast Ethiopia
The main purpose of this study was to characterize the livelihood resilience of smallholder farmers in the face of recurring droughts in northeast Ethiopia. The data was collected using a cross-sectional survey of 274 households and five focus group discussions. Principal component analysis and mult...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238691/ https://www.ncbi.nlm.nih.gov/pubmed/37274688 http://dx.doi.org/10.1016/j.heliyon.2023.e16422 |
Sumario: | The main purpose of this study was to characterize the livelihood resilience of smallholder farmers in the face of recurring droughts in northeast Ethiopia. The data was collected using a cross-sectional survey of 274 households and five focus group discussions. Principal component analysis and multiple linear regression models were employed to analyze the data. The Livelihood Resilience Index (LRI), framed on absorptive, adaptive, and transformative capacities, was used to quantify the households’ livelihood resilience. The results indicated that about 57% of the surveyed respondents were non-resilient, while 43% were resilient to different degrees. Abay Tekeze watershed (ATW) livelihood zone exhibits the highest proportion of resilient households (57.4%), while North Wollo highland belg has the lowest proportion (22.7%). The high resilience in ATW was attributed to the relatively lower persistence of droughts, better accessibility in enabling institutions, more access to agricultural inputs, and the training and support given to farmers. The better-off were more resilient (90.9%) than the medium (52.1%) and the poor (34.6%) households. Among the latent dimensions, sensitivity with β value −0.372, climate change and variability (−0.33), and enabling institutions and environments (0.288) showed a significant (p < 0.0001) influence on LRI. This was followed by adaptive capacity and food access (0.249), agricultural practice and technology (0.213), and asset possession (0.19), in respective order. It implies that the absorptive capacity of households showed the leading influence in determining LRI, while adaptive and transformative capacities had nearly similar low effects. Thus, it is recommended that future planning for building livelihood resilience and drought risk interventions in the area should address the levels of resilience identified and the relative importance of each latent dimension indicated. |
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