Agro-ecosystems’ Vulnerability to Climate Change in Drought Prone Areas of Northeastern Ethiopia

Endalew Addis

Abstract


Agro-ecosystem level evidence is crucial to design and formulate climate change adaptation policies so as to build climate resilient communities. However, agro-ecosystems’ vulnerability to climate change studies are not available in drought prone areas of northeastern Ethiopia. On the other hand, these drought prone agro-ecosystems which depend mainly on rain fed agriculture and pastoral/agro-pastoral ways of life are intermittently vulnerable to climate variability and change. Hence, the objective of this study is to examine agro-ecosystems vulnerability to climate change in drought prone areas of northeastern Ethiopia focusing on Kobo and Golina districts in Amhara and Afar regions respectively. Accordingly, data was gathered from secondary sources (station data from National Meteorological Agency), observation, key informant interviews, focus group discussions, and household survey in highland mixed farming, lowland mixed farming, agro-pastoral, and pastoral agro-ecosystems. Consequently, quantitative data analyzed by SPSS and STATA software whereas qualitative information analyzed by content analysis. More specifically, principal component analysis (PCA) model used to perform quantitative analysis to calculate adaptive capacity, sensitivity, exposure and vulnerability indexes of highland mixed farming, lowland mixed farming, agro-pastoral, and pastoral agro-ecosystems. The findings have shown that while lowland mixed farming is less vulnerable since it is the most adaptive and the least exposed compared to others, agro-pastoral agro-ecosystem is most vulnerable because it is the least adaptive and the highly exposed when compared to others. Hence, it is recommended that the adaptive capacity of agro-ecosystems should be improved as it reduces the sensitivity and finally the overall vulnerability.

Keywords: agro-ecosystem, climate change, vulnerability, drought-prone, principal component analysis

 


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ISSN (Paper)2224-3186 ISSN (Online)2225-0921

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