Abstract
This study assessed households’ resilience to climate change-induced shocks in Dinki watershed, northcentral highlands of Ethiopia. The data were collected through a cross-sectional survey conducted on 288 households, three focus group discussions, and 15 key informant interviews. The Climate Resilience Index (CRI) based on the three resilience capacities (absorptive, adaptive and transformative) frame was used to measure households’ resilience to climate change-induced shocks on an agro-ecological unit of analysis. A principal component analysis (PCA) and multiple regression analysis were used to identify determinant factors and indicators to households’ resilience, respectively. Findings indicate that the indexed scores of major components clearly differentiated the study communities in terms of their agro-ecological zones. Specifically, the absorptive capacity (0.495) was the leading contributing factor to resilience followed by adaptive (0.449) and transformative (0.387) capacities. Likewise, the Midland was relatively more resilient with a mean index value of 0.461. Both the PCA and multiple regression analysis indicated that access to and use of livelihood resources, such as farmlands and livestock holdings, diversity of income sources, infrastructure and social capital were determinants of households’ resilience. In general, it might be due to their exposure to recurrent shocks coupled with limited adaptive capacities including underdeveloped public services, poor livelihood diversification practices, among others, the study communities showed minimal resilience capacity with a mean score of 0.44. Thus, in addition to short-term buffering strategies, intervention priority focusing on both adaptive and transformative capacities, particularly focusing on most vulnerable localities and constrained livelihood strategies, would contribute to ensuring long-term resilience in the study communities.
Highlights
The result of the principal component analysis based on the resilience blocks generated four possible components contributing to a cumulative variance of 82.99% using an eigenvalue cutoff of 1.0
income and food access (IFA) on factor 1 was the most important component contributing to resilience; whereas adaptive capacity (AC), access to basic services (ABS) and social capital (SC) were vital components supporting resilience to climate change-induced shocks (Table 2)
Unlike to the Chayanov’s theory of consumption-labor-balance, the results in this study showed that households with large asset holdings have more access to basic households’ capitals and tend to invest more on their farms
Summary
Weather shocks are extreme weather events resulted from deviations in weather or climate variable beyond the usual range of historic patterns [2]. These shocks are short-lived, abrupt, occur very rarely, lasting only from several hours to several days. Weather shocks are noticeable due to their severe impact from the usual weather pattern and cause adverse impacts on humans, infrastructure and ecosystems. Examples include very high (low) temperature, very heavy rainfall, extreme heat, flooding, drying, very high wind speed, etc. Extreme events which last for longer periods (months to years) are termed as extreme climate events [3]
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