The Adaptive Capacity Index of Smallholder Farmers to Climate Related Shocks in Kinakomba Ward, Tana River County, Kenya

Peter Ndegwa, Andrew W. Wamukota, Annie H. Ong’ayo


According to IPCC (2014) Adaptive capacity is the ability of systems, institutions, humans and other organisms to adjust to potential damage, take advantage of opportunities and respond to consequences arising. In a climate change context it relates to inter-relationship of social, political, economic, technological and institutional factors operating at a variety of scales Vincent, Katharine (2007) some genetic while others exposure specific. This study analyzed the adaptive capacity to climate related shocks of 390 farming households in Kinakomba Ward. The objective was: To determine the adaptive capacity index of the smallholder farmers in Kinakomba Ward. The index included five indicators of human resources, physical resources, financial resources, information and livelihoods diversity (Eakin and Bojorquez-Tapia 2008). The researcher used two methods to analyse adaptive capacity: Firstly an interview with 390 farming households to gather data on farming and household characteristics and Natural resources availability and secondly a panel of 15 Key Informants provided ratings of indicators of adaptive capacity using analytic hierarchy process (AHP). Using the Analytic Hierarchy Process (AHP) the results indicated that Livelihoods Diversity had the highest adaptive capacity score at 0.3 while the lowest adaptive capacity for Criterion was information at 0.12. Meaning that Livelihoods diversity was 3 times more preferred than information. The panel of key informants gave this alternative the highest weight and so this was the single adaptive capacity for Kinakomba ward. The results further revealed that occupational multiplicity had the highest score at 0.21 the panel of the key informants gave this indicator a high rating thus making it have the highest adaptive capacity while the lowest was given to infrastructure at 0.03, meaning occupational multiplicity at 0.21was 6 times more preferred to infrastructure at 0.03. The study concluded that When the Number of livelihoods sources are many and when the number of members in the household are also having different sources of livelihoods, then that household has a high adaptive capacity. Consequently when all the members of the households are adults and each has a job then the adaptive capacity of that household is high while a high dependency ratio leads to low adaptive capacity. The study recommended that the County and National governments and stakeholders to employ measures to adapt to climate change and variability.

Keywords; Analytic Hierarchy process(AHP), Adaptive Capacity, Key informants, Analytical Network Process (ANP) software, Super Decisions version 3.0

DOI: 10.7176/FSQM/95-07

Publication date:March 31st 2020

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ISSN (Paper)2224-6088 ISSN (Online)2225-0557

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