Determinants of climate change adaptation and perceptions among small-scale farmers of Embu County, Eastern Kenya

Climate change threatens the livelihoods of millions of small-scale farmers in East Africa. How farmers perceive climate change and its impacts has a strong bearing on how they adapt to the adverse impacts. This paper focused on factors that determine climate change adaptation and perceptions among small-scale farmers of Embu County. A survey was carried out across five sub-counties of Embu County where a multi-stage sampling procedure was used to select 411 households. A questionnaire was administered to each household. A total of five FGDs were generated by the use of quota sampling. The data obtained from the FGDs were thematically analyzed while that from each household was subjected to both descriptive statistics and Heckman's probit model. The results showed 96% of the respondents observed unreliable seasonal rainfall amount, distribution, and increased temperatures. For instance, 23% interviewed were aware of the long-term change in temperature while 55% were aware of a change in the amount of rainfall per season. These respondents identified crop failure and the decline in crop yields as indicators of climate change. The farmers’ perceptions were corroborated by the long-term rainfall and temperature of Mann-Kendall trends analysis, which showed a negative rainfall correlation and temperatures increased by 0.02°C for Kiambere and 0.03°C for Embu stations. Gender was significant at p<0.1 in influencing farmers' perception of climate change while education level and social networks were statistically significant at p<0.05. Furthermore, Heckman's selectivity probit model showed that the education level of the household head and access to a credit facility influenced small-scale farmers' adaptation choices. There is a need to strengthen the capacities of farmers through training, provision of extension services, and formulation of a climate advisory committee within the county government to breakdown climate change information into user-friendly.   Key words: Heckman model, climate variability.