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Household's socio-economic factors influencing the level of adaptation to climate variability in the dry zones of Eastern Kenya

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dc.contributor.author Mugendi, Daniel N.
dc.contributor.author Mugi-Ngenga, E.W.
dc.contributor.author Mucheru-Muna, M.W.
dc.contributor.author Mugwe, Jayne
dc.contributor.author Ngetich, F.K.
dc.contributor.author Mairura, F.S.
dc.date.accessioned 2015-12-17T08:54:25Z
dc.date.available 2015-12-17T08:54:25Z
dc.date.issued 2015-11
dc.identifier.citation Journal of Rural Studies Volume 43, February 2016, Pages 49–60 en_US
dc.identifier.uri http://hdl.handle.net/123456789/576
dc.description doi:10.1016/j.jrurstud.2015.11.004 en_US
dc.description.abstract Climate variability has a negative impact on crop productivity and has had an effect on many small-holder farmers in the arid and semi-arid lands (ASALs). Small-holder farmers in Eastern Kenya are faced with the constraint associated with climate variability and have consequently made effort at local level to utilize adaptation techniques in their quest to adapt to climate variability. However, documentation of the factors that influence the level of adaptation to climate variability in the study area is quite limited. Hence, this study aimed at assessing how the household's socio-economic factors influence the level of adaptation to climate variability. The study sites were Tharaka and Kitui-Central sub-Counties in Tharaka-Nithi and Kitui Counties of Eastern Kenya respectively. The data collected included the household demographic and socio-economic characteristics and farmers' adaptation techniques to cope with climate variability. Triangulation approach research design was used to simultaneously collect both quantitative and qualitative data. Primary data was gathered through a household survey. Both random and purposive sampling strategies were employed. Data analysis was done using descriptive and inferential statistics. Multinomial and Binary logistic regression models were used to predict the influence of socioeconomic characteristics on the level of adaptation to climate variability. This was done using variables derived through a data reduction process that employed Principal Component Analysis (PCA). The study considered five strategies as measures of the level of adaptation to climate variability; crop adjustment; crop management; soil fertility management; water harvesting and crop types; boreholes and crop variety. Several factors were found significant in predicting the level of adaptation to climate variability as being either low or medium relative to high. These were average size of land under maize; farming experience; household size; household members involved in farming; education level; age; main occupation and gender of the household head. Household socio economic factors found significant in explaining the level of adaptation should be considered in any efforts that aim to promote adaptation to climate variability in the agricultural sector amongst smallholder farmers. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.subject Small-holder farmers en_US
dc.subject Agriculture en_US
dc.subject Principal component analysis en_US
dc.subject Climate variability en_US
dc.subject Adaptation en_US
dc.title Household's socio-economic factors influencing the level of adaptation to climate variability in the dry zones of Eastern Kenya en_US
dc.type Article en_US


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