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dc.contributor.authorMugendi, Daniel N.
dc.contributor.authorMugi-Ngenga, E.W.
dc.contributor.authorMucheru-Muna, M.W.
dc.contributor.authorMugwe, Jayne
dc.contributor.authorNgetich, F.K.
dc.contributor.authorMairura, F.S.
dc.date.accessioned2015-12-17T08:54:25Z
dc.date.available2015-12-17T08:54:25Z
dc.date.issued2015-11
dc.identifier.citationJournal of Rural Studies Volume 43, February 2016, Pages 49–60en_US
dc.identifier.urihttp://hdl.handle.net/123456789/576
dc.descriptiondoi:10.1016/j.jrurstud.2015.11.004en_US
dc.description.abstractClimate 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.isoenen_US
dc.publisherElsevieren_US
dc.subjectSmall-holder farmersen_US
dc.subjectAgricultureen_US
dc.subjectPrincipal component analysisen_US
dc.subjectClimate variabilityen_US
dc.subjectAdaptationen_US
dc.titleHousehold's socio-economic factors influencing the level of adaptation to climate variability in the dry zones of Eastern Kenyaen_US
dc.typeArticleen_US


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