Integrating Indigenous and Conventional knowledge-based climate forecast for farmers’ enhanced adaptation to climate variability in Tharaka-Nithi and Kitui Counties
| dc.contributor.author | Mugi, Esther Wangeci | |
| dc.date.accessioned | 2014-09-04T12:44:35Z | |
| dc.date.available | 2014-09-04T12:44:35Z | |
| dc.date.issued | 2014-09-04 | |
| dc.description | Master of Environmental Studies (Agroforestry and Rural Development), School of Environmental Studies. 97p. June , 2014 | en_US |
| dc.description.abstract | Climate variability has a negative impact on crop productivity and has affected many small-holder farmers in the arid and semi-arid lands (ASALs). Small-holder farmers in the study area are faced with the constraint of climate variability and have consequently made effort at the local level to utilize indigenous knowledge (IK) in addition to conventional knowledge to mitigate the impacts of the variability. However, documentation of the IK indicators is limited. This study was therefore undertaken with the aim of identifying the IK and preparedness techniques employed in coping with climate variability by small-holder farmers, integrate the indigenous and conventional knowledge of climate forecasting and assess how the household’s socio-economic factors influence the level of adaptation to climate variability. The study was conducted in Tharaka and Kitui-Central Sub-Counties in Tharaka-Nithi and Kitui counties, respectively and used both primary and secondary data. Data collected included: (i) Indigenous and conventional knowledge of climate forecasting employed by small holder farmers, (ii) Household demographic and socio-economic characteristics, (iii) Farmers’ adaptation strategies to cope with climate variability, (iv) Rainfall and temperature data from Kenya Meteorological Department (KMD). Research design involved a triangulation approach to simultaneously collect both quantitative and qualitative data. Primary data was specifically gathered through the use of a survey. Sampling strategy involved random sampling and also a purposive sampling in combination with snow balling technique. Data was analyzed using descriptive statistics, multinomial and binary logistic regression, using variables produced through Principal Component Analysis (PCA). Results showed that there were significant differences in the use of indigenous strategies such as change in the sky (2=14.631), moon (2=7.851) and wind (2=5.864) at p<0.05 in the two sub-counties. Majority (87%) of the farmers used change in the colour of trees’ leaves as an indigenous strategy in weather forecasting. Results from the analysis of conventional data (rainfall and temperature) were found to conform to the information from small-holder farmers’ perception on how climate has varied over the reference period. The study considered five strategies as measures of level of adaptation to climate variability; crop adjustment; crop management; soil fertility management; water harvesting and crop types; boreholes and crop variety factors. 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 were found significant (p<0.05) in predicting the level of adaptation to climate variability as being either low or medium relative to high. This study concludes that IK of weather forecasting is still in use today hence, effort should be put in place to document the indicators that are used in combination with conventional knowledge for use in future by small scale farmers. Furthermore, effort should be put in place to integrate the IK and the conventional knowledge. In addition, household socio economic factors that explain the level of adaptation should be considered in any efforts that aim to promote adaptation to climate variability in the agricultural sector among the smallholder farmers | en_US |
| dc.description.sponsorship | Kenyatta University | en_US |
| dc.identifier.uri | http://ir-library.ku.ac.ke/handle/123456789/11163 | |
| dc.language.iso | en | en_US |
| dc.title | Integrating Indigenous and Conventional knowledge-based climate forecast for farmers’ enhanced adaptation to climate variability in Tharaka-Nithi and Kitui Counties | en_US |
| dc.type | Thesis | en_US |
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