Farmers’ Perceptions on the Effects of Climate Variability on Dairy Farming in Masaba North, Nyamira County, Kenya
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Climate variability is an emerging phenomenon that is threatening dairy farming globally. The dairy-climate change dilemma in Kenya cannot be mistaken. However, extensive research into dairy farming and an understanding of the dynamics of climate variability effects is greatly lacking.The study investigated the effects of climate variability on dairy farming in Masaba North Sub-county of Nyamira County, Kenya. The main objective was to determine the effects of climate variability on dairy production in the study area. During the study two sampling techniques were used; purposive and systematic sampling that captured key informants and household information respectively with a targeted sample size of 100 respondents. Further, the findings obtained were analyzed through Statistical Package of Social Sciences and Excel. Data was presented in tables, graphs and pie charts. From the results, a hypothesis was tested using Chi-Square (X2). The null hypothesis on effect of milk production was accepted where, (X2 = 0.087, DF =2, P = 0.001). At least 93% of dairy farmers had basic primary education during the study. The farmers’ perceptions on climate variability were set on the Likert scale to determine their magnitudes through total weights. The findings showed that temperature had rose by at least +0.50 C in the past 35 years with anomalies of rainfall across the years indicating variability effect in the area. Heat stress affected animal performance with 67% dairy farmers’ views hypothetically accepted. 89% of respondents stated that seasons had changed and were unpredictable. From the study, 42% of farmers used crossbreeding to improve animal performance a way of mitigating climate change. The integral recommendations were; improve dairy cattle performance through adoption of modern livestock techniques, growing of fast vegetating fodder crops and harnessing immediate farmers’ education to mitigate climate variability effects.