Impacts of Climatic Variability on Wildlife and Livestock Composition and Productivity Index in Maasai Mara Narok County, Kenya
Chege, Mercy Wairimu
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Climatic variability is the spatial and temporal differences or fluctuations in climatic factors that include, total annual precipitation, timing of precipitation events, the amount of rain that falls during a single precipitation event and its duration, total rainfall differences in areas that are geographically similar, temperature averages in a particular season and temperature extremes in a single season. Mara-Serengeti region is a rangeland supporting the most diverse migration of grazing animals. The study looked into impacts of climatic variability on wildlife and livestock species composition and productivity index in the Maasai Mara National Reserve and ten adjacent conservancies. The specific objectives were 1) To examine rainfall and temperature trends on wildlife and livestock numbers in Maasai Mara National Reserve and conservancies, Narok County from 1975 to 2016. 2) To establish the selected livestock and wildlife productivity index using the Prying livestock productivity model.3) To establish the selected livestock and wildlife composition in the study area using the Prying livestock productivity model. Stratified random sampling was applied to determine the sample size of 382 respondents from ten conservancies and 185 respondents from the hospitality sector and government. Questionnaires were distributed randomly within the manyattas. Interviews were conducted on key informants. Prying livestock productivity a species independent bio-economic model was used to assess productivity and composition of the animals which was compared with variations in climatic trends. Landsat images of 1976, 1985, 1995, 2000, 2003, 2013 and 2016 were acquired, analysed and classified for change detection of land cover. Statistical Package of Social Sciences and excel sheets are used for analysis of data. T-tests were used to find out significance difference at a confidence level of 95%. The null hypothesis where wildlife and livestock productivity vary significantly indicated that the FEE of livestock and wildlife grazers and browsers are not significantly different with a P-value of 0.024 and 0.028 respectively. Comparisons in composition of livestock and wildlife yielded a P-value of 0.013, therefore they were not statistically significant. The data was presented in line and bar graphs and tables. Landsat images indicated decreasing grasslands and increasing shrublands, more so from 1976 to 2016 when grasslands decreased from 88% to 75% while shrublands increased from 6% to 18%. In dry years wildlife numbers decreased from1976 and notably 1995 and 2000 when there were droughts and also 2013 and 2016, a contributing factor being the upward trend in temperatures and reduced rainfall, that was also erratic. The results show that Elephants had the lowest productivity with a Feed Energy Efficiency of 0.02 and warthog had the highest, of 0.10, yet Elephants consume large amounts of dry matter. Mixed feeders had the highest productivity with a mean of 0.062, browsers 0.056 and grazers 0.053 Feed Energy Efficiencies. Goats and sheep (Shoats) numbers increased as the wildlife decreased attributed to high percentages of breeding females and controlled management practices in livestock. The study recommends that, drought resistant forage should be encouraged to provide good nutritional feed to livestock and wild animals’ to cope with climate variability, to increase the wildlife and livestock numbers. Number of water points is introduced depending on the total area to cope with dry seasons/droughts. Animal populations and their composition need to be maintained depending on the carrying capacity of the land, to avoid overstocking.