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Land Cover Change and Its Socio-Economic Impact on the Residents of the Mara River, Kenya

DOI: 10.4236/ajcc.2019.83022, PP. 404-438

Keywords: Land Cover Change, Socio-Economic Impact, Mara River Sub-Catchments, Kenya

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Abstract:

Anthropogenic activities are increasingly catalyzing natural climatic factors that drive land cover change at different spatial scales. Available land cover data of the Mara River basin however give a broader picture of the entire basin regardless of the heterogeneity that exists at the sub-catchment level. This study sought to establish sub-catchment specific information on land cover changes through examination of satellite images of four Mara River sub-catchments (Amala, Nyangores, Talek and Sand River) for the period 1987-2017. The relationship between temperature, rainfall and land cover was also computed. In addition, a household survey and focus group discussions were conducted in each sub-catchments to establish the socio-economic impacts of land cover change on the community’s wellbeing. Forest cover was dominant in Amala (39.8%) and Nyangores (43.7%) sub-catchments in 1987 but by 2017 crop lands had surpassed forest cover in the two sub-catchments, accounting for 53.2% and 45.7%, respectively. However, in Talek (52.8%) and Sand River (47.4%) sub-catchments, grassland was the dominant land cover type in 1987 and after the 30 year period, grasslands remained dominant in Sand River, while shrub land became dominant in Talek sub-catchment. A weak positive correlation was observed between rainfall and forest cover, shrub land and cropland, while a negative correlation was observed between rainfall and bare land. Average temperature showed a positive moderate correlation with bare land and built up areas. Analysis of survey data revealed that livestock keeping, temperature increase, type of trees, education level of household head and weak environmental laws were the main drivers of land cover change (P < 0.05), while decline in forest cover, crop failure and shift in planting seasons were attributed to climate change. Pearson correlation of annual precipitation against crop yield for the period 1987-2017 revealed negative correlations for maize (r = ?0.587), beans (r = ?0.5459), sorghum (r = ?0.351), cow peas (r = ?0.544), and pigeon peas (r = ?0.337). Focus group discussions participants were supportive of environmental protective measures to reverse negative land cover changes, while planting drought resistant trees, crop diversification and awareness creation among community members were recommended as the most ideal environmental

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