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Understanding the linkages between the biogeophysical and socio-economic processes that operate at different spatial and temporal scales is important for land cover change mitigation. This study analysed several factors that explained the forest-shrubland conversions, grassland conversions and cropland expansions in Lake Nakuru drainage basin and Eastern Mau forest reserve in Kenya from 1985 to 2011. Logistic regression models were developed using a combination of remote sensing-based land cover data, and geographical information systems-based geophysical and socio-economic data (i.e., temperature, rainfall, elevation, slope, aspect, topographic wetness, curvature, soil pH, soil cation exchange capacity (CEC), population density and distance to road, river and town). The results were varied; for example, in the period 1985–2000, forest-shrubland conversions were linked to distance to road), distance to town, soil pH, soil CEC, rainfall, topographic wetness, curvature and aspect. The same factors, in addition to slope and distance to river, also determined the likelihood of forest-shrubland conversions in the period 2000–2011. Overall, significance of the determining factors varied depending on time and nature of land cover change. For example, topographical factors influenced grassland conversions in the period 1985–2000, while soil-related factors did not. But in the period 2000–2011, the converse was true. Therefore, policies for restoration, conservation and sustainable management of critical ecosystems (e.g., forests) should be spatially targeted and time-specific. These results broaden our knowledge of land cover dynamics in this locality, and provide a base for effective environmental policy formulation, planning and management.
