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Spatially explicit models are becoming increasingly important tools for simulating land-use change. In this study, we formulated and tested models that incorporated spatial correlates of agricultural expansion and used them to predict local- and landscape-scale patterns of agricultural land-use change and its implications in the Maasai-Steppe of Northern Tanzania. We evaluated the relationship between agricultural land-use and its spatial correlates using Multiple Logistic Regression on data derived from satellite imageries for the year 2000. We then examined the implications of the agricultural land-use change on the range and migratory corridors of key migratory wildlife species within the context of wildlife conservation and land-use planning. Our results showed that, biophysical variables provide the primary conditions for land-cover conversions to agriculture. There was a strong overlap between lands suitable for agriculture, wildlife migratory corridors and the wet season dispersal areas. Expanding cultivation towards protected areas severely restricted wildlife movements to dispersal areas outside parks by blocking their migratory corridors. Further, the global model used for the prediction of probability of land-conversions to agriculture suggested future expansions will be constrained by values of the biophysical variables analysed here. The rapidity of rangeland conversions to farming in the study area presents a major threat to wildlife conservation and disrupts the ecosystems viability in supporting its rich biodiversity and the agro-pastoral livelihood. There is urgency for pursuing land-use strategies and plans, which are both profitable and sustainable for the agro-pastoral communities and the wildlife. The plans should address the different land-use options by considering current and future trends, implications and the ease for their cohabitation as analysed in this study.
