A maximum entropy model for predicting wild boar distribution in Spain

摘要: Wild boar (Sus scrofa) populations in many areas of the Palearctic including Iberian Peninsula have grown continuously over last century. This increase has led to numerous different types conflicts due damage these mammals can cause agriculture, problems they create conservation natural areas, and threat pose animal health. In context both wildlife management design health programs for disease control, it is essential know how wild are distributed on a large spatial scale. Given that quantifying distribution species using census techniques virtually impossible case large-scale studies, modeling thus be used instead estimate animals’ distributions, densities, abundances. this study, potential Spain was predicted by integrating data presence environmental variables into MaxEnt approach. We built tested models 100 bootstrapped replicates. For each replicate or simulation, divided two subsets were model fitting (60% data) cross-validation (40% data). The final found accurate with an area under receiver operating characteristic curve (AUC) value 0.79. Six explanatory predicting identified basis percentage their contribution model. exhibited high degree predictive accuracy, which been confirmed its agreement satellite images field surveys.