Applying species distribution modelling to the conservation of an ecologically plastic species (Papio papio) across biogeographic regions in West Africa

Ecological niche models are valuable tools to support conservation decision-making. Still, they are sensitive to the study area spatial extent. Ecologically plastic species ranging over different biogeographic regions often exhibit populations adapted to distinct environmental conditions. In such cases, regional models may be more accurate than global models in discriminating suitable areas in specific regions under such circumstances. We use the Guinea baboon as model system, to test the effects of restricting the range of environmental variables and study area extent, and explore geographic differences in the environmental conditions occupied by ecologically plastic species. Additionally, we explore conservation implications for this particular case study. We built global (West Africa) and regional models (Sahel, Savannah and Afrotropical) using a maximum entropy approach and explore geographic differences in environmental conditions occupied by regional populations using Principal Components Analyses. The most important variables identified differed between model types, distance to gueltas in global model and distances to gueltas, to croplands and to water bodies in regional models, as well as models' accuracy to define distribution and suitable areas, which are overestimated by global models. Environmental conditions overlapped slightly between regional populations, and the Sahel displayed the most divergent one. Areas of potential conflict between the species and humans were identified in the Savannah and Afrotropical region, but latter lack protected areas. We show for modelling the current distribution of ecologically plastic species, regional models are more accurate than global models in defining the species' environmental predictors and suitable areas. This will improve the definition of accurate local suitable areas for ecologically plastic species and improve the allocation of resources for local conservation actions.