Species distributions are influenced by both climate conditions and landscape structure. Here we propose an integrated analysis of climatic and landscape niche-based models for a forest-dependent primate, the endangered black lion tamarin (Leontopithecus chrysopygus). We applied both climate and landscape variables to predict the distribution of this tamarin and used this information to prioritize strategic areas more accurately. We anticipated that this approach would be beneficial for the selection of pertinent conservation strategies for this flagship species. First, we built climate and landscape niche-based models separately, combining seven algorithms, to infer processes acting on the species distribution at different scales. Subsequently, we combined climate and landscape models using the EcoLand Analysis. Our results suggest that historic and current landscape fragmentation and modification had profoundly adverse effects on the distribution of the black lion tamarins. The models indicated just 2096 km (out of an original distribution of 92,239 km ) of suitable areas for both climate and landscape. Of this suitable area, the species is currently present in less than 40%, which represents less than 1% of its original distribution. Based on the combined map, we determined the western and southeast regions of the species range to be priority areas for its conservation. We identified areas with high climatic and high landscape suitability, which overlap with the remaining forest fragments in both regions, for habitat conservation and population management. We suggest that areas with high climatic but low landscape suitability should be prioritized for habitat management and restoration. Areas with high landscape suitability and low climatic suitability, such as the Paranapiacaba mountain range should be considered in light of projected climate change scenarios. Our case study illustrates that a combined approach of climatic and landscape niche-based modeling can be useful for establishing focused conservation measures that may increase the likelihood of success.
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