LAUSR

Tropical forests and the biodiversity within them are rapidly declining in the face of increasing human populations. Resource management and conservation of endangered species requires an understanding of how species perceive and respond to their environments. Species distribution modeling (SDM) is an appropriate tool for identifying conservation areas of concern and importance. In this study, SDM was used to identify areas of suitable chimpanzee (Pan troglodytes verus) habitat within the Greater Nimba Landscape, Guinea, West Africa. This location was ideal for investigating the effects of landscape structure on habitat suitability due to the topographic variation of the landscape and the Critically Endangered status of the Western chimpanzee. Additionally, this is the only mountainous, long-term chimpanzee study site and little is known about the effects of topography on chimpanzee behavior. Suitable habitat was predicted based on the location of direct and indirect signs of chimpanzee presence and the spatial distribution of 12 biophysical variables within the study area. Model performance was assessed by examining the area under the curve. The overall predictive performance of the model was 0.721. The variables most influencing habitat suitability were the normalized difference vegetation index (37.8%), elevation (27.3%), hierarchical slope position (11.5%), surface brightness (6.6%), and distance to rivers (5.4%). The final model highlighted the isolation and fragmentation of chimpanzee habitat within the Greater Nimba Landscape. Understanding the factors influencing chimpanzee habitat suitability, specifically the biophysical variables considered in this study, will greatly contribute to conservation efforts by providing quantitative habitat information and improving survey efficiency.