Examining primate community occurrence patterns in agroforest landscapes using arboreal and terrestrial camera traps

Context Forest-agricultural mosaics are now considered critical for biodiversity. Within these landscapes, the type of land use surrounding remnant forests influences the ability of arboreal non-flying wildlife to travel, disperse and ultimately survive, making arboreal species disproportionally impacted from habitat change. To inform land management strategies we must first understand how wildlife, including arboreal taxa, respond to heterogeneous landscapes. Objectives Here, we examine the occurrence patterns of four arboreal and three semi-terrestrial primate species in response to agroforest landscape characteristics in southern Guinea-Bissau, West Africa. Methods We combine results from arboreal and terrestrial camera traps across Cantanhez National Park (1067 km(2)). We fit occupancy models using anthropogenic and environmental covariates generated via remote sensing and in-situ vegetation surveys. Results Arboreal camera traps (N = 38 locations, 1922 camera trap days) detected all seven primate species, terrestrial camera traps (N = 62 locations, 3113 camera trap days) detected five. Arboreal red colobus (Piliocolobus badius) and semi-terrestrial Guinea baboon (Papio papio) were the only species not detected at all outside forest blocks. Occupancy of semi-terrestrial chimpanzee (Pan troglodytes) increased nearer villages, whereas that of arboreal king colobus (Colobus polykomos) and Demidoff's galago (Galagoides demidoff) decreased. Our models also suggest that semi-arboreal Campbell's monkeys (Cercopithecus campbelli) increase arboreality nearer villages. Conclusions We demonstrate heterogeneous spatial responses amongst primates across the agroforest landscape. The lack of distinct patterns between groups (arboreal vs. semi-terrestrial primates) is likely due to species-specific human-induced anti-predator strategies and hunting preferences. Our results highlight the contribution of arboreal camera traps to community-based landscape-scale studies in anthropogenic environments.