Using large spatial scale camera trap data and hierarchical occupancy models to evaluate species richness and occupancy of rare and elusive wildlife communities in southwest China

AIM: Owing to the broad use of camera traps, integration and standardization among camera trap studies has become key to maximizing their utility for local and global biodiversity conservation. Our goal was to introduce the use of a hierarchical modelling framework in the context of coordinated biodiversity monitoring to compare species richness and occupancy by integrating camera trap data from multiple study areas. LOCATION: Southwest China. METHODS: We used hierarchical occupancy models to integrate camera trap data for elusive mammal and pheasant communities from three study areas representing different habitat types: alpine and subalpine zones, dry‐hot valleys and subtropical montane forests. We evaluate the responses of species occurrence to human influence and habitat parameters based on a Bayesian approach. RESULTS: We captured photographs of 23 mammal and 7 pheasant species over 10,095 trap nights. The model revealed that the alpine and subalpine zones supported the highest species richness of the target communities among the three habitat types. Surprisingly, dry‐hot valleys supported similar levels of species richness to subtropical montane forest. Species richness showed a similar bell‐shaped relationship with elevation, with the richness curve peaking at intermediate elevations at about 3500 m above sea level (asl). Posterior distributions for community‐level hyper‐parameters indicated the consistent and negative effects of human disturbance on species occupancy. The community model also revealed a strong quadratic relationship between elevation and occupancy, with the highest occupancy occurring at about 3700 m asl. MAIN CONCLUSION: Using hierarchical occupancy models for integrating camera trap data from multiple study areas, we show that alpine/subalpine zone and dry‐hot valleys have the highest richness and should be given more priority for conservation of biodiversity in southwest China. We recommend broader application of the hierarchical occupancy modelling approach to camera trap data to obtain more comprehensive insights relevant to regional biodiversity conservation.