Coexistence patterns of sympatric giant pandas (Ailuropoda melanoleuca) and Asiatic black bears (Ursus thibetanus) in Changqing National Nature Reserve, China

Abstract

Similar species may co-occur in sympatry because of the partitioning of habitat use and resources at different spatial and temporal scales. Understanding coexistence patterns of species may contribute to further uncovering the underlying coexistence mechanisms, and ultimately benefit the conservation of threatened species. In this study, camera trapping was used to investigate spatial and temporal activity patterns of sympatric giant pandas (Ailuropoda melanoleuca) and Asiatic black bears (Ursus thibetanus) in Changqing National Nature Reserve in Qinling Mountains, China. Our study obtained 281 independent detections of giant pandas and 185 of Asiatic black bears during 93,606 camera-trap days from April 2014 to October 2017. We performed occupancy modeling and temporal overlap analyses to examine the spatial-temporal relationships between pandas and bears, and results showed that: (1) giant pandas had higher detection probabilities than Asiatic black bears, while having lower occupancy probabilities; (2) Elevation positively predicted giant panda and negatively predicted Asiatic black bear occupancy, understory vegetation type negatively predicted giant panda occupancy, and distance to nearest settlement positively predicted Asiatic black bear occupancy; (3) giant pandas were more active in spring and winter, while Asiatic black bears were more active in summer, and the two species had low spatial overlap with one another throughout the year; (4) both giant pandas and Asiatic black bears showed mainly diurnal activity patterns, and had high temporal overlap with one another in spring and moderate temporal overlap with one another in autumn. Our results provide detailed information of the spatial and temporal ecology of sympatric giant pandas and Asiatic black bears in the Qinling Mountains of China, which could act as a guide to construct conservation priorities as well as design efficient management programs.