COS 2-10
Abundance and occupancy of Leopard and their prey in Wangqing Leopard Reserve, China
Monday, August 11, 2014: 4:40 PM
302/303, Sacramento Convention Center
Li Zhang, State Key Laboratory of Earth Surface Processes and Resource Ecology & College of Life Sciences, Beijing Normal University, Beijing, China
Yanchao Cheng, State Key Laboratory of Earth Surface Processes and Resource Ecology & College of Life Sciences, Beijing Normal University, Beijing, China
Limin Feng, State Key Laboratory of Earth Surface Processes and Resource Ecology & College of Life Sciences, Beijing Normal University, Beijing, China
Tianming Wang, State Key Laboratory of Earth Surface Processes and Resource Ecology & College of Life Sciences, Beijing Normal University, Beijing, China
Pu Mou, State Key Laboratory of Earth Surface Processes and Resource Ecology & College of Life Sciences, Beijing Normal University, Beijing, China
Jianping Ge, State Key Laboratory of Earth Surface Processes and Resource Ecology & College of Life Sciences, Beijing Normal University, Beijing, China
Background/Question/Methods Large cats, the top predators in many ecosystems, had declined or been extinct during the last century. Accurate assessments of their current status are difficult due to low population density, large home range, and elusiveness of observations. The camera-trapping technique becomes a promising tool for monitoring the animals. Amur leopard (
Panthera pardus orientalis) is one of critically endangered cat, and believed to live only in two separate populations in the southern tip of Russia Fareast and northeast China. Here we reported our preliminary results on a newly discovered Amur leopard population in Northeast China, and it prey densities. An intensive camera-trapping survey for Amur leopard was carried out from July 2013 to November 2013. Total 61 trapping sites were selected to form a network of grids, with each representing a 3.6X3.6 km habitat area. The average trapping time was 135-day, for total 8241 trapping days. Images were labeled and then processed by Capture histories for each species. Rowcliffe’s random encounter model (REM) was used to estimate densities of prey species. Occupancy model was applied to all prey species and leopard. The prey densities were introduced as co-variables in leopard occupancy analysis.
Results/Conclusions During the monitoring period, we obtained 21 leopard images with a trapping rate of 0.25 (100* pictures of animal/days). We totally recorded 30 species including four main leopard prey species: red deer, sika deer, wild boar and roe deer. Since the pictures of sika deer and red deer were less than 10, we applied REM for roe deer 1.9390(±0.68), and wild boar 0.3371(±0.28) only to estimate their densities. The standard-transferred total prey density (measured as number of average roe deer) was 2.46/km2, and this indicate that the area could support 3-6 adult leopards. Occupancy analysis of preys showed diverse spatial patterns for different prey species. However, the occupancy of leopard had a decreasing south-north gradient, which was highly correlated with the standard prey densities across trapping sites. Leopards were intensively observed and several individuals were constantly observed in the survey area. Prey density analysis support that a viable leopard population could have persisted there. Prey density could explain a large portion of variation of leopard occupancy.