%A Xuehua Liu, Yuke Zhang, Xiangyu Zhao, Xiangbo He, Qiong Cai, Yun Zhu, Baisuo He, Qiang Jiu %T Introduction to the wildlife camera-trapping database of the middle Qinling Mountains %0 Journal Article %D 2020 %J Biodiv Sci %R 10.17520/biods.2020094 %P 1075-1080 %V 28 %N 9 %U {https://www.biodiversity-science.net/CN/abstract/article_61075.shtml} %8 2020-09-20 %X

The Qinling Mountains, which are located in the midwestern part of China, are biogeographically important because they are home to China’s four national wildlife treasures, i.e., giant panda (Ailuropoda melanoleuca), golden takin (Budorcas bedfordi), golden monkey (Rhinopithecus roxellana) and crested ibis (Nipponia nippon). These species are also called the four flagship species in the Qinling forest ecosystem. Therefore, using infrared camera trapping to monitor the wildlife in the Qinling Mountains is very important since it can provide information of species and also scientific data on wildlife behaviour and activity pattern. The ecological research team from Tsinghua University conducted camera trappings between 2009 and 2020 in the Qinling Mountains for seven projects. These projects monitored wildlife diversity, primarily in four nature reserves, covering an area of 1,113 km 2 (26.5 km × 42 km). There were a total of 267 camera-trapping sites. For the 152,160 camera working days, we were able to obtain totally 855,260 photos. From these photos we identified 27 mammal species and 63 bird species, and were able to address several research aspects including: wildlife behavior, identifying rare species, understanding habitat use and adaption, and understanding the human impacts on wildlife. Based on the gathered photos, we established the wildlife camera-trapping database of the middle Qinling Mountains, which has only been shared within the research group and collaborators. Based on our results from 10 years of monitoring, we propose the following suggestions for future research: (1) We need much longer time and we need to implement camera trapping in more habitat types to collect more digital images to be able to monitor the status of animal species rarely seen in front of cameras. For example, Mustela kathiah, Lutra lutra, and Catopuma temminckii were each captured only once in 10-year monitoring. (2) More deep data mining work is necessary in using this database to understand species-species relationships, species-habitat relationships, and population dynamics. (3) Continual research on the population dynamics of species with large populations (like Budorcas bedfordi and Sus scrofa) and carnivores species at the top of food chain (like Panthera pardus) is able to provide scientific support to the whole Qinling ecosystem. (4) Mining this photo database to monitor and research wildlife disease’s occurring as well as developing.