Biodiv Sci ›› 2014, Vol. 22 ›› Issue (6): 725-732.DOI: 10.3724/SP.J.1003.2014.14079

Special Issue: 野生动物的红外相机监测

• Orginal Article • Previous Articles     Next Articles

On the assessment of big cats and their prey populations based on camera trap data

Zhilin Li1, Aili Kang2, Jianmin Lang3, Yangang Xue3, Yi Ren2, Zhiwen Zhu2, Jianzhang Ma1, Peiqi Liu2,*(), Guangshun Jiang1,*()   

  1. 1. College of Wildlife Resources, Northeast Forestry University; The Feline Research Center of State Forestry Administra- tion, Harbin 150040
    2 .Wildlife Conservation Society (WCS), China Program, Beijing 100080
    3 .Jilin Hunchun Amur Tiger National Nature Reserve Administration, Hunchun, Jilin 133300;
  • Received:2014-04-14 Accepted:2014-10-08 Online:2014-11-20 Published:2014-12-11
  • Contact: Liu Peiqi,Jiang Guangshun

Abstract:

The development of camera traps has improved our ability to study Amur tigers (Panthera tigris altaica), Amur leopards (Panthera pardus orientalis) and their prey populations. This research introduces camera trap monitoring methods of Amur tigers, Amur leopards and their prey populations in Chunhua and Madida areas of the Hunchun Nature Reserve, Changbai Mountains, China. A selection of monitoring positions, methods of erecting, parameter settings, and data filtering techniques are presented. Additionally, unique identifiers of Amur tigers and Amur leopards based on body patterns, calculations of relative abundance indexes (RAI), and the establishment of RAI models between the predators and prey are presented. We discuss the applicability of unique identifiers with ipsilateral patterns, the differences between camera trap monitoring and traditional survey methods, and the error of camera trap monitoring. We conclude that predicting densities of Amur tigers and Amur leopards with camera traps and automatic-individual-identifiers still needs improvement. Camera trap densities of one pair per 25 km2 can meet the needs for Amur tigers and leopards within Chunhua and Madida of the Hunchun Nature Reserve, but a separate monitoring project is needed for ungulates prey.

Key words: generalized additive models, individual identify, relative abundance index, error analysis, population evaluation