生物多样性 ›› 2014, Vol. 22 ›› Issue (6): 725-732.DOI: 10.3724/SP.J.1003.2014.14079

所属专题: 野生动物的红外相机监测

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探讨基于红外相机技术对大型猫科动物及其猎物的种群评估方法

李治霖1, 康霭黎2, 郎建民3, 薛延刚3, 任毅2, 朱志文2, 马建章1, 刘培琦2,,A;*(), 姜广顺1,,A;*()   

  1. 1 .东北林业大学野生动物资源学院, 国家林业局猫科动物研究中心, 哈尔滨 150040
    2 .国际野生生物保护学会(WCS)中国项目, 北京 100080
    3 .吉林珲春东北虎国家级自然保护区管理局, 吉林珲春 133300
  • 收稿日期:2014-04-14 接受日期:2014-10-08 出版日期:2014-11-20 发布日期:2014-12-11
  • 通讯作者: 刘培琦,姜广顺
  • 基金资助:
    国家自然科学基金(31272336)、国家基金委专项基金(L1322010)和WCS中国项目

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

摘要:

红外相机技术的发展促进了对东北虎(Panthera tigris altaica)、东北豹(Panthera pardus orientalis)及其猎物种群的研究。本研究以珲春保护区春化和马滴达两个区域的监测结果为例, 介绍利用该技术对我国长白山区东北虎、东北豹及其猎物的种群评估方法, 包括监测位点的选择、相机的架设方式及参数设置、数据筛选、东北虎和东北豹体侧花纹个体识别方法、物种相对丰富度的计算以及捕食者与猎物丰富度关系模型的构建。最后就东北虎、东北豹体侧花纹个体识别技术的适用性、红外相机监测与传统调查方法的差异, 相机监测的误差进行了讨论。研究表明, 利用红外相机技术进行密度预测以及东北虎、东北豹个体自动识别技术还需继续完善。1对/25 km2的相机架设密度基本上满足对于珲春保护区春化至马滴达区域虎豹的监测强度要求, 但对于有蹄类则需要另外的监测方案。

关键词: 广义可加模型, 个体识别, 相对丰富度指数, 误差分析, 种群评估

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