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林业科学 ›› 2019, Vol. 55 ›› Issue (5): 188-196.doi: 10.11707/j.1001-7488.20190521

• 研究简报 • 上一篇    

基于红外相机监测的汪清自然保护区东北豹种群动态

孔维尧1,2, 孙权3, 刘鑫鑫2, 曲丽3, 王福友3, 姚明远2, 邹红菲1   

  1. 1. 东北林业大学野生动物资源学院 哈尔滨 150040;
    2. 吉林省林业科学研究院长白山动物资源与生物多样性吉林省重点实验室 长春 130033;
    3. 东北虎豹国家公园管理局汪清分局 汪清国家级自然保护区管理局 汪清 133200
  • 收稿日期:2018-10-07 修回日期:2019-03-12 出版日期:2019-05-25 发布日期:2019-05-20
  • 基金资助:
    吉林省财政公益项目(GY-2017-08);GEF/WB项目(P122383);WWF项目(10000766);吉林省重点实验室项目(20170622017JC)。

Population Dynamic of Far Eastern Leopard(Panthera pardus orientalis) in Wangqing Nature Reserve Based on Infrared Camera Monitoring

Kong Weiyao1,2, Sun Quan3, Liu Xinxin2, Qu Li3, Wang Fuyou3, Yao Mingyuan2, Zou Hongfei1   

  1. 1. Wildlife Resource College, Northeast Forestry University Harbin 150040;
    2. Jilin Provincial Academy of Forestry Science Jilin Provincial Key Laboratory of Wildlife and Biodiversity in Changbai Mountain Changchun 130033;
    3. Northeast Tiger and Leopard National Park Administration Wangqing Suboffice Wangqing National Nature Reserve Administration Wangqing 133200
  • Received:2018-10-07 Revised:2019-03-12 Online:2019-05-25 Published:2019-05-20

摘要: [目的]东北豹是分布最北、种群数量最小的豹亚种,濒危等级为"极危"。分析采用相机监测技术得到的汪清保护区内东北豹种群数量和分布情况的长期动态,为这一濒危物种的保护提供科学依据。[方法]2013年秋-2017年秋,在汪清保护区内东北豹主要分布区以每3 km×3 km网格1对的密度布设相机。采用相对丰富度指数(relative abundance indices,RAI)计算东北豹相对丰富度,以99%核密度等值线定义东北豹分布区,在Extract Compare软件中进行个体识别。在CAPTURE软件中对有效监测期的数据进行闭合种群检验、适宜模型评估和种群数量估计。以8 km为半径,在相机布设处向周边外延绘制缓冲区作为有效监测面积,评估东北豹种群密度。[结果]在9个监测季,东北豹RAI指数波动在0.34~2.12之间。2013年秋季东北豹分布区为201 km2,2017年秋季分布区为992 km2。共识别东北豹个体9只,其中成年雌性和雄性各3只、幼崽2只、性别不明个体1只。在种群数量低的情况下,CAPTURE闭合种群检验效力并不强,检验结果总体偏低。Mh模型(假设拍摄率有个体差异)选择标准得分在2015春、2015秋、2016秋、2017春4个监测季最高,在其他5个监测季得分仅次于M0(假设拍摄率一致)。卡方拟合优度检验显示,Mb(假设捕获前后拍摄率有差异)、Mt(假设不同时段拍摄率有差异)模型评估捕获率与M0模型无显著差异。研究期间东北豹种群密度波动在0.12~0.88只·(100 km2-1,种群总捕获率整体较高,但2017年春季拍摄个体仅占种群评估数量的0.43。[结论]受地理因素和猎物丰富度变化影响,东北豹时空分布具有异质性。CAPTURE闭合种群检验对小样本检验效力不强。Mh假设是进行东北豹种群数量评估的适宜模型,"拍摄羞怯反应"会导致种群密度评估结果偏高。

关键词: 东北豹, 红外相机监测, 时空分布格局, 种群密度评估, 野生动物

Abstract: [Objective] Far Eastern Leopard (Panthera pardus orientalis) disperses in the northernmost region and maintains the minimum population of Panthera pardus subspecies. It is evaluated as Critical Endangered in IUCN Red List. In this study, we analyzed long-term dynamic of population size and distribution of Far Eastern Leopard in Wangqing Nature Reserve and expected to provide scientific data for the protection of this endangered species.[Method] From Autumn 2013 to Autumn 2017, cameras were set up with a density of 1 pair per 3 km×3 km grid in the main leopard habitat in Wangqing Nature Reserve. The relative abundance indices (RAI) was used to calculate leopard abundance, the distribution area was defined by 99% kernel density contour, and individual was identified in Extract Compare software. The closure test, model selection and population estimation were performed for the data of effective monitoring period with CAPTURE software. The effective trapping area was estimated by projecting an 8 km radius buffer around each camera trap location. Then we calculated population density using effective trapping area.[Result]The RAI of leopard varied from 0.34 to 2.12 during 9 monitoring seasons. The distribution area of leopard was 201 km2 in Autumn 2013 and 992 km2 in Autumn 2017. A total of 9 individuals were identified, including 3 females, 3 males, 2 cubs and 1 unrecognizable. Both the value and the power of CAPTURE closure test were low when population size was small. The model selection criterions of Mh (heterogeneity effects model) were highest in 4 monitoring seasons, and second only after M0 (null model) in the other 5 seasons. The goodness of fit tests of M0 vs Mb(behaviour effects model) and M0 vs Mt(time effects model)showed that there were no significant differences between groups. The population density of leopard ranged from 0.12 to 0.88 individual per 100 km2 during research period. The value of captured individual/estimated population size was relatively high in general, albeit there was a low value of 0.43 in Spring 2017.[Conclusion] The distribution pattern of leopard obviously showed spatiotemporal heterogeneity due to geographic variance and prey abundance fluctuation. CAPTURE closed population test was ineffective for small sample test. Mh model was proper to evaluate leopard population. The capture rates showed no variance after trap or in different trap occasions. Leopard population density would be overestimated due to trap-shy response.

Key words: Panthera pardus orientalis, camera trap, spatiotemporal patterns, population density evaluation, wild animal

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