生物多样性 ›› 2022, Vol. 30 ›› Issue (9): 21357.  DOI: 10.17520/biods.2021357

• 中国猫科动物研究与保护专题 •    下一篇


杨剑焕1,*(), 李敬华1, 杨浩炫1, 欧梓键1, 郑玺1, Anthony J. Giordano2, 陈辈乐1   

  1. 1.嘉道理农场暨植物园, 香港 999077, 中国
    2.Society for the Preservation of Endangered Carnivores & Their International Ecological Study, Ventura, CA 93006, USA
  • 收稿日期:2021-09-05 接受日期:2021-11-22 出版日期:2022-09-20 发布日期:2021-12-30
  • 通讯作者: 杨剑焕
  • 作者简介:* E-mail: jhyang@kfbg.org

Population density and activity patterns of the leopard cat (Prionailurus bengalensis) in southern China: Estimates based on camera-trapping data

Jianhuan Yang1,*(), King Wa Li1, Ho Yuen Yeung1, Tsz Kin Au1, Xi Zheng1, Anthony J. Giordano2, Bosco Pui Lok Chan1   

  1. 1. Kadoorie Farm and Botanic Garden, Hong Kong 999077, China
    2. Society for the Preservation of Endangered Carnivores & Their International Ecological Study, Ventura, CA 93006, USA
  • Received:2021-09-05 Accepted:2021-11-22 Online:2022-09-20 Published:2021-12-30
  • Contact: Jianhuan Yang


可靠的种群密度数据对野生动物的保护和管理十分重要。豹猫(Prionailurus bengalensis)是中国分布最广且常见的猫科动物, 但野生种群密度估算的研究并不多。本研究于2020年6月至2021年5月在香港新界嘉道理农场暨植物园开展红外相机调查, 利用空间标记-重捕法估算当地豹猫的种群密度并用核密度估计方法分析其活动节律。本次调查以网格方式布置红外相机, 在约1.5 km2的研究范围之内设置了19个相机位点, 每个位点安装2台相机以获取豹猫身体两侧花纹来进行个体识别。连续12个月调查共捕获113次有效的豹猫拍摄事件, 当中仅61次事件的照片足够清晰以进行个体识别。基于种群封闭的要求, 我们以2个月为单位将12个月的数据分为6个采样期去分析豹猫种群密度, 结果显示仅两个采样期的估算值最为准确, 分别为0.64 ± 0.31 (0.26-1.55)只/km2和0.87 ± 0.48 (0.31-2.40)只/km2, 是已知全球豹猫密度最高的地点之一。结果还发现, 雨季研究地点的豹猫并无明显的日活动节律, 在旱季则偏夜行-晨昏行性多一些, 但也有一定的日间活动; 雨季和旱季的日活动节律无显著差异。本研究是首次以个体识别配以空间标记-重捕模型对中国大陆地区豹猫种群密度调查的研究; 我们也提出一些关于红外相机架设方法的建议, 以提高照片个体识别的准确度并增加重捕次数, 最后提高密度估算的准确度。本研究也进一步证明豹猫适应性极强, 在活动节律上表现出极高的可塑性, 在严格保护下可以恢复健康的种群。

关键词: 空间标记-重捕模型, 种群密度, 活动节律, 相机陷阱, 小型猫科动物, 食肉目, 香港


Aim: Reliable estimates of population density are fundamental to wildlife conservation and management. Although the leopard cat is the most common and widespread wild felid in China, little is known about the ecology and population biology of this species in the country. Using spatially explicit capture-recapture (SECR) modelling derived from extensive camera-trapping data, we estimated the population density and activity patterns of leopard cats in a well- protected private nature reserve in southern China.
Methods: Between June 2020 and May 2021, we conducted a camera-trap survey across a pre-determined grid system in Kadoorie Farm and Botanic Garden (KFBG), Hong Kong. KFBG was established on a barren hillside following sustained anthropogenic disturbances. After six decades of protection, secondary forest currently covers approximately 80% of the site. We deployed a total of 19 camera trap stations across our small 1.5 km2 study area, with two opposite-facing cameras at each station to obtain images of both flanks of leopard cats. The consecutive 12-month survey yielded 113 independent capture events of the leopard cat, of which 61 events were clear enough to facilitate individual identification. Based on closed population assumptions for capture-recapture models, we also divided the 12-month survey into six two-month sampling periods, and estimated the population density for each sampling period using Maximum Likelihood SECR modelling. We also examined activity kernel densities to estimate the difference in diel activity patterns between wet and dry seasons.
Results: Our analyses revealed that results from two sampling periods were robust and precise enough (i.e., low standard error and narrow 95% confidence intervals) to estimate leopard cat density. We estimated leopard cat density between June and July 2020 as D = 0.64 ± 0.31 (0.26-1.55) individuals/km2, and between February and March 2021 as D = 0.87 ± 0.48 (0.31-2.40) individuals/km2, which are among the highest density estimates for this species reported in any region. We also found that the diel activity pattern of leopard cats in the study site is arrhythmic during the wet season, but became more nocturnal-crepuscular during the dry season, though they also exhibited some diurnal activity. Kernel density analyses however suggested no significant differences in diel activity patterns occurred between wet and dry seasons.
Conclusions: Our study provides important early data on the population density of leopard cats in southern China, the results of which allow for comparisons with other studies elsewhere using capture-recapture modelling approaches. We further demonstrate the utility of SECR methods for estimating population density over short and long sampling periods across necessarily small sampling areas. We further provide practical recommendations for conducting camera trap surveys to enhance the success rates of individual identification and “recapture” of leopard cats. In accordance with the conclusion of other studies, our results show that leopard cats are highly adaptable, exhibit great plasticity in daily activity, and thrive well in human-modified landscapes.

Key words: spatially explicit capture-recapture (SECR), population density, activity pattern, camera traps, small felid, Carnivora, Hong Kong