中国金钱豹（Panthera pardus）的分布、现状与监测策略

金钱豹(Panthera pardus)是世界上分布最广的野生猫科动物，但我们必须看到，它们在亚洲的种群数量已经显著减少。历史上，金钱豹曾广布于除干旱戈壁沙漠和海拔4'000米以上西部山地之外的中国全境。然而，近年的调查表明，金钱豹已经从很多地区消失，远没有人们曾经认为的那么常见。本论文在多重地理尺度下开展研究，旨在深化对中国金钱豹保护生物学的理解。论文采用多种数据源采集金钱豹在全国范围内的分布记录，以评估金钱豹的分布和生存现状。研究结果表明，金钱豹在中国急剧减少，只在11个省的44个位点发现了确凿的分布记录。现存金钱豹种群小(<50个体)且分散，主要存在于相互孤立的自然保护区中，使得它们面临着较高的局地灭绝的风险。值得注意的是，这些中国金钱豹的分布记录大多是在对其他旗舰物种进行调查和研究时所获得的，而很少直接源于关于金钱豹的项目和研究。因此，现有的金钱豹研究没有将那些不与其他旗舰物种重叠，尤其是金钱豹单独适应的栖息地和生态系统包括在内，那主要是一些离人类干扰较近而其他物种已经局地灭绝的区域。山西省就是一个这样的地区，该省位于华北地区黄河流域的中部，华北豹(P.p. japonensis)这一仅分布于中国的金钱豹亚种就生活在这里。在本论文中，我们建立物种分布模型以预测哪些环境条件适宜于金钱豹生存，进而确定哪些区域适于它们生存。首先，我们从2008到2013年间在全省范围内非系统安装的红外相机数据中提取出金钱豹的分布数据。然后，在1km2大小的栅格内选取分别代表地形、植被和人类活动的六个不相关变量，用来分析环境因子对雪豹分布的影响。MAXENT模型的分析结果表明，影响金钱豹分布的最重要的因素是森林覆盖率(贡献率为90%)，道路和人口密度的影响则比较小(分别为3.3%和2.6%)。研究发现，在山西省南部仍有大面积的适宜栖息地，包括了两个国家级保护区。选取其中面积最大的历山国家级自然保护区，作为进行第一次种群密度估算的区域。于是，我们在整个保护区(252 km2)内系统地安装了139台红外相机。通过对照片的个体鉴别，共识别出了5只金钱豹，并采用种群密度估算所能应用的最现代的统计建模技术进行了分析。通过标志重捕(MARK)和空间标志重捕(SPACECAP)模型所得的结果比较相近(分别为0.7和0.6±0.3只金钱豹／100km2)。这一密度相当于在中国东北极度濒危的东北豹(P.p. orientalis)，同时也是世界上金钱豹密度的最低记录之一。论文对应用痕迹调查作为红外相机的替代或补充手段进行种群监测的可行性进行了探讨，但找到的痕迹不多(粪便34个， 足迹3个， 抓痕5个， 毛发2处)。实际上，除非通过DNA分析验证，否则无法确认野外粪便样本所属的物种。研究发现，在所有判别为目标物种的粪便中，只有14%真正来自金钱豹，其它大多数都是犬科动物的粪便。因为豹的样本数量小，无法进行近一步的探究，所以我们应用雪豹(Panthera uncia)景观中的食肉动物群落进行分析判别，并得出了相似的结果：超过一半在野外被认为是雪豹的粪便实际上来自赤狐(Vulpes vulpes)。由此可见，因为错误识别率如此之高，依靠粪便样本所进行的物种调查和监测都应使用分子粪便学技术完成物种鉴定。同时，痕迹的低遇见率(0.1痕迹／km)提示我们，除非提高调查强度(加长样线距离)和／或增加发现率(在有积雪时进行调查)，否则无法应用痕迹调查达到预期效果。必须看到，我们对中国金钱豹的知识缺口依然很大，这种信息的缺失会降低保护工作的有效性。我们所进行的系统性调查适用于金钱豹这样难以发现的物种的监测和研究，即便在种群密度很低的情况下也依然适用。另一方面，痕迹调查无法提供分析所需的足够多的样本量，而且需要通过分子粪便学技术鉴定以避免误判。可以认为，监测方案以及管理实践必须得到优化并在整合国家、省和自然保护区各尺度基础上加以实施，以确保这些小而破碎化的种群得到长期有效的保护。

Leopards (Panthera pardus) are the most widely distributed wild felid species globally, yet their populations in Asia have declined significantly. Historically, leopards were widespread across all of China except for the arid Gobi Desert and western mountainous areas above 4,000 meters above sea level. However, recent surveys indicate that leopards have disappeared from many regions and are far less common than previously thought.

This study was conducted at multiple geographic scales to deepen our understanding of the conservation biology of leopards in China. We collected national-scale distribution records of leopards using multiple data sources to assess their current distribution and population status. Our results show that leopards have undergone a drastic decline in China, with confirmed occurrence records only at 44 sites across 11 provinces. The remaining leopard populations are small (<50 individuals) and fragmented, primarily existing in isolated nature reserves, posing a high risk of local extinction.

Notably, most of these Chinese leopard occurrence records were obtained during surveys and studies targeting other flagship species, with few directly derived from leopard-specific projects or research. Consequently, existing leopard studies have excluded habitats and ecosystems that do not overlap with other flagship species, particularly those exclusively adapted to leopards—mainly areas close to human disturbance where other species have gone locally extinct.

Shanxi Province, located in the middle reaches of the Yellow River in North China, is one such region, where the North China leopard (P. p. japonensis), a leopard subspecies endemic to China, resides. In this study, we developed species distribution models (SDMs) to predict environmental conditions suitable for leopard survival and identify suitable habitats for them. First, we extracted leopard distribution data from non-systematically deployed camera trap data collected across the entire province between 2008 and 2013. Subsequently, we selected six uncorrelated variables representing topography, vegetation, and human activity at the 1 km² grid scale to analyze the impacts of environmental factors on leopard distribution. The results from the MAXENT model showed that the most critical factor influencing leopard distribution is forest cover (contribution rate: 90%), while the impacts of road density and human population density are relatively minor (3.3% and 2.6%, respectively).

We found that large areas of suitable habitat still exist in southern Shanxi Province, including two national nature reserves. We selected the Lishan National Nature Reserve, the largest among them, as the site for the first population density estimation. We then systematically deployed 139 camera traps across the entire reserve (252 km²). Through individual identification of captured images, we identified a total of 5 leopards, and analyzed the data using the most modern statistical modeling techniques applicable to population density estimation. The results from the mark-recapture (MARK) and spatial mark-recapture (SPACECAP) models were relatively consistent (0.7 and 0.6 ± 0.3 leopards per 100 km², respectively). This density is comparable to that of the critically endangered Amur leopard (P. p. orientalis) in Northeast China, and is also among the lowest leopard density records globally.

We also explored the feasibility of using sign surveys as an alternative or supplement to camera traps for population monitoring, but found very few signs: 34 feces, 3 footprints, 5 scratch marks, and 2 hair samples. In fact, without DNA verification, it is impossible to confirm the species of wild fecal samples. We found that only 14% of feces initially identified as target species were actually from leopards, with most others being from canids. Due to the small sample size of leopard signs, we conducted analysis and discrimination using the carnivore community in the snow leopard (Panthera uncia) landscape, and obtained similar results: more than half of feces initially identified as snow leopard in the field were actually from red foxes (Vulpes vulpes). This demonstrates that due to the high misidentification rate, species surveys and monitoring relying on fecal samples should use molecular scatology techniques for species identification. Meanwhile, the low encounter rate of signs (0.1 signs per km) suggests that sign surveys cannot achieve the expected results unless survey effort is increased (lengthening transect distance) and/or detection rate is improved (conducting surveys during snow cover).

It must be recognized that significant gaps in our knowledge of Chinese leopards remain, and this lack of information reduces the effectiveness of conservation efforts. Our systematic survey is applicable to the monitoring and research of cryptic species such as leopards, even in situations with very low population densities. On the other hand, sign surveys cannot provide sufficient sample sizes for analysis and require molecular scatology identification to avoid misjudgments. We conclude that monitoring protocols and management practices must be optimized and implemented at integrated national, provincial, and nature reserve scales to ensure the long-term effective conservation of these small, fragmented populations.

搜集汇总

背景与挑战

背景概述

该数据集基于一篇研究论文，聚焦中国金钱豹的分布、现状与监测策略。研究发现金钱豹种群急剧减少，仅存于11个省的44个位点，种群小而分散，主要栖息在孤立的自然保护区中，面临较高的局地灭绝风险。研究采用红外相机和物种分布模型等方法，揭示森林覆盖率是影响分布的关键因素，并评估了监测策略，指出系统性调查适用于低密度种群，而痕迹调查需结合分子技术以提高准确性。