“在哪里”和“有多少”? 中国雪豹调查与空缺

雪豹(Panthera uncia)分布广泛且调查难度较大, 全世界的雪豹研究面临的首要问题是雪豹基础数据的缺乏。本文通过检索1980至2018年已发表的含有中国境内雪豹分布和密度信息的中英文文章共35篇, 从中提取出雪豹的分布与密度信息, 其中含有密度估计的文献18篇。同时, 来自雪豹调查的15位一线成员通过填写表格和问卷的形式提供了28个地块上未发表的雪豹密度调查信息。基于此, 我们逐一分析了各省份已有的雪豹调查现状和存在的调查空缺, 发现雪豹分布调查的两大空白区域主要存在于与吉尔吉斯斯坦接壤的西天山地区和西藏南部的冈底斯-念青唐古拉山山脉和喜马拉雅山脉。相对我国雪豹栖息地总面积, 有过密度估算的面积仅占1.7%, 仍然处于刚刚起步的阶段, 并且已有的密度调查几乎都是在质量较好的雪豹栖息地内进行的。今后除了需要继续努力收集汇总已有的调查结果, 仍然需要在雪豹分布区(特别是空缺区域)内增加调查。     

祁连山国家公园牧民对雪豹(Panthera Unica)保护的态度认知及其影响因素

祁连山地区是中国乃至全球雪豹(Panthera Unica)分布最集中、种群密度最高的地区之一，该地区的雪豹科学保护对于全球雪豹种群具有重要意义。了解祁连山国家公园牧民对雪豹保护的态度认知、探究影响牧民对雪豹保护态度的主要因素，对于保护国家公园生态系统的原真性、促进人与野生动物和谐共处具有重要意义。基于半结构式访谈对祁连山国家公园牧民进行了随机抽样调查，结果表明：(1)受访者认为狼(n=34, 91.89%)和雪豹(n=16, 43.24%)是最重要的两种致害野生动物；(2)所有受访者对雪豹保护均持积极态度；(3)受访者认为野生动物捕杀(n=14, 50.00%)和草场退化(n=9, 32.14%)是家畜面临的两大威胁因素；(4)“雪豹捕杀家畜”和“为家畜购买商业保险”是影响牧民对雪豹保护态度的关键因素(P<0.05)。为促进人与野生动物长期共存，需要各级政府以国家公园体制建设为契机，进一步加强科学研究，制定更加科学合理的野生动物保护与管理措施。     

雪豹保护遗传学和基因组学研究进展

雪豹(Panthera uncia)隶属于食肉目猫科豹属,是生活在青藏高原及其周边地区的旗舰物种。随着分子生物学和高通量测序技术的发展,雪豹保护遗传学和保护基因组学研究得到快速的发展,其中非损伤性遗传取样法显著推动了雪豹保护遗传学研究。本文综述了非损伤性遗传取样法在雪豹物种鉴定、个体识别和性别鉴定等研究中的应用,雪豹的系统发生地位、系统地理格局和种群遗传结构及其亚种争议、演化历史、适应性演化和基因组特征等保护遗传学和基因组学方面的研究现状和进展,并对雪豹保护遗传学和基因组学未来发展趋势进行了展望,以期促进雪豹保护生物学研究和保护对策的科学制定。     

三江源国家级自然保护区内云塔村雪豹种群动态

种群监测可为物种研究和保护提供关键信息和依据。雪豹(Panthera uncia)作为亚洲高山生态系统的顶级捕食者和旗舰种, 一直是研究和保护的重点, 但其难以到达的栖息地、隐秘的行踪和广阔的家域使其监测工作开展难度较大, 雪豹种群动态研究较为匮乏。本研究在2013年10月至2019年1月期间, 使用当地社区维护的红外相机, 监测三江源国家级自然保护区通天河沿保护分区内青海省玉树州哈秀乡云塔村雪豹种群的密度和动态, 共识别出35只雪豹个体。基于数据质量较好的2015、2016、2017年连续3年的红外相机数据各年截取3个月数据, 使用空间标记-重捕模型估算种群数量和密度, 发现当地雪豹种群和成年个体密度基本维持稳定, 种群增长率为1.02, 但监测期间雪豹个体更替明显, 平均个体更替率为0.44, 并且围绕两片雪豹核心利用区域发生了领域取代。推测雪豹种群具有较多个体更替和领域取代是因为种群处在雪豹潜在扩散通道上, 或调查范围未覆盖完整种群。本研究是国内首次对雪豹进行较为长期的种群动态监测和分析, 研究结果体现了动态监测的重要性, 也显示出以当地社区为主体监测哺乳动物种群的可能性。     

四川邛崃山脉雪豹与赤狐时空生态位关系

食肉动物是生态系统中关键的功能类群,探究顶级捕食者和次级捕食者的种间作用和共存机制有助于我们深入理解生态系统变化和物种种群动态变化的驱动机制,是目前全球大型兽类种群衰退背景下的重要议题.在动物物种生态位的诸多维度中,空间与时间生态位是其中最为关键的两个维度,了解同域分布物种之间在时、空生态位上的相互关系是探究物种共存机...     

基于分子宏条形码分析四川卧龙国家级自然保护区雪豹的食性

作为中亚和青藏高原山地生态系统中的顶级捕食者, 雪豹(Panthera uncia)对于维持食物网结构和生态系统稳定性有重要作用。了解雪豹的食性组成和变化对于理解其生态系统功能和物种间相互作用有重要意义。以往的雪豹食性分析多基于对其粪便中食物残渣的形态学鉴定, 但准确度受人员经验和主观因素影响较大。邛崃山脉位于雪豹分布区东南缘, 该区域的雪豹种群规模小且相对孤立, 研究匮乏。本研究基于非损伤性取样, 在邛崃山脉的卧龙国家级保护区采集疑似雪豹粪便样品38份, 首先提取粪便DNA, 并扩增线粒体DNA 16S rRNA基因片段进行分子物种鉴定, 确定其中22份为雪豹粪便样品。随后, 利用脊椎动物通用引物和雪豹特异性阻抑引物扩增粪便DNA中的食物成分, 并进行高通量测序, 分析雪豹食性构成。食性分析结果显示岩羊(Pseudois nayaur)是卧龙地区雪豹最主要的食物, 在67%的样品中均有检出。家牦牛(Bos grunniens)在33%的样品中出现, 也在雪豹食性中占较高比例。此外, 鼠兔(Ochotona spp.)和鸟类也在少量样品中发现。可见, 野生猎物是卧龙地区雪豹的主要食物资源; 与大世界大多数其他地区的雪豹食性相同, 野生大型有蹄类是雪豹最重要的食物。然而家畜(牦牛)在卧龙雪豹食谱中有相当高的占比, 显示该区域内可能存在较为严重的由雪豹捕食散养家畜引起的人兽冲突问题。     

四川邛崃山脉雪豹与散放牦牛潜在分布重叠与捕食风险评估

由雪豹(Panthera uncia)捕食散放家畜引起的人兽冲突是目前中国雪豹保护面临的主要挑战之一。四川邛崃山脉地处雪豹分布范围的东南缘, 本研究以邛崃山中部的自然保护区群为研究区, 收集了2014-2018年红外相机调查和动物粪便DNA分析中采集到的雪豹与散放牦牛的分布位点, 使用MaxEnt物种分布模型预测两物种在研究区内的潜在分布范围, 以两物种分布重叠的程度作为评估雪豹捕食家畜潜在风险的指标, 从而识别雪豹-家畜冲突的高危区域。结果表明, 在邛崃山中部的保护区群中, 模型预测的雪豹适宜栖息地面积为871.14 km ², 牦牛适宜栖息地面积为988.41 km ², 二者重叠面积达534.47 km ², 主要分布在研究区西部的高山草甸地区, 占域内雪豹适宜栖息地总面积的61.35%。研究区域内总体上可能存在较高的雪豹-家畜冲突风险。在这些自然保护区以及新建的大熊猫国家公园的管理规划中, 应把高山放牧作为对区内野生雪豹种群的关键威胁之一, 重点关注模型预测的人兽冲突高危区域, 通过改变社区牧业管理方式、发展社区替代生计等方式, 降低潜在冲突的风险。     

天山中部雪豹栖息地适宜性研究初报

栖息地丧失和破碎化是许多濒危物种面临的主要威胁,对于分布在高原山地的濒危物种雪豹亦是如此。为了更好地了解天山雪豹的分布情况和栖息地质量,2018年11月至2019年6月,我们在天山中部借助红外相机开展野外调查,调查面积2 425 km²,共获得78个雪豹的出现位点。利用8个物种分布模型对雪豹在此地的生境选择建模,综合结果表明,崎岖度和海拔是影响雪豹分布的主要因素,其中崎岖度大于70和海拔1 700~2 900 m是雪豹出现频率最高的地区。集成模型空间预测显示大部分适宜栖息地集中于乌苏市以东至板房沟分局管辖地区。本研究通过野外调查和模型分析获得了天山中部雪豹的分布区域及环境因子对其的影响,为天山雪豹保护及跨境合作提供科学的数据支撑。     

Assessing Estimators of Snow Leopard Abundance

Abstract: The secretive nature of snow leopards (Uncia uncia) makes them difficult to monitor, yet conservation efforts require accurate and precise methods to estimate abundance. We assessed accuracy of Snow Leopard Information Management System (SLIMS) sign surveys by comparing them with 4 methods for estimating snow leopard abundance: predator:prey biomass ratios, capture-recapture density estimation, photo-capture rate, and individual identification through genetic analysis. We recorded snow leopard sign during standardized surveys in the SaryChat Zapovednik, the Jangart hunting reserve, and the Tomur Strictly Protected Area, in the Tien Shan Mountains of Kyrgyzstan and China. During June-December 2005, adjusted sign averaged 46.3 (SaryChat), 94.6 (Jangart), and 150.8 (Tomur) occurrences/km. We used counts of ibex (Capra ibex) and argali (Ovis ammon) to estimate available prey biomass and subsequent potential snow leopard densities of 8.7 (SaryChat), 1.0 (Jangart), and 1.1 (Tomur) snow leopards/100 km². Photo capture-recapture density estimates were 0.15 (n = 1 identified individual/1 photo), 0.87 (n = 4/13), and 0.74 (n = 5/6) individuals/100 km² in SaryChat, Jangart, and Tomur, respectively. Photo-capture rates (photos/100 trap-nights) were 0.09 (SaryChat), 0.93 (Jangart), and 2.37 (Tomur). Genetic analysis of snow leopard fecal samples provided minimum population sizes of 3 (SaryChat), 5 (Jangart), and 9 (Tomur) snow leopards. These results suggest SLIMS sign surveys may be affected by observer bias and environmental variance. However, when such bias and variation are accounted for, sign surveys indicate relative abundances similar to photo rates and genetic individual identification results. Density or abundance estimates based on capture-recapture or ungulate biomass did not agree with other indices of abundance. Confidence in estimated densities, or even detection of significant changes in abundance of snow leopard, will require more effort and better documentation.     

Calibrating a camera trap–based biased mark–recapture sampling design to survey the leopard population in the N'wanetsi concession,Kruger National Park,South Africa

Estimating large carnivore abundance can be challenging. A biased leopard (Panthera pardus) population survey was conducted in the N'wanetsi concession in the Kruger National Park (KNP), South Africa, using motion‐sensitive camera traps from April to August 2008. Survey effort included 88 trapping occasions and 586 trap days. The survey yielded 24 leopard photographs, comprising fourteen adults of eleven males and three females. The capture rate was determined to be 24.4 trap days per leopard. Estimates of population abundance stabilized at approximately 500 trap days. Precision of population estimates began to stabilize after 378 trap days. We estimated that there were nineteen leopards in an area of 150 km². Leopard density was estimated at 12.7 leopards per 100 km². We explore the possibility of employing the methods used in this study to survey the leopard population in the KNP and surrounding areas.     

Sympatric snow leopards and Tibetan wolves: coexistence of large carnivores with human-driven potential competition

The snow leopard Panthera uncia coexists with the wolf Canis lupus throughout most of its distribution range. We analysed the food habits of snow leopards and wolves in their sympatric range in the Karakoram mountains of Pakistan. A total of 131 genotyped scats (N?=?74, snow leopard; N?=?57, Tibetan wolf) were collected during the cold periods (i.e. winter and spring) of 2011 and 2012 in the Hushey valley. Large mammals, i.e. livestock and ibex, accounted for 84.8 and 83.1% of the diet (relative frequency) of the snow leopard and the wolf, respectively. Domestic prey was the staple of the diet of both snow leopards (66.6%) and wolves (75.1%). Ibex Capra ibex, the only wild ungulate in our study area, contributed 18.2 and 16.9% of relative frequencies in the diets of the snow leopard and the wolf, respectively. In winter, the snow leopard heavily relied on domestic sheep (43.3%) for food, whereas the wolf preyed mainly on domestic goats (43.4%). Differently from other study areas, both snow leopards and wolves showed no apparent prey preference (Jacobs index: snow leopard min. ??0.098, max. 0.102; Tibetan wolf min. ??0.120, max. 0.03). In human depauperate areas, with livestock and only a few wild prey, should competitive interactions arise, two main scenarios could be expected, with either predator as a winner. In both cases, the best solution could primarily impinge on habitat restoration, so that a balance could be found between these predators, who have already coexisted for thousands of years.     

Predicting the distributions of predator (snow leopard) and prey (blue sheep) under climate change in the Himalaya

Future climate change is likely to affect distributions of species, disrupt biotic interactions, and cause spatial incongruity of predator–prey habitats. Understanding the impacts of future climate change on species distribution will help in the formulation of conservation policies to reduce the risks of future biodiversity losses. Using a species distribution modeling approach by MaxEnt, we modeled current and future distributions of snow leopard (Panthera uncia) and its common prey, blue sheep (Pseudois nayaur), and observed the changes in niche overlap in the Nepal Himalaya. Annual mean temperature is the major climatic factor responsible for the snow leopard and blue sheep distributions in the energy‐deficient environments of high altitudes. Currently, about 15.32% and 15.93% area of the Nepal Himalaya are suitable for snow leopard and blue sheep habitats, respectively. The bioclimatic models show that the current suitable habitats of both snow leopard and blue sheep will be reduced under future climate change. The predicted suitable habitat of the snow leopard is decreased when blue sheep habitats is incorporated in the model. Our climate‐only model shows that only 11.64% (17,190 km²) area of Nepal is suitable for the snow leopard under current climate and the suitable habitat reduces to 5,435 km² (reduced by 24.02%) after incorporating the predicted distribution of blue sheep. The predicted distribution of snow leopard reduces by 14.57% in 2030 and by 21.57% in 2050 when the predicted distribution of blue sheep is included as compared to 1.98% reduction in 2030 and 3.80% reduction in 2050 based on the climate‐only model. It is predicted that future climate may alter the predator–prey spatial interaction inducing a lower degree of overlap and a higher degree of mismatch between snow leopard and blue sheep niches. This suggests increased energetic costs of finding preferred prey for snow leopards – a species already facing energetic constraints due to the limited dietary resources in its alpine habitat. Our findings provide valuable information for extension of protected areas in future.     

Low leopard populations in protected areas of Maputaland: a consequence of poaching,habitat condition,abundance of prey,and a top predator

Identifying the primary causes affecting population densities and distribution of flagship species are necessary in developing sustainable management strategies for large carnivore conservation. We modeled drivers of spatial density of the common leopard (Panthera pardus) using a spatially explicit capture–recapture—Bayesian approach to understand their population dynamics in the Maputaland Conservation Unit, South Africa. We camera‐trapped leopards in four protected areas (PAs) of varying sizes and disturbance levels covering 198 camera stations. Ours is the first study to explore the effects of poaching level, abundance of prey species (small, medium, and large), competitors (lion Panthera leo and spotted hyenas Crocuta crocuta), and habitat on the spatial distribution of common leopard density. Twenty‐six male and 41 female leopards were individually identified and estimated leopard density ranged from 1.6 ± 0.62/100 km² (smallest PA—Ndumo) to 8.4 ± 1.03/100 km² (largest PA—western shores). Although dry forest thickets and plantation habitats largely represented the western shores, the plantation areas had extremely low leopard density compared to native forest. We found that leopard density increased in areas when low poaching levels/no poaching was recorded in dry forest thickets and with high abundance of medium‐sized prey, but decreased with increasing abundance of lion. Because local leopard populations are vulnerable to extinction, particularly in smaller PAs, the long‐term sustainability of leopard populations depend on developing appropriate management strategies that consider a combination of multiple factors to maintain their optimal habitats.     

Development of primers to characterize the mitochondrial control region of the snow leopard (Uncia uncia)

The snow leopard (Uncia uncia) is a rare carnivore living above the snow line in central Asia. Using universal primers for the mitochondrial genome control region hypervariable region 1 (HVR1), we isolated a 411‐bp fragment of HVR1 and then designed specific primers near each end of this sequence in the conserved regions. These primers were shown to yield good polymerase chain reaction products and to be species specific. Of the 12 snow leopards studied, there were 11 segregating sites and six haplotypes. An identification case of snow leopard carcass (confiscated by the police) proved the primers to be a useful tool for forensic diagnosis in field and population genetics studies.     

Meta‐replication,sampling bias,and multi‐scale model selection: A case study on snow leopard (Panthera uncia) in western China

Replicated multiple scale species distribution models (SDMs) have become increasingly important to identify the correct variables determining species distribution and their influences on ecological responses. This study explores multi‐scale habitat relationships of the snow leopard (Panthera uncia) in two study areas on the Qinghai–Tibetan Plateau of western China. Our primary objectives were to evaluate the degree to which snow leopard habitat relationships, expressed by predictors, scales of response, and magnitude of effects, were consistent across study areas or locally landcape‐specific. We coupled univariate scale optimization and the maximum entropy algorithm to produce multivariate SDMs, inferring the relative suitability for the species by ensembling top performing models. We optimized the SDMs based on average omission rate across the top models and ensembles’ overlap with a simulated reference model. Comparison of SDMs in the two study areas highlighted landscape‐specific responses to limiting factors. These were dependent on the effects of the hydrological network, anthropogenic features, topographic complexity, and the heterogeneity of the landcover patch mosaic. Overall, even accounting for specific local differences, we found general landscape attributes associated with snow leopard ecological requirements, consisting of a positive association with uplands and ridges, aggregated low‐contrast landscapes, and large extents of grassy and herbaceous vegetation. As a means to evaluate the performance of two bias correction methods, we explored their effects on three datasets showing a range of bias intensities. The performance of corrections depends on the bias intensity; however, density kernels offered a reliable correction strategy under all circumstances. This study reveals the multi‐scale response of snow leopards to environmental attributes and confirms the role of meta‐replicated study designs for the identification of spatially varying limiting factors. Furthermore, this study makes important contributions to the ongoing discussion about the best approaches for sampling bias correction.     

Modelling potential habitat suitability for critically endangered Arabian leopards (Panthera pardus nimr) across their historical range in Saudi Arabia

Camera trapping can detect and monitor rare species in landscapes spanning thousands of square kilometres but placement of cameras in areas where the animals most likely occur will increase detection success. This vital information is lacking for the critically endangered Arabian leopard (Panthera pardus nimr) that has undergone a 90% decline across its range in Saudi Arabia. We aimed to identify suitable Arabian leopard habitat and potential population capacity in Saudi Arabia using data from leopards living in ecologically analogous habitat in South Africa and Oman. We developed a resource selection function (RSF) from 14 leopards’ GPS data in the Cederberg, South Africa, and validated the model using three leopards in the Little Karoo, and two Arabian leopards in Oman. We then projected the model to the historical range of Arabian leopards in Saudi Arabia to estimate likely leopard locations and potential population sizes based on home range metrics. The RSF successfully discriminated between used and available locations (specificity = 96.7%) and had high predictive ability (Rho > 0.9). Leopards selectively used areas away from human settlements and roads, with high enhanced vegetation index, and intermediate slopes and elevations. Saudi Arabia could theoretically host 4 distinct populations totalling 162–362 Arabian leopard females, depending on home range size. Camera traps deployed in the south-western mountains of Saudi Arabia may be most likely to detect remnant populations of Arabian leopards. Further research is needed into the local abundance of prey species and human activity to ensure the persistence of suitable leopard ranges and inform conservation actions.     

Vigorous Dynamics Underlie a Stable Population of the Endangered Snow Leopard Panthera uncia in Tost Mountains,South Gobi,Mongolia

Population monitoring programmes and estimation of vital rates are key to understanding the mechanisms of population growth, decline or stability, and are important for effective conservation action. We report, for the first time, the population trends and vital rates of the endangered snow leopard based on camera trapping over four years in the Tost Mountains, South Gobi, Mongolia. We used robust design multi-season mark-recapture analysis to estimate the trends in abundance, sex ratio, survival probability and the probability of temporary emigration and immigration for adult and young snow leopards. The snow leopard population remained constant over most of the study period, with no apparent growth (λ = 1.08+−0.25). Comparison of model results with the “known population” of radio-collared snow leopards suggested high accuracy in our estimates. Although seemingly stable, vigorous underlying dynamics were evident in this population, with the adult sex ratio shifting from being male-biased to female-biased (1.67 to 0.38 males per female) during the study. Adult survival probability was 0.82 (SE+−0.08) and that of young was 0.83 (SE+−0.15) and 0.77 (SE +−0.2) respectively, before and after the age of 2 years. Young snow leopards showed a high probability of temporary emigration and immigration (0.6, SE +−0.19 and 0.68, SE +−0.32 before and after the age of 2 years) though not the adults (0.02 SE+−0.07). While the current female-bias in the population and the number of cubs born each year seemingly render the study population safe, the vigorous dynamics suggests that the situation can change quickly. The reduction in the proportion of male snow leopards may be indicative of continuing anthropogenic pressures. Our work reiterates the importance of monitoring both the abundance and population dynamics of species for effective conservation.     

新疆托木尔峰国家级自然保护区雪豹的种群密度

雪豹(Panthera uncia)是一种仅公布于中亚高山地区的珍稀濒危大型猫科动物,被IUCN红皮书列为濒危物种,并被收录入CITES公约附录Ⅰ,在中国雪豹被列为国家一级重点保护动物(杨奇森和冯祚建,1998).     

No silver bullet? Snow leopard prey selection in Mt. Kangchenjunga,Nepal

In this study, we investigated the impact of domestic and wild prey availability on snow leopard prey preference in the Kangchenjunga Conservation Area of eastern Nepal—a region where small domestic livestock are absent and small wild ungulate prey are present. We took a comprehensive approach that combined fecal genetic sampling, macro‐ and microscopic analyses of snow leopard diets, and direct observation of blue sheep and livestock in the KCA. Out of the collected 88 putative snow leopard scat samples from 140 transects (290 km) in 27 (4 × 4 km²) sampling grid cells, 73 (83%) were confirmed to be from snow leopard. The genetic analysis accounted for 19 individual snow leopards (10 males and 9 females), with a mean population size estimate of 24 (95% CI: 19–29) and an average density of 3.9 snow leopards/100 km² within 609 km². The total available prey biomass of blue sheep and yak was estimated at 355,236 kg (505 kg yak/km² and 78 kg blue sheep/km²). From the available prey biomass, we estimated snow leopards consumed 7% annually, which comprised wild prey (49%), domestic livestock (45%), and 6% unidentified items. The estimated 47,736 kg blue sheep biomass gives a snow leopard‐to‐blue sheep ratio of 1:59 on a weight basis. The high preference of snow leopard to domestic livestock appears to be influenced by a much smaller available biomass of wild prey than in other regions of Nepal (e.g., 78 kg/km² in the KCA compared with a range of 200–300 kg/km² in other regions of Nepal). Along with livestock insurance scheme improvement, there needs to be a focus on improved livestock guarding, predator‐proof corrals as well as engaging and educating local people to be citizen scientists on the importance of snow leopard conservation, involving them in long‐term monitoring programs and promotion of ecotourism.     

In the shadows of snow leopards and the Himalayas: density and habitat selection of blue sheep in Manang,Nepal

There is a growing agreement that conservation needs to be proactive and pay increased attention to common species and to the threats they face. The blue sheep (Pseudois nayaur) plays a key ecological role in sensitive high‐altitude ecosystems of Central Asia and is among the main prey species for the globally vulnerable snow leopard (Panthera uncia). As the blue sheep has been increasingly exposed to human pressures, it is vital to estimate its population dynamics, protect the key populations, identify important habitats, and secure a balance between conservation and local livelihoods. We conducted a study in Manang, Annapurna Conservation Area (Nepal), to survey blue sheep on 60 transects in spring (127.9 km) and 61 transects in autumn (134.7 km) of 2019, estimate their minimum densities from total counts, compare these densities with previous estimates, and assess blue sheep habitat selection by the application of generalized additive models (GAMs). Total counts yielded minimum density estimates of 6.0–7.7 and 6.9–7.8 individuals/km² in spring and autumn, respectively, which are relatively high compared to other areas. Elevation and, to a lesser extent, land cover indicated by the normalized difference vegetation index (NDVI) strongly affected habitat selection by blue sheep, whereas the effects of anthropogenic variables were insignificant. Animals were found mainly in habitats associated with grasslands and shrublands at elevations between 4,200 and 4,700 m. We show that the blue sheep population size in Manang has been largely maintained over the past three decades, indicating the success of the integrated conservation and development efforts in this area. Considering a strong dependence of snow leopards on blue sheep, these findings give hope for the long‐term conservation of this big cat in Manang. We suggest that long‐term population monitoring and a better understanding of blue sheep–livestock interactions are crucial to maintain healthy populations of blue sheep and, as a consequence, of snow leopards.