Abstract: Camera trapping is the most widely used data collection method for estimating snow leopard (Panthera uncia) abundance; however, the accuracy of this method is limited by human observer errors from misclassifying individuals in camera trap images. We evaluated the extent Whiskerbook (www.whiskerbook.org), an artificial intelligence (AI) software, could reduce this error rate and enhance the accuracy of capture-recapture abundance estimates. Using 439 images of 34 captive snow leopard individuals, classification was performed by five observers with prior experience in individual snow leopard ID (“experts”) and five observers with no such experience (“novices”). The “expert” observers classified 35 out of 34 snow leopard individuals, on average erroneously splitting one individual into two, thus resulting in a higher number than true individuals. The success rate of experts was 90 %, with less than a 3 % error in estimating the population size in capture-recapture modeling. However, the “novice” observers successfully matched 71 % of encounters, recognizing 25 out of 34 individuals, underestimating the population by 25 %. It was found that expert observers significantly outperformed novice observers, making statistically fewer errors (Mann Whitney U test P = 0.01) and finding the true number of individuals (P = 0.01). These differences were contrasted with a previous study by Johansson et al. 2020, using the same subset of 16 individuals from European zoos. With the help of AI and the Whiskerbook platform, “experts” were able to match 87 % of encounters and identify 15 out of 16 individuals, with modeled estimates of 16 ± 1 individuals. In contrast, “novices” were 63 % accurate in matching encounters and identified 12 out of 16 individuals, modeling 12 ± 1 individuals that underestimated the population size by 12 %. When comparing the performance of observers using AI and the Whiskerbook platform to observers performing the tasks manually, we found that observers using Whiskerbook made significantly fewer errors in splitting one individual into two (P = 0.04). However, there were also a significantly higher number of combination errors, where two individuals were combined into one (P = 0.01). Specifically, combination errors were found to be made by “novices” (P = 0.04). Although AI benefited both expert and novice observers, expert observers outperformed novices. Our results suggest that AI effectively reduced the misclassification of individual snow leopards in camera trap studies, improving abundance estimates. However, even with AI support, expert observers were needed to obtain the most accurate estimates.

Abstract: Context: The accurate estimation of landscape resistance to movement is important for ecological understanding and conservation applications. Rigorous estimation of resistance requires validation and optimization. One approach uses genetic data for the optimization or validation of resistance models. Objectives We used a genetic dataset of snow leopards from China to evaluate how landscape genetics resistance models varied across genetic distances and spatial scales of analysis. We evaluated whether landscape genetics models were superior to models of resistance derived from habitat suitability or isolation-by-distance.
Methods: We regressed genetically optimized, habitat-based, and isolation-by-distance hypotheses against genetic distances using mixed effect models. We explored all subset combinations of genetically optimized variables to find the most supported resistance scenario for each genetic distance.
Results: Genetically optimized models always out-performed habitat-based and isolation-by-distance hypotheses. The choice of genetic distances influenced the apparent influence of variables, their spatial scales and their functional response shapes, producing divergent resistance scenarios. Gene flow in snow leopards was largely facilitated by areas of intermediate ruggedness at intermediate elevations corresponding to small-to-large valleys within and between the mountain ranges.
Conclusions: This study highlights that landscape genetics models provide superior estimation of functional dispersal than habitat surrogates and suggests that optimization of genetic distance should be included as an optimization routine in landscape genetics, along with variables, scales, effect size and functional response shape. Furthermore, our study provides new insights on the ecological conditions that promote gene flow in snow leopards, which expands ecological knowledge, and we hope will improve conservation planning.

Abstract: Mammalian carnivores are key to our understanding of ecosystem dynamics, but most of them are threatened with extinction all over the world. Conservating large carnivores is often an arduous task considering the complex relationship between humans and carnivores, and the diverse range and reasons of threats they face. Climate change is exacerbating the situation further by interacting with most existing threats and amplifying their impacts. The Mountains of Central and South Asia are warming twice as rapidly as the rest of the northern hemisphere. There has been limited research on the effect of climate change and other variables on large carnivores. We studied the patterns in spatio-temporal distribution of three sympatric carnivores, common leopard, snow leopard, and Asiatic black bear in Kishtwar high altitude National Park, a protected area in the Great Himalayan region of Jammu and Kashmir. We investigated the effects of key habitat characteristics as well as human disturbance and climatic factors to understand the spatio-temporal change in their distributions between the early 1990s and around the year 2016–2017. We found a marked contraction in the distribution of the three carnivores between the two time periods. While snow leopard shifted upwards and further away from human settlements, common leopard and Asiatic black bear suffered higher rates of local extinctions at higher altitudes and shifted to lower areas with more vegetation, even if that brought them closer to settlements. We also found some evidence that snow leopards were less likely to have faced range contraction in areas with permanent glaciers. Our study underscores the importance of climate adaptive conservation practices for long-term management in the Greater Himalaya, including the monitoring of changes in habitat, and space-use patterns by human communities and wildlife.

Abstract: In Nepal, naur are usually the staple wild prey for the snow leopard, a solitary stalker hunter, and in some cases, for the wolf who hunts in a pack. We assumed that naur would adapt their anti-predatory responses to the presence of chasing and ambushing predators in the Manang Valley, where there are snow leopards and wolves, and in the Nar Phu valley, an area where there is only the snow leopard.
Aims. The aim of this study was to determine if there were differences in anti-predator strategies (vigilance, habitat selection and escape terrain) of naur in two valleys over two seasons, spring and autumn.
Methods. In spring 2019, we conducted a reconnaissance survey on the status of the naur and its habitat in the Manang and Nar Phu valleys of the Annapurna Conservation Area, Nepal. In spring and autumn 2020 and 2021, we observed 360 focal naur individuals (180 individuals in each valley), using the vigilance behaviour methodology to examine the behaviour of the naur.
Key results. There was little difference in the size of the naur groups between the Manang and Nar Phu valleys. The naur were twice as vigilant in Manang (15%), where there are snow leopards and wolves, as they were in Nar Phu (9%), with only snow leopards. The distance from the naur to escape cover was significantly shorter in Manang than in Nar Phu valley. Naur used significantly more rolling terrain in Nar Phu than in Manang. Conclusions. The return of wolves to the Manang valley may have resulted in an increase in the level of naur vigilance. Most likely, the wolves in Manang have already had an effect on the female-to-young-ratio, and this effect will possibly have important consequences for the naur population, as well as at the ecosystem level in the future. Other key determining factors, such as the climate crisis and changes in local resources, could have a significant impact on the naur population, indicating the need for more research. Implications. The findings of this study would provide valuable baseline information for the design of a science-based conservation strategy for conservation managers and scientists on naur, snow leopards and wolves.

Abstract: Fostering human–wildlife coexistence necessitates a thorough and nuanced grasp of local attitudes toward wildlife. Attitudes can vary substantially based on the sociodemographic backgrounds of individuals within a society. This study examines Tibetan attitudes toward large carnivores, emphasizing the importance of contextualization in discerning the effects of sociodemographic factors on attitudes. We began by analyzing existing research on Tibetan attitudes toward wildlife in China, identifying previously studied sociodemo- graphic variables. We then executed an online survey to evaluate the affective, behavioral, cognitive, and overall attitudes of ethnic Tibetans in China toward snow leopards (Panthera uncia), gray wolves (Canis lupus), and brown bears (Ursus arctos). Our findings show that while factors such as gender, age, religious identity, and level of education shape these attitudes, their influence differs depending on the specific attitude component and the target animal under examination. Therefore, making broad generalizations about sociodemographic differences in attitudes can be misleading. It is imperative for attitude research to clearly define the attitude component (what type of attitude), object (attitude toward what), and circumstance (attitude in which situation) being studied. Conducting ethnographic fieldwork in collaboration with local cultural experts can deepen our understanding of local perspectives and the ways sociodemographic factors influence attitudes. Such insights are pivotal for developing conservation strategies attuned to local sociocultural contexts.

Abstract: Polar bears (Ursus maritimus), Eurasian lynx (Lynx lynx) and snow leopards (Panthera uncia) are elusive large carnivores inhabiting snow-covered and remote areas. Their effective conservation and management are challenged by inadequate population information, necessitating development of novel data collection methods. Environmental DNA (eDNA) from snow tracks (footprints in snow) has identified species based on mitochondrial DNA, yet its utility for individual-based analyses remains unsolved due to challenges accessing the nuclear genome. We present a protocol for capturing nuclear eDNA from polar bear, Eurasian lynx and snow leopard snow tracks and verify it through genotyping at a selection of microsatellite markers. We successfully retrieved nuclear eDNA from 87.5% (21/24) of wild polar bear snow tracks, 59.1% (26/44) of wild Eurasian lynx snow tracks, and the single snow leopard sampled. We genotyped over half of all wild polar bear samples (54.2%, 13/24) at five loci, and 11% (9/44) of wild lynx samples and the snow leopard at three loci. Genotyping success from Eurasian lynx snow tracks increased to 24% when tracks were collected by trained rather than untrained personnel. Thirteen wild polar bear samples comprised 11 unique genotypes and two identical genotypes; likely representing 12 individual bears, one of which was sampled twice. Snow tracks show promise for use alongside other non-invasive and conventional methods as a reliable source of nuclear DNA for genetic mark-recapture of elusive and threatened mammals. The detailed protocol we present has utility for broadening end user groups and engaging Indigenous and local communities in species monitoring.

Abstract: Illegal trade in big cat (Panthera spp.) body parts is a prominent topic in scientific and public discourses concerning wildlife conservation. While illegal trade is generally acknowledged as a threat to big cat species, we suggest that two enabling factors have, to date, been under-considered. To that end, we discuss the roles of human-felid conflict, and “local” use in illegal trade in big cat body parts. Drawing examples from across species and regions, we look at generalities, contextual subtleties, ambiguities, and definitional complexities. We caution against underestimating the extent of “local” use of big cats and highlight the potential of conflict killings to supply body parts.

Abstract: Snow leopards (Panthera uncia) are elusive predators inhabiting high-altitude and mountainous rugged habitats. The current study was conducted in the Yanchiwan National Nature Reserve, Gansu Province, China, to assess the habitat suitability of snow leopards and identify key environmental factors inducing their distribution. Field data collected between 2019 and 2022 through scat sampling and camera trapping techniques provided insights into snow leopard habitat preferences. Spatial distribution and cluster analyses show distinct hotspots of high habitat suitability, mostly concentrated near mountainous landscapes. While altitude remains a critical determinant, with places above 3300 m showing increased habitat suitability, other factors such as soil type, human footprint, forest cover, prey availability, and human disturbance also play important roles. These variables influence ecological dynamics and are required to assess and manage snow leopard habitats. The MaxEnt model has helped us to better grasp these issues, particularly the enormous impact of human activities on habitat suitability. The current study highlights the importance of altitude in determining snow leopard habitat preferences and distribution patterns in the reserve. Furthermore, the study underscores the significance of considering elevation in conservation planning and management strategies for snow leopards, particularly in mountainous regions. By combining complete environmental data with innovative modeling tools, this study not only improves local conservation efforts but also serves as a model for similar wildlife conservation initiatives around the world. By understanding the environmental factors driving snow leopard distribution, conservation efforts can be more efficiently directed to ensure the long-term survival of this endangered species. This study provides valuable insights for evidence-based conservation efforts to safeguard the habitats of snow leopards amidst emerging anthropogenic pressure and environmental fluctuations.

Abstract: The snow leopard has never been common, but there may be fewer than 4,000 left in its Himalayan habitat, and poaching and tourism-related development in the region could drive its numbers down further.