Abstract: The Pallas’s cat (Otocolobus manul) is one of the most understudied taxa in the Felidae family. The species is currently assessed as being of “Least Concern” in the IUCN Red List, but this assessment is based on incomplete data. Additional ecological and genetic information is necessary for the long-term in situ and ex situ conservation of this species. We identified 29 microsatellite loci with sufficient diversity to enable studies into the individual identification, population structure, and phylogeography of Pallas’s cats. These microsatellites were genotyped on six wild Pallas’s cats from the Tibet Autonomous Region and Mongolia and ten cats from a United States zoo-managed population that originated in Russia and Mongolia. Additionally, we examined diversity in a 91 bp segment of the mitochondrial 12S ribosomal RNA (MT-RNR1) locus and a hypoxia-related gene, endothelial PAS domain protein 1 (EPAS1). Based on the microsatellite and MT-RNR1 loci, we established that the Pallas’s cat displays moderate genetic diversity. Intriguingly, we found that the Pallas’s cats had one unique nonsynonymous substitution in EPAS1 not present in snow leopards (Panthera uncia) or domestic cats (Felis catus). The analysis of the zoo-managed population indicated reduced genetic diversity compared to wild individuals. The genetic information from this study is a valuable resource for future research into and the conservation of the Pallas’s cat.

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: Surveying snow leopard prey species such as argali, ibex or blue sheep through traditional ground-based observations is time-consuming, expensive, and challenging. Aerial drones present a promising alternative. We tested using thermal-sensor- equipped drones to count ungulate populations in Mongolia’s Ikh Nart Nature Reserve, surveying ~400km of transects along five fixed routes for forty-three missions. Drones detected 235 prey animals and 209 livestock; 26% of all sightings were in areas that would not have been visible to hypothetical ground-based observers. Our tests reinforced the utility of drones for counting snow leopard prey and highlighted important issues and future advances for supporting largely autonomous prey surveys. We recommend biologists build upon existing technology to attain an inexpensive, easy to use, and field ready set of equipment and procedures that can reliably improve or replace traditional transect or point count methods for large prey species.

Abstract: Accurately assessing the status of threatened species requires reliable population estimates. Despite this necessity, only a small proportion of the global distribution range of the vulnerable snow leopard (Panthera uncia) has been systematically sampled. The Indian section of the Greater Himalayas, which includes Kishtwar High Altitude National Park (KHANP), harbours potential snow leopard habitat. Nevertheless, there has been limited ecological and conservation research focusing on species that are specific to KHANP, as well as limited research on the broader biodiversity of the Greater Himalayas. We used Spatially Explicit Capture‐Recapture (SECR) models to provide—to our knowledge—the first robust snow leopard population density and abundance estimates from KHANP. We also provide a Relative Abundance Index (RAI) for non‐volant mammals (excluding small rodents). Our study sampled three catchments within the Dachhan region of KHANP—Kibber, Nanth and Kiyar—using 44 cameras over a 45‐day period between May and June 2023. We identified four unique snow leopard individuals across 15 detections in nine camera locations. SECR analysis estimated a density of 0.50 snow leopards per 100 km2 (95% confidence interval: 0.13–1.86), corresponding to an abundance of four individual (4–9) adults. Camera trapping revealed a total of 16 mammal species, including the endangered Kashmir musk deer (Moschus cupreus). Marmots (Marmota caudata) had the highest RAI of 21.3 (±0.2). Although the estimated density and abundance of snow leopards in our study area had relatively wide 95% confidence intervals, our combined results of snow leopard densities and RAIs of prey species such as ibex and marmots indicate that KHANP is a potentially important area for snow leopards. Given the geopolitical history of Jammu and Kashmir in India, the region where KHANP is located, wildlife research remains a low priority. We hope our study encourages authorities to support further research. This study is an initial step towards evaluating the potential of KHANP as a conservation landscape under the Government of India's Project Snow Leopard.

Abstract: Adaptations to arid environments, involving strategies to conserve and utilize water, are vital for wildlife. Water availability in these regions depends on seasonal rainfall, and subsequently affect species distribution and behavior. This note documents a snow leopard (Panthera uncia) in the Tost Mountains of southern Mongolia digging for water, a previously undocumented behavior. The first author identified evidence of snow leopards digging for water. Camera traps were then used in an attempt to document this behavior. Unique pelt patterns identified one snow leopard digging for water in the summer of 2022, with drinking observed. Other species also drank at the site, suggesting snow leopards could act as ecological engineers by providing water for other species. Four other snow leopards were observed to visit the site in the late fall, winter, and early spring of 2022 and 2023. These snow leopards did not dig or drink, but this may largely have been related to subzero temperatures (-15°C to -30°C) and the ground being frozen for most of this period. The snow leopard digging for and exposing water may help to support biodiversity in desert ecosystems. However, further research is needed to determine its prevalence and impact. Understanding these strategies is crucial for conservation, especially with increasing droughts and extreme weather in arid landscapes.