Abstract: China may hold a greater proportion of the global snow leopard Panthera uncia population than any other country, with the area of good quality suitable habitat, estimated at nearly 300,000 km2, comprising .50% of that available across the species' entire range. We can now reconfirm the presence of snow leopard in the Taxkurgan area of Xinjiang Province in north-west China after a period of 20 years.

Abstract: Caspian tiger, cheetah, moral have disappeared from the region's fauna. Species such as hyena, leopard, manul are endangered, honey badger and caracal available only on the south of Karakalpakstan, lynx, snow leopard and saiga are rare species. The implemented protection measures helped Iranian otter, Bukhara red deer, marchor, and Severtsev's sheep escape a total extermination. To preserve many valuable animals in Uzbekistan small investments in their habitats improvement are required. Nature reserves and preserves occupy a total area of more than 220,000 ha in the country. All rare species of Central Asia's fauna are under protection of the state.

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: Bounded by two of the world's highest mountain ranges, the Great Himalaya and the Karakoram, Ladakh is a land of exhilarating mountain landscapes, rocky gorges and a unique cultural heritage. It is also home to distinctive wildlife such as the snow leopard, blue sheep and Tibetan wild ass, all living in a unique high altitude desert ecosystem. Not surprisingly, Ladakh is becoming a sought after tourist destination for international and domestic visitors alike. Over the past two decades tourism has grown substantially, although erratically, with both positive and less positive results for Ladakh's environment and people. People are recognizing that it is important to act now and engage in an informed dialogue in order to conserve the natural and cultural resources on which the future of tourism and related incomes depend. The Snow Leopard Conservancy (SLC) is working in collaboration with local communities and nongovernmental organizations to foster co-existence between people and predators like the endangered snow leopard by reducing livestock depredation losses and improving household incomes in environmentally friendly, socially responsible and economically viable ways. Well-balanced tourism is one income generating option.

Abstract: Blue sheep (Pseudois nayaur) are the main prey of the endangered snow leopard (Panthera uncia) as well as an important game species in Nepal. A knowledge of how blue sheep utilize their habitat is essential for the scientific management of the sheep and for the conservation of the snow leopard, but we only have a limited understanding of this aspect of blue sheep ecology. I studied the habitat use pattern of blue sheep by direct observation in the Anna-purna Conservation Area, Nepal where they occur sympatrically with the snow leopard. The sheep used grassland habitats more frequently during pre-parturition (spring) and post-parturition (autumn) than other habitat types, but scrub and grassland habitats were used equally frequently during the rut (winter). The sheep used smooth undulating slopes of medium steepness (<40 degrees) on southerly aspects within the elevation range of 4,200-4,600 m most frequently in all seasons, and there was no evidence of seasonal migration along the elevation gradient. When not in broken landforms (e.g., cliff, landslides), the sheep maintained proximity (less than or equal to 150 m) to such features suggesting their importance as escape cover (i.e., from predators). The use of habitat components by blue sheep appeared to be related to the distribution of foraging areas and escape cover.