Abstract: Snow leopards (Uncia uncia) are highly cryptic and occupy remote inaccessible habitat, making studying the cats difficult in the extreme. Yet sound knowledge of the cat's ecology, behavior and habitat needs is required to intelligently conserve them. This information is lacking for snow leopards, and until recently so was the means to fill that knowledge gap. Two long-term studies of snow leopards using VHF radio collars have been undertaken in Nepal (1980s) and Mongolia (1990s) but logistical and technological constraints made the findings of both studies equivocal. Technological advances in the interim, such as GPS collars which report data via satellite, make studies of snow leopards more promising, at least in theory.

Abstract: The snow leopard (Uncia uncial Schreber, 1776) is the most poorly studied species of the cat family in the world and, in particular, in Russia, where the northern periphery of the species area (no more than 3% of it) is located in the Altai-Hangai-Sayan range [1]. It is generally known that the existing data on the Russian part of the snow leopard population have never been a result of targeted studies; at best, they have been based on recording the traces of the snow leopard vital activity [2]. This is explained by the snow leopard's elusive behavior, inaccessibility of its habitats for humans, and its naturally small total numbers in the entire species area. All published data on the population status of the snow leopard in Russia, from the first descriptions of the species [3-6] to the latest studies [7, 8] are subjective, often speculative, and are not confirmed by
quantitative estimates. It is obvious, however, that every accurate observation of this animal is of particular interest [9]. The purpose of our study was to determine the structure and size of the population group presumably inhabiting the Western Sayan mountain ridge at the northern boundary of the species area

Abstract: Livestock production is the primary source of livelihood and income in most of the high steppe and alpine regions of the Indian Trans-Himalaya. In some areas, especially those established or proposed for biodiversity conservation, recent increases in populations of domestic livestock, primarily sheep and goats, have raised concern about domestic animals competitively excluding wild herbivores from the rangelands. We
evaluated the influence of domestic sheep and goat grazing on the habitat use and time budget of the endangered Tibetan argali Ovis ammon hodgsoni in the proposed Gya-Miru Wildlife Sanctuary, Ladakh, India. We asked if the domestic sheep and goat grazing and collateral human activities relegate the argali to suboptimal habitats, and alter their foraging time budgets. Data were collected on habitat use and time budget of a population of c. 50 argalis before and after c. 2,000 sheep and goats moved onto their winter pasture in the Tsabra catchment of the aforementioned reserve. Following the introduction of domestic sheep and goats, argalis continued to use the same catchment but shifted to steeper habitats, closer to cliffs, with lower vegetation cover, thus abandoning previously used plant communities with denser cover. Argalis' active time spent foraging also decreased by 10% in response to the presence of livestock. These results suggest a clear disturbance effect of livestock on argalis, and indicate a potential for competition, conceivably a significant disadvantage for argalis in winter when forage availability is minimal.

Abstract: The snow leopard (Panthera uncia) and blue sheep (Pseudois nayaur) are the inhabitants of remote areas at higher altitudes with extreme geographic and climatic conditions. The habitats of these least-studied species are crucial for sustaining the Himalayan ecosystem. We employed the Maximum Entropy (MaxEnt) species distribution model to predict the potential habitat suitability of snow leopards and blue sheep and extracted common overlapped niches. For this, we utilised presence location, bio-climatic and environmental variables, and correlation analysis was applied to reduce the negative impact of multicollinearity. A total of 134 presence locations of snow leopards and 64 for blue sheep were selected from the Global Biodiversity Information Facility (GBIF). The annual mean temperature (Bio1) was found to be the most useful and highly influential factor to predict the potential habitat suitability of snow leopards. Annual mean temperature, annual precipitation and isothermality were the major influencing factors for blue sheep habitat suitability. Highly influential bio-climatic, topographic and environmental variables were integrated to construct the model for predicting habitat suitability. The area under the curve (AUC) values for snow leopard (0.87) and blue sheep (0.82) showed that the models are under good representation. Of the total area investigated, 47% was suitable for the blue sheep and 38% for the snow leopards. Spatial habitat assessment revealed that nearly 11% area from the predicted suitable habitat class of both species was spatially matched (overlapped), 48.6% area was unsuitable under niche overlap and 40.5% area was spatially mismatched niche. The presence of snow leopards and blue sheep in some highly suitable areas was not observed, yet such areas have the potential to sustain these elusive species. The other geographical regions interested in exploring habitat suitability may find the methodological framework adopted in this study useful for formulating an effective conservation policy and management strategy.