Abstract: Irbis is a very endangered species in Uzbekistan. The article provides a brief description of the snow leopard appearance and distribution. Reasons for reduction of snow leopard population is reduction of ungulate populations it preys on ibex and wild sheep and anthropogenic disturbance. Hunting for snow leopard is prohibited everywhere.

Abstract: All natural zones are represented in the mountains of Central Asia: deserts, semi-deserts, steppes, meadows, forests and shrubs, sub-alpine zones, alpine zones. Irbis (snow leopard) is a typical inhabitant of highlands. In the USSR, snow leopard is distributed in the mountains of Central Asia and southern Siberia. Outside the country this species is met in the Himalayas, Tibet, mountains of Mongolia. It is rare everywhere. The annual world trade is less than 1,000 animals. Being a non-numerous species, it causes negligible damage to farming and hunting industry.

Abstract: This documents contains a review of the snow leopard's distribution, status and habitat in Mongolia, describes threats and conservation needs of the species, and outlines presently implemented actions. Five major threats are identified: 1) Poaching 2) loss of prey 3) degradation, fragmentation and loss of habitat 4) conflict with herders 5) lack of public awareness. Actions to mitigate the five major threats are recommended and future conservation priorities are set.

Abstract: 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.