Abstract: The Ladakh urial (Ovis vignei vignei) is a highly endangered animal (IUCN Red List 2000) listed in the Appendix 1 of CITES and Schedule 1 of the Indian Wildlife Protection Act 1972. Its numbers had been reduced to a few hundred individuals in the 1960s and 70s through hunting for trophies and meat (Fox et al. 1991, Mallon 1983, Chundawat and Qureshi 1999, IUCN Red List 2000). However, with the protection bestowed by the IWPA 1972, and resultant decrease in hunting, the population seems to have shown a marginal increase to about 1000-1500 individuals in its range in Ladakh (Chundawat and Qureshi 1999, IUCN Red List 2000). Although the species had in the past, been able to coexist with the predominantly Buddhist society of Ladakh, the recent increase in the population of both humans and their livestock has placed immense pressures on its habitat (Shackleton 1997, Chundawat and Qureshi 1999, Raghavan and Bhatnagar 2003). This is especially important considering that the Ladakh urial habitat coincides with the areas of maximum human activity in terms of settlements, agriculture, pastoralism and development, in Ladakh (Fox et al. 1991, Chundawat and Qureshi 1999, Raghavan and Bhatnagar 2003). Increased developmental activities such as construction of roads, dams, and military bases in these areas have also increased the access to their habitat. This has consequently made the species more vulnerable to the threats of poaching and habitat destruction (Fox et al. 1991, Chundawat and Qureshi 1999, Raghavan and Bhatnagar 2002). Pressure from increased livestock grazing is one of the major threats faced by the species today (Shackleton 1997, Fox et al. 1991, Mallon 1983, IUCN Red List 2000 Chundawat and Qureshi 1999, Raghavan and Bhatnagar 2003). In the impoverished habitat provided by the Trans-Himalayas, there is great competition for the scarce resources between various animal species surviving here (Fox 1996, Mishra 2001). The presence of livestock intensifies this competition and can either force the species out of its niche (competitive exclusion) by displacing it from that area or resource, or lead to partitioning of resources between the species, spatially or temporally, for coexistence (Begon et al. 1986, Gause 1934).

Abstract: The existence of a trans-boundary population of the snow leopard (Panthera uncia) that inhabits the massifs of Tsagaanshuvuut (Mongolia) – Tsagan-Shibetu (Russia) was determined through non-invasive genetic analysis of scat samples and by studying the structure of territory use by a collared female individual. The genetic analysis included species identification of samples through sequencing of a fragment of the cytochrome b gene and individual identification using a panel of 8 microsatellites. The home range of a female snow leopard marked with a satellite Global Positioning System (GPS) collar was represented by the minimum convex polygon method (MCP) 100, the MCP 95 method and the fixed kernel 95 method. The results revealed insignificant genetic differentiation between snow leopards that inhabit both massifs (minimal fixation index [FST]), and the data testify to the unity of the cross-border group. Moreover, 5 common individuals were identified from Mongolian and Russian territories. This finding clearly shows that their home range includes territories of both countries. In addition, regular movement of a collared snow leopard in Mongolia and Russia confirmed the existence of a cross-border snow leopard group. These data support that trans-boundary conservation is important for snow leopards in both countries. We conclude that it is crucial for Russia to study the northern range of snow leopards in Asia.

Abstract: The data on spreading, numbers and population density of snow leopard in Kazakhstan are given in this article. The total number of the snow leopard in Kazakhstan is evaluated in 100-110 individuals. The everywhere occurred numbers' reduction under the influence of the anthropogenic factors is observed. The snow leopard' inhabitation area varies from 20 to 120 square kilometers depending on its regions. Sex and composition of the population and its aggregative behavior are given. The dynamics of numbers and mortality are estimated.

Abstract: The current study in Mongolia is truly groundbreaking, in that it shows that the problem of commercial wildlife trade is also vast, unsustainable, and a major threat to wildlife populations in other areas. This paper's Executive Summary briefs the topics of wildlife trade in Mongolia, fur trade, medicinal trade, game meat trade, trophy and sport hunting, trade chains and markets, trade sustainability, impacts of wildlife trade on biodiversity conservation, impacts of trade on rural livelihoods, enabling wildlife management, and management recommendations. The main content of the paper includes: wildlife trade survey methods, a history of wildlife trade in Mongolia, wildlife take and trade today, enabling wildlife management, and recommendations and priority actions. The recommendations have been divided into six separate sections, including (1) cross-cutting recommendations, (2) international trade enforcement, (3) domestic trade enforcement, (4) hunting management, (5) trophy and sport hunting management, and (6) community-based approaches. Each section identifies short-term, long-term, and regulatory goals in order of priority within each subsection.

Abstract: Spatial capture–recapture (SCR) methods use the location of
detectors (camera traps, hair snares and live-capture traps) and the
locations at which animals were detected (their spatial capture
histories) to estimate animal density. Despite the often large expense
and effort involved in placing detectors in a landscape, there has been
relatively little work on how detectors should be located. A natural
criterion is to place traps so as to maximize the precision of density
estimators, but the lack of a closed-form expression for precision has
made optimizing this criterion computationally demanding. 2. Recent
results by Efford and Boulanger (2019) show that precision can be well
approximated by a function of the expected number of detected
individuals and expected number of recapture events, both of which can
be evaluated at low computational cost. We use these results to develop
a method for obtaining survey designs that optimize this approximate
precision for SCR studies using count or binary proximity detectors, or
multi-catch traps. 3. We show how the basic design protocol can be
extended to incorporate spatially varying distributions of activity
centres and animal detectability. We illustrate our approach by
simulating from a camera trap study of snow leopards in Mongolia and
comparing estimates from our designs to those generated by regular or
optimized grid designs. Optimizing detector placement increased the
number of detected individuals and recaptures, but this did not always
lead to more precise density estimators due to less precise estimation
of the effective sampling area. In most cases, the precision of density
estimators was comparable to that obtained with grid designs, with
improvement in some scenarios where approximate CV(¬D) < 20% and density
varied spatially. 4. Designs generated using our approach are
transparent and statistically grounded. They can be produced for survey
regions of any shape, adapt to known information about animal density
and detectability, and are potentially easier and less costly to
implement. We recommend their use as good, flexible candidate designs
for SCR surveys when reasonable knowledge of model parameters exists. We
provide software for researchers to construct their own designs, in the
form of updates to design functions in the r package oSCR.