Abstract: This study was aimed at assessing the status of Snow leopard, its major prey base, and the extent of human-Snow leopard conflict and major threats to the wildlife in north Chitral (Torkhow valley) Pakistan. Snow leopard occurrence was conformed through sign transect surveys i.e. SLIMS. Based on the data collected the number of Snow leopards in this survey block (1022 Kmý) is estimated to be 2-3 animals. Comparing this estimate with the available data from other parts of the district the population of snow leopard in Chitral district was count to be 36 animals. Livestock depredation reports collected from the area reflect the existence of human-snow leopard conflict and 138 cases were recorded affecting 102 families (in a period of eight years, 2001-2008). Ungulates (Himalayan Ibex) rut season surveys were conducted in coordination with NWFP Wildlife department. A total of 429 animals were counted using direct count (point method) surveys. Other snow leopard prey species recorded include marmot, hare, and game birds. Signs of other carnivores i.e. wolf, jackal, and fox were also noticed. Major threats to the survival of wildlife especially snow leopard reckoned include retaliatory killing (Shooting, Poisoning), poaching, loss of natural prey, habitat degradation (over grazing, fodder and fuel wood collection), lack of awareness, and over population. GIS map of the study area was developed highlighting the area searched for Snow leopard and its prey species. Capacity of the Wildlife Department staff was built in conducting SLIMS and ungulate surveys through class room and on field training. Awareness regarding the importance of wildlife conservation was highlighted to the students, teachers and general community through lectures and distribution of resource materials developed by WWF-Pakistan.

Abstract: The high altitudes of Arunachal Pradesh,India, located in the Eastern Himalaya biodiversity hotspot, remain zoologically unexplored and unprotected. We report results of recent mammal surveys in the high altitude habitats of western Arunachal Pradesh. A total of 35 mammal species (including 12 carnivores, 10 ungulates and 5 primates) were recorded, of which 13 are categorized as Endangered or Vulnerable on the IUCN Red List. One species of primate, the Arunachal macaque Macaca munzala, is new to science and the Chinese goral Nemorhaedus caudatus is a new addition to the ungulate fauna of the Indian subcontinent. We documented peoples' dependence on natural resources for grazing and extraction of timber and medicinal plants. The region's mammals are threatened by widespread hunting. The snow leopard Uncia uncia and dhole Cuon alpinus are also persecuted in retaliation for livestock depredation. The tiger Panthera tigris, earlier reported from the lower valleys, is now apparently extinct there, and range reductions over the last two decades are reported for bharal Pseudois nayaur and musk deer Moschus sp.. Based on mammal species richness, extent of high altitude habitat, and levels of anthropogenic disturbance, we identified a potential site for the creation of Arunachal's first high altitude wildlife reserve (815 km2). Community-based efforts that provide incentives for conservation-friendly practices could work in this area, and conservation awareness programmes are required, not just amongst the local communities and schools but for politicians, bureaucrats and the army.

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.

Abstract: Snow leopard conservation work in Bhutan dates back to 1999 and 2000 when the International Snow Leopard Trust-in collaboration with the Royal Government of Bhutan and World Wildlife Fund-initiated a training workshop. More than 30 government staff were trained in SLIMS survey techniques. As a part of the training exercise, a preliminary survey on snow leopard was also carried out using the SLIMS methods in Jigme Dorji Wangchuck National Park. Based on the survey results, we estimated there was a population of 100 snow leopards in the wild and 10,000 km2 of habitat. In 2005, World Wildlife Fund (WWF) organized the WWF/South Asia Regional Workshop on Snow leopard Conservation in Bhutan. Both regional (Bhutan, India, China, Nepal and Pakistan) and international experts revisited the snow leopard programs and developed a work plan for the overall conservation of the snow leopard in the region. This led to WWF's Regional Snow leopard Conservation Strategy. WWF is pleased to submit our final report to the International Snow Leopard Trust on the oneyear, $8,000 grant in support of Snow Leopard and Prey Population Conservation in Bhutan. With the support of the Snow Leopard Trust, we have made great strides towards achieving our goal for this project: To determine the current status of snow leopard and ungulate prey populations in prime snow leopard habitats. Major accomplishments and activities completed thanks to the generous support of the International Snow Leopard Trust include:
 Signed of a Terms of Reference between Royal Government, International Snow Leopard
Trust – India, World Wildlife Fund and International Snow Leopard Trust -US;
 Developed a joint revised project work plan; and
 Purchased basic field supplies and equipment needed for the surveys planned.

Abstract: Nepal's snow leopards (Uncia uncia) are mostly found along the northern border with Tibet (China). The largest populations are in Dolpa, Mugu, Manang, and Myagdi Districts. Potential habitat totals about 30,000 square kilometers. Numbers are estimated at 300-500, but surveys are urgently needed to confirm this rough guess. Like elsewhere, the primary threats center on poaching, depletion of natural prey, livestock depredation and resultant retributive killing of snow leopards by herders, and the lack of public awareness and support for conserving snow leoaprds, especially among local herders.