Abstract: We conducted surveys above 3000 m elevation in eight protected areas of Uttarakhand and Himachal Pradesh. These surveys provide new information on snow leopard in Uttarakhand on the basis of indirect evidence such as pugmark and scat. Snow leopard evidence (n = 13) were found between 3190 and 4115 m elevation. On an average, scats (n = 09) of snow leopard were found for every 56 km walked and pugmarks (n = 04) for every 126 km walked. Altogether, about 39% of the evidence were found on the hill-slope followed by valley floor (30%), cliff (15%) and 8% from both stream bed and scree slope. Genetic analysis of the scats identified three different individuals by using snow leopard specific primers. Snow leopard-human conflicts were assessed through questionnaire based interviews of shepherds from Govind Pashu Vihar Wildlife Sanctuary, Askot Wildlife Sanctuary and Nanda Devi Biosphere Reserve areas of Uttarakhand. Surveys revealed that livestock depredation (mule, goat and sheep) is the only cause of snow leopard-human conflicts and contributed 36% of the diet of snow leopard. Blue sheep and rodents together comprised 36.4% of the total diet. We found that 68.1% of the surveyed area was used for pastoral activities in Uttarakhand and Himachal Pradesh and 12.3% area was under tourism, defence and developmental activities.

Abstract: I studied snow leopards (Panthera uncia) and blue sheep (Pseudois nayaur) in Manang District, Annapurna Conservation Area, Nepal, to estimate numbers and analyze predatorprey interactions. Five to seven adult leopards used the 105-km2 study area, a density of 4.8 to 6.7 leopards/100 km2. Density of blue sheep was 6.6-10.2 sheep/km2, and biomass density was 304 kg/km2. Estimated relative biomass consumed by snow leopards suggested that blue sheep were the most important prey; marmots (Marmota himalayana) also contributed significantly to the diet of snow leopards. Snow leopards in Manang were estimated to harvest 9-20% of total biomass and 11-24% of total number of blue sheep annually. Snow leopard :blue sheep ratio was 1 :1 14-1 :159 on a weight basis, which was considered sustainable given the importance of small mammals in the leopard's diet and the absence of other competing predators.

Abstract: Direct and indirect interactions among predators affect predator fitness, distribution, and overall community structure. Yet, outside of experimental settings, such interactions are difficult to observe and thus poorly understood. Patterns of niche overlap among predators reflect and shape community interactions and may therefore help elucidate the nature and intensity of intraguild interactions. To better understand the coexistence of two apex predators, snow leopards (Panthera uncia) and wolves (Canis lupus), we investigated their spatial, temporal, and dietary niche overlap in summer in the Pamir Mountains of Tajikistan. We estimated population- level space use via spatial capture–recapture models based on noninvasive genetics and camera traps, diel activity patterns based on camera trap detections, and diet composition from prey remains in carnivore scats, from which we estimated coefficients between 0 and 1 for overlap in space, time, and diet, respectively. Snow leopards and wolves displayed moderate spatial partitioning (0.26, 95% confidence interval [CI]: 0.17–37), but overlapping temporal (0.77, 95% CI: 0.64–0.90) and dietary (0.97, 95% CI: 0.80–0.99) niches. Both predators relied on seasonally abundant marmots (Marmota caudata) rather than wild ungulates, their typical primary prey, suggesting that despite patterns of overlap that were superficially conducive to exploitation competition and predator facilitation, prey were likely not a limiting factor. Therefore, prey-mediated interactions, if present, were unlikely to be a major structuring force in the ecosystem. By implication, carnivore conservation planning and monitoring in the mountains of Central Asia should more fully account for the seasonal importance of marmots in the ecosystem.

Abstract: The secretive nature of snow leopards (Uncia uncia) makes them difficult to monitor, yet conservation efforts require accurate and precise methods to estimate abundance. We assessed accuracy of Snow Leopard Information Management System (SLIMS) sign surveys by comparing them with 4 methods for estimating snow leopard abundance: predator:prey biomass ratios, capture-recapture density estimation, photo-capture rate, and individual identification through genetic analysis. We recorded snow leopard sign during standardized surveys in the SaryChat Zapovednik, the Jangart hunting reserve, and the Tomur Strictly Protected Area, in the Tien Shan Mountains of Kyrgyzstan and China. During June-December 2005, adjusted sign averaged 46.3 (SaryChat), 94.6 (Jangart), and 150.8 (Tomur) occurrences/km. We used
counts of ibex (Capra ibex) and argali (Ovis ammon) to estimate available prey biomass and subsequent potential snow leopard densities of 8.7 (SaryChat), 1.0 (Jangart), and 1.1 (Tomur) snow leopards/100 km2. Photo capture-recapture density estimates were 0.15 (n = 1 identified individual/1 photo), 0.87 (n = 4/13), and 0.74 (n = 5/6) individuals/100 km2 in SaryChat, Jangart, and Tomur, respectively. Photo-capture rates
(photos/100 trap-nights) were 0.09 (SaryChat), 0.93 (Jangart), and 2.37 (Tomur). Genetic analysis of snow leopard fecal samples provided minimum population sizes of 3 (SaryChat), 5 (Jangart), and 9 (Tomur) snow leopards. These results suggest SLIMS sign surveys may be affected by observer bias and environmental variance. However, when such bias and variation are accounted for, sign surveys indicate relative abundances similar to photo rates and genetic individual identification results. Density or abundance estimates based on capture-recapture or ungulate biomass did not agree with other indices of abundance. Confidence in estimated densities, or even detection of significant changes in abundance of snow leopard, will require more effort and better documentation.