In human-populated landscapes worldwide, domestic dogs (Canis lupus familiaris) are the most abundant terrestrial carnivore. Although dogs have been used for the protection of livestock from wild carnivores, they have also been implicated as predators of livestock. We used a combination of methods (field surveys, interview surveys, and data from secondary sources) to examine the patterns and factors driving livestock depredation by free-ranging dogs, as well as economic losses to local communities in a Trans-Himalayan agro-pastoralist landscape in India. Our results show that livestock abundance was a better predictor of depredation in the villages than local dog abundance. Dogs mainly killed small-bodied livestock and sheep were the most selected prey. Dogs were responsible for the majority of livestock losses, with losses being comparable to that by snow leopards. This high level of conflict may disrupt community benefits from conservation programs and potentially undermine the conservation efforts in the region through a range of cascading effects.

Understanding the distribution of wildlife species and their response to diverse anthropogenic pressures is important for conservation planning and management of wildlife space in human-dominated landscapes. Assessments of anthropogenic impacts on mammals of the Indian Himalayan Region have mostly been limited to locations inside protected areas. We studied the occurrence of mammals in an unexplored landscape, the 7,586 km2 Bhagirathi basin, at an altitude of 500–5,200 m. The basin encompasses wilderness areas of various habitat types and protection status that are exposed to a range of anthropogenic pressures. Camera trapping at 209 locations during October 2015–September 2017 confirmed the occurrence of 39 species of mammals, nine of which are categorized as threatened (four Vulnerable, five Endangered) and four as Near Threatened on the IUCN Red List. We recorded five mammal species that were hitherto undocumented in Uttarakhand State: the argali Ovis ammon, Tibetan sand fox Vulpes ferrilata, woolly hare Lepus oiostolus, Eurasian lynx Lynx lynx and woolly flying squirrel Eupetaurus cinereus. In addition, we recorded two Endangered species, the dhole Cuon alpinus and tiger Panthera tigris. Threatened species such as the sambar Rusa unicolor, common leopard Panthera pardus and Asiatic black bear Ursus thibetanus occur in a wide variety of habitats despite anthropogenic disturbance. We recorded the snow leopard Panthera uncia in areas with high livestock density but temporally segregated from human activities. The musk deer Moschus spp. and Himalayan brown bear Ursus arctos isabellinus were recorded in subalpine habitats and appeared to be less affected by human and livestock presence. Our findings highlight the potential of the Bhagirathi basin as a stronghold for conservation of several threatened and rare mammal species.

Of the sub-species of Holarctic wolf, the Woolly wolf (Canis lupus chanco) is uniquely adapted to atmospheric hypoxia and widely distributed across the Himalaya, Qinghai Tibetan Plateau (QTP) and Mongolia. Taxonomic ambiguity still exists for this sub-species because of complex evolutionary history anduse of limited wild samples across its range in Himalaya. We document for the first time population genetic structure and taxonomic affinity of the wolves across western and eastern Himalayan regions from samples collected from the wild (n = 19) using mitochondrial control region (225bp). We found two haplotypes in our data, one widely distributed in the Himalaya that was shared with QTP and the other confined to Himachal Pradesh and Uttarakhand in the western Himalaya, India. After combining our data withpublished sequences (n = 83), we observed 15 haplotypes. Some of these were shared among different locations from India to QTP and a few were private to geographic locations. A phylogenetic tree indicated that Woolly wolves from India, Nepal, QTP and Mongolia are basal to other wolves with shallow divergence (K2P; 0.000-0.044) and high bootstrap values. Demographic analyses based on mismatch distribution and Bayesian skyline plots (BSP) suggested a stable population over a long time (~million years) with signs of recent declines. Regional dominance of private haplotypes across its distribution range may indicate allopatric divergence. This may be due to differences in habitat characteristics, availability of different wild prey species and differential deglaciation within the range of the Woolly wolf during historic time. Presence of basal and shallow divergence within-clade along with unique ecological requirements and adaptation to hypoxia, the Woolly wolf of Himalaya, QTP, and Mongolian regions may be considered as a distinct an Evolutionary Significant Unit (ESU). Identifying management units (MUs) is needed within its distribution range using harmonized multiple genetic data for effective conservation planning.

Throughout the Himalaya, mountain ungulates are threatened by hunting for meat and body parts, habitat loss, and competition with livestock. Accurate population estimates are important for conservation management but most of the available methods to estimate ungulate densities are difficult to implement in mountainous terrain. Here, we tested the efficacy of the recent extension of the point transect method, using camera traps for estimating density of two mountain ungulates: the group-living Himalayan blue sheep or bharal Pseudois nayaur and the solitary Himalayan musk deer Moschus leucogaster. We deployed camera traps in 2017–2018 for the bharal (summer: 21 locations; winter: 25) in the trans-Himalayan region (3,000–5,000 m) and in 2018–2019 for the musk deer (summer: 30 locations; winter: 28) in subalpine habitats (2,500–3,500 m) in the Upper Bhagirathi basin, Uttarakhand, India. Using distance sampling with camera traps, we estimated the bharal population to be 0.51 ± SE 0.1 individuals/km2 (CV = 0.31) in summer and 0.64 ± SE 0.2 individuals/km2 (CV = 0.37) in winter. For musk deer, the estimated density was 0.4 ± SE 0.1 individuals/km2 (CV = 0.34) in summer and 0.1 ± SE 0.05 individuals/km2 (CV = 0.48) in winter. The high variability in these estimates is probably a result of the topography of the landscape and the biology of the species. We discuss the potential application of distance sampling with camera traps to estimate the density of mountain ungulates in remote and rugged terrain, and the limitations of this method.

Human modification and habitat fragmentation significantly impact large carnivores requiring large, connected habitats to persist in a landscape. Understanding species responses to such change and the protection of critical areas and connectivity they provide is essential when planning effective conservation strategies. Our study examines the spatial distribution of the snow leopard (Panthera uncia) across a gradient of protection status, anthropogenic pressures and habitat types in the Gangotri landscape (~4600 km2), Western Himalaya. Using spatial capture‐recapture modeling, we analyzed a 4‐year camera trapping dataset (2015–2019) to assess the relationship between snow leopard movement and topography and identified the conducible areas for facilitating movement across the landscape. Snow leopard density was positively associated with elevation and slope, and was higher in protected areas (summer: 1.42 SE 0.02/100km2; winter 2.15 SE 0.03 vs. summer: 0.4 SE 0.01; winter: 0.6 SE 0.01 for unprotected areas). Precipitous terrain and several prominent mountain peaks were found to be resistant to snow leopard movement. Even with a range of human activities inside protected areas, the higher density suggests a positive impact of protection. Density‐weighted connectivity showed that conducible areas are available between the Gangotri landscape and the adjacent protected areas. However, compared to protected area, these areas are relatively less used and require attention for management. We recommend regulating human activities and co‐managing pastures with local communities to revive prey base outside protected areas, especially in corridors, to ensure such areas are functionally conducive. Our study provides a framework to collectively quantitate the spatial pattern of abundance, distribution and connectivity. Our approach has broad applicability for policymakers to develop strategic plans for balancing the conservation of species, and other land uses in a multiuse landscape.