Understanding carnivore interactions in a cold arid trans‐Himalayan landscape: What drives co‐existence patterns within predator guild along varying resource gradients?

Abstract Predators compete for resources aggressively, forming trophic hierarchies that shape the structure of an ecosystem. Competitive interactions between species are modified in the human‐altered environment and become particularly important where an introduced predator can have negative effects on native predator and prey species. The trans‐Himalayan region of northern India has seen significant development in tourism and associated infrastructure over the last two decades, resulting in many changes to the natural setting of the landscape. While tourism, combined with unmanaged garbage can facilitate red fox (Vulpes vulpes), it also allows free‐ranging dogs (Canis lupus familiaris), an introduced mesopredator to thrive, possibly more than the native red fox. We look at the little‐known competitive dynamics of these two meso‐carnivores, as well as their intra‐guild interactions with the region's top carnivores, the snow leopard (Panthera uncia) and the Himalayan wolf (Canis lupus chanco). To study interactions between these four carnivores, we performed multispecies occupancy modeling and analyzed spatiotemporal interactions between these predators using camera trap data. We also collected scat samples to calculate dietary niche overlaps and determine the extent of competition for food resources between these carnivores. The study found that, after controlling for habitat and prey covariates, red fox site use was related positively to snow leopard site use, but negatively to dog and wolf site use. In addition, site use of the dog was associated negatively with top predators, that is, snow leopard and Himalayan wolf, while top predators themselves related negatively in their site use. As anthropogenic impacts increase, we find that these predators coexist in this resource‐scarce landscape through dietary or spatiotemporal segregation, implying competition for limited resources. Our research adds to the scant ecological knowledge of the predators in the region and improves our understanding of community dynamics in human‐altered ecosystems

Monitoring diversity and abundance of mammals with camera-traps: a case study of Manas National Park, Assam, India

Information on the status and distribution of species within a geographical area is vital for developing effective conservation plans. We conducted camera-trapping (n = 473) to determine diversity, species composition, relative abundance index, sampling effort, and conservation status of mammals in forested habitats of Manas National Park, Assam, India. Camera stations accumulated data over 11,388 trap nights over three sampling years: 2017–2019. Camera-traps recorded 34 mammalian species belonging to seven orders, 15 families, and 29 genera, with 22,738 independent records. Among them, 17 species are globally threatened or 50% of the recorded species. The species accumulation curve reached an asymptote, indicating an adequate sampling design for obtaining a robust inventory of the mammalian community. Despite a history of ethnopolitical conflict, almost all mammals expected to occur in the park were detected. Our study will enable future evaluations of the recovery process in terms of changes in mammal abundance over time

Revisiting the Woolly wolf (Canis lupus chanco) phylogeny in Himalaya: Addressing taxonomy, spatial extent and distribution of an ancient lineage in Asia.

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

Modeling Potential Impacts of Climate Change on the Distribution of Wooly Wolf (Canis lupus chanco)

The Central Asian wolves form a cohort within the wolf-dog clade known as the wooly wolf (Canis lupus chanco). These wolves are poorly studied and their current extent and distribution remain unknown. Apex predators already existing at higher elevations like wooly wolves can be severely affected by climate change because of the absence of suitable refuge. Concomitantly, in the era of Anthropocene, the change in land use land cover (LULC) is rapidly increasing. Even the most adaptable species occurring in human-dominated landscapes may fail to survive under the combined impact of both climate change and human pressure. We collected 3,776 presence locations of the wooly wolf across its range from published literature and compiled 39 predictor variables for species distribution modeling, which included anthropogenic factors, climatic, vegetation, and topographic features. We predicted the change in their distribution under different anthropogenic factors, climate change, and land-use land-cover change scenarios. Wolf showed affinity toward areas with low to moderately warm temperatures and higher precipitations. It showed negative relationships with forests and farmlands. Our future projections showed an expansion of wolf distribution and habitat suitability under the combined effects of future climate and LULC change. Myanmar and Russia had the introduction of high and medium suitability areas for the wooly wolf in future scenarios. Uzbekistan and Kazakhstan showed the consistent loss in high suitability areas while Mongolia and Bhutan had the largest gain in high suitability areas. The study holds great significance for the protection and management of this species and also provides opportunities to explore the impact on associated species.This research was supported by the Wildlife Institute of India. We are thankful to the Director and Dean, Wildlife Institute of India, for support and encouragement. This work was carried out under the project “Response to Anthropocene and Climate Change: Movement Ecology of Selected Mammal Species in the Indian Himalayan region” funded by the National Mission on Himalayan Studies (NMHS).Peer reviewe

Mean Jacobs' index values (±1 S.E.) for prey species of the snow leopard at two or more sites.

<p>Black illustrates significantly preferred prey, open bars represent species killed in proportion to their availability and stippled bars (or no bar) indicate significantly avoided prey species. As described in the text, we analysed the data of Siberian ibex and blue sheep twice to remove one outlying result for each.</p

Sites and source of data used for this study.

<p>25 studies were referred spanning four zones in the snow leopard's distribution <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0088349#pone.0088349-Anwar1" target="_blank">[18]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0088349#pone.0088349-Maheshwari1" target="_blank">[ 54]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0088349#pone.0088349-Lhagvasuren1" target="_blank">[63]</a>.</p

Flow chart of process employed for the current study.

<p>Flow chart of process employed for the current study.</p

Prey weight and relative occurrence of prey in snow leopard scat.

<p>Prey weights used were ¾ the body mass of average adult female of each prey species. Double hump indicates that snow leopard feeds primarily on large prey but may shift to small-bodied prey sub-optimally.</p

Segmented model of the relationship between the mass-rank of each prey species and the corresponding cumulative Jacobs' Index +1 value for snow leopard.

<p>Actual prey species' masses, which correspond to the lowest, break-point, and highest prey mass-ranks are indicated.</p