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Zhang, C., Ma, T., Ma, D. (2023). Status of the snow leopard Panthera uncia in the Qilian Mountains, Gansu Province, China. Oryx, , 1–6.
Abstract: Population density estimation is integral to the effective conservation and management of wildlife. The snow leopard Panthera uncia is categorized as Vulnerable on the IUCN Red List, and reliable information on its density is a prerequisite for its conservation and management. Little is known about the status of the snow leopard in the central and eastern Qilian Mountains, China. To address this, we estimated the population density of the snow leopard using a spatially explicit capture–recapture model based on camera trapping in Machang in the central and eastern Qilian Mountains during January–March 2019. We set up
40 camera traps and recorded 84 separate snow leopard captures over 3,024 trap-days. We identified 18 individual snow leopards and estimated their density to be 2.26/100 km. Our study provides baseline information on the snow leopard and the first population estimate for the species in the central and eastern Qilian Mountains.
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Kichloo, M. A., Sharma, K., Sharma, N. (2023). Climate casualties or human disturbance? Shrinking distribution of the three large carnivores in the Greater Himalaya. Springer – Climatic Change, 176(118), 1–17.
Abstract: Mammalian carnivores are key to our understanding of ecosystem dynamics, but most of them are threatened with extinction all over the world. Conservating large carnivores is often an arduous task considering the complex relationship between humans and carnivores, and the diverse range and reasons of threats they face. Climate change is exacerbating the situation further by interacting with most existing threats and amplifying their impacts. The Mountains of Central and South Asia are warming twice as rapidly as the rest of the northern hemisphere. There has been limited research on the effect of climate change and other variables on large carnivores. We studied the patterns in spatio-temporal distribution of three sympatric carnivores, common leopard, snow leopard, and Asiatic black bear in Kishtwar high altitude National Park, a protected area in the Great Himalayan region of Jammu and Kashmir. We investigated the effects of key habitat characteristics as well as human disturbance and climatic factors to understand the spatio-temporal change in their distributions between the early 1990s and around the year 2016–2017. We found a marked contraction in the distribution of the three carnivores between the two time periods. While snow leopard shifted upwards and further away from human settlements, common leopard and Asiatic black bear suffered higher rates of local extinctions at higher altitudes and shifted to lower areas with more vegetation, even if that brought them closer to settlements. We also found some evidence that snow leopards were less likely to have faced range contraction in areas with permanent glaciers. Our study underscores the importance of climate adaptive conservation practices for long-term management in the Greater Himalaya, including the monitoring of changes in habitat, and space-use patterns by human communities and wildlife.
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Bohnett, E., Holmberg, J., Faryabi, S. P., An, L., Ahmad, B., Rashid, W., Ostrowski, S. (2023). Comparison of two individual identification algorithms for snow leopards (Panthera uncia) after automated detection. Ecological Informatics, 77(102214), 1–14.
Abstract: Photo-identification of individual snow leopards (Panthera uncia) is the primary data source for density estimation via capture-recapture statistical methods. To identify individual snow leopards in camera trap imagery, it is necessary to match individuals from a large number of images from multiple cameras and historical catalogues, which is both time-consuming and costly. The camouflaged snow leopards also make it difficult for machine learning to classify photos, as they blend in so well with the surrounding mountain environment, rendering applicable software solutions unavailable for the species. To potentially make snow leopard individual identification available via an artificial intelligence (AI) software interface, we first trained and evaluated image classification techniques for a convolutional neural network, pose invariant embeddings (PIE) (a triplet loss network), and compared the accuracy of PIE to that of the HotSpotter algorithm (a SIFT-based algorithm). Data were acquired from a curated library of free-ranging snow leopards taken in Afghanistan between 2012 and 2019 and from captive animals in zoos in Finland, Sweden, Germany, and the United States. We discovered several flaws in the initial PIE model, such as a small amount of background matching, that was addressed, albeit likely not fixed, using background subtraction (BGS) and left-right mirroring (LR) techniques which demonstrated reasonable accuracy (Rank 1: 74% Rank-5: 92%) comparable to the Hotspotter results (Rank 1: 74% Rank 2: 84%)The PIE BGS LR model, in conjunction with Hotspotter, yielded the following results: Rank-1: 85%, Rank-5: 95%, Rank-20: 99%. In general, our findings indicate that PIE BGS LR, in conjunction with HotSpotter, can classify snow leopards more accurately than using either algorithm alone.
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Golla, T. R., Tensen, L., Vipin, Kumar, K., Kumar, S., Gaur, A. (2023). Neutral and adaptive genetic variation in Indian snow leopards, Panthera uncia. Current Science, 125(2), 204–209.
Abstract: In this study, we reveal patterns of genetic variation in snow leopards (Panthera uncia) by combining neutral (mtDNA, microsatellites) and adaptive (MHC II-DRB) genes. We collected 56 faecal samples from three locations in India. We observed moderate levels of microsatellite diversity (N = 30; A = 5.6; HO = 0.559). Nine unique MHC II-DRB sequences were identified in four snow leopard samples, of which 8 were novel. We found low levels of polymorphism in MHC class II-DRB exon, which was higher in captive (VA = 9.4%) compared to wild individuals (VA = 7.8%), likely as a result of a population bottleneck.
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Allen, M. L., Rovero, F., Oberosler, V., Augugliaro, C., Krofel, M. (2023). Effects of snow leopards (Panthera uncia) on olfactory communication of Pallas’s cats (Otocolobus manul) in the Altai Mountains, Mongolia. Behaviour, , 1–9.
Abstract: Olfactory communication is important for many solitary carnivores to delineate territories and communicate with potential mates and competitors. Pallas’s cats (Otocolobus manul) are small felids with little published research on their ecology and behaviour, including if they avoid or change behaviours due to dominant carnivores. We studied their olfactory communication and visitation at scent-marking sites using camera traps in two study areas in Mongolia. We documented four types of olfactory communication behaviours, and olfaction (sniffing) was the most frequent. Pallas’s cats used olfactory communication most frequently at sites that were not visited by snow leopards (Panthera uncia) and when they used communal scent-marking sites, they were more likely to use olfactory communication when a longer time had elapsed since the last visit by a snow leopard. This suggests that Pallas’s cats may reduce advertising their presence in response to occurrence of snow leopards, possibly to limit predation risk.
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Atzeni, L., Wang, J., Riordan, P., Shi, K., Cushman, S. A. (2023). Landscape resistance to gene flow in a snow leopard population from Qilianshan National Park, Gansu, China. Landscape Ecology, .
Abstract: Context: The accurate estimation of landscape resistance to movement is important for ecological understanding and conservation applications. Rigorous estimation of resistance requires validation and optimization. One approach uses genetic data for the optimization or validation of resistance models. Objectives We used a genetic dataset of snow leopards from China to evaluate how landscape genetics resistance models varied across genetic distances and spatial scales of analysis. We evaluated whether landscape genetics models were superior to models of resistance derived from habitat suitability or isolation-by-distance.
Methods: We regressed genetically optimized, habitat-based, and isolation-by-distance hypotheses against genetic distances using mixed effect models. We explored all subset combinations of genetically optimized variables to find the most supported resistance scenario for each genetic distance.
Results: Genetically optimized models always out-performed habitat-based and isolation-by-distance hypotheses. The choice of genetic distances influenced the apparent influence of variables, their spatial scales and their functional response shapes, producing divergent resistance scenarios. Gene flow in snow leopards was largely facilitated by areas of intermediate ruggedness at intermediate elevations corresponding to small-to-large valleys within and between the mountain ranges.
Conclusions: This study highlights that landscape genetics models provide superior estimation of functional dispersal than habitat surrogates and suggests that optimization of genetic distance should be included as an optimization routine in landscape genetics, along with variables, scales, effect size and functional response shape. Furthermore, our study provides new insights on the ecological conditions that promote gene flow in snow leopards, which expands ecological knowledge, and we hope will improve conservation planning.
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Islam, M., Sahana, M., Areendran, G., Jamir, C., Raj, K., Sajjad, H. (2023). Prediction of potential habitat suitability of snow leopard (Panthera uncia) and blue sheep (Pseudois nayaur) and niche overlap in the parts of western Himalayan region. Geo: Geography and Environment, 10(e00121), 1–15.
Abstract: The snow leopard (Panthera uncia) and blue sheep (Pseudois nayaur) are the inhabitants of remote areas at higher altitudes with extreme geographic and climatic conditions. The habitats of these least-studied species are crucial for sustaining the Himalayan ecosystem. We employed the Maximum Entropy (MaxEnt) species distribution model to predict the potential habitat suitability of snow leopards and blue sheep and extracted common overlapped niches. For this, we utilised presence location, bio-climatic and environmental variables, and correlation analysis was applied to reduce the negative impact of multicollinearity. A total of 134 presence locations of snow leopards and 64 for blue sheep were selected from the Global Biodiversity Information Facility (GBIF). The annual mean temperature (Bio1) was found to be the most useful and highly influential factor to predict the potential habitat suitability of snow leopards. Annual mean temperature, annual precipitation and isothermality were the major influencing factors for blue sheep habitat suitability. Highly influential bio-climatic, topographic and environmental variables were integrated to construct the model for predicting habitat suitability. The area under the curve (AUC) values for snow leopard (0.87) and blue sheep (0.82) showed that the models are under good representation. Of the total area investigated, 47% was suitable for the blue sheep and 38% for the snow leopards. Spatial habitat assessment revealed that nearly 11% area from the predicted suitable habitat class of both species was spatially matched (overlapped), 48.6% area was unsuitable under niche overlap and 40.5% area was spatially mismatched niche. The presence of snow leopards and blue sheep in some highly suitable areas was not observed, yet such areas have the potential to sustain these elusive species. The other geographical regions interested in exploring habitat suitability may find the methodological framework adopted in this study useful for formulating an effective conservation policy and management strategy.
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Khanyari, M., Dorjay, R., Lobzang, S. Bijoor, A., Suryawanshi, K. (2023). Co-designing conservation interventions through participatory action research in the Indian Trans-Himalaya. Ecological Solutions and Evidence, 2023;4(e12232), 1–14.
Abstract: 1. Community-based conservation, despite being more inclusive than fortress con- servation, has been criticized for being a top-down implementation of external ideas brought to local communities for conservation's benefit. This is particularly true for Changpas, the pastoral people of Changthang in trans-Himalayan India who live alongside unique wildlife.
2. Our main aim was to co-design conservation interventions through participatory action research. We worked with two Changpa communities, to understand the issues faced by them. Subsequently, we co-designed context-sensitive interventions to facilitate positive human–nature interactions. We did so by integrating the PARTNERS (Presence, Aptness, Respect, Transparency, Empathy, Responsiveness, Strategic Support) principles with the Trinity of Voice (Access, Standing and Influence).
3. In Rupsho, we facilitated focus group discussions (FGDs) led by the community. We found livestock depredation by wildlife was primarily facilitated by the weather. This led to co-designing of a new corral design, which was piloted with seven households, safeguarding 2385 pashmina goats and sheep. Approximating the value of each sheep/goat to be USD125, this intervention amounts to a significant economic protection of USD c. 42,500 for each household. This is along with intangible gains of trust, ownership and improved self-esteem.
4. In Tegazong, a restricted area adjoining the Indo-China border with no previous research records, we worked with 43 Changpa people to co-create research questions of mutual interest. Wildlife presence and reasons for livestock loss were identified as areas of mutual interest. The herders suggested they would record data in a form of their choice, for 6 months, while they live in their winter pastures. This participatory community monitoring revealed nutrition and hypothermia to be a key cause of livestock death. Subsequently, we delimited two previously untested interventions: lamb cribs and provisioning of locally sourced barley as a feed supplement. The wildlife monitoring recorded the first record of Tibetan Gazelle Procapra picticuadata, outside of their known distribution, in Tegazong.
5. We aim to highlight the benefits of co-designing projects with local communities that link research and conservation, while also discussing the challenges faced. Ultimately, such projects are needed to ensure ethical knowledge generation and conservation, which aims to be decolonial and inclusive.
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Ismaili, R. R. R., Peng, X., Li., Y, Ali, A., Ahmad, T., Rahman, A. U., Ahmad, S., Shi, K. (2024). Modeling Habitat Suitability of Snow Leopards in Yanchiwan National Reserve, China. Animals, 14(1938), 1–21.
Abstract: Snow leopards (Panthera uncia) are elusive predators inhabiting high-altitude and mountainous rugged habitats. The current study was conducted in the Yanchiwan National Nature Reserve, Gansu Province, China, to assess the habitat suitability of snow leopards and identify key environmental factors inducing their distribution. Field data collected between 2019 and 2022 through scat sampling and camera trapping techniques provided insights into snow leopard habitat preferences. Spatial distribution and cluster analyses show distinct hotspots of high habitat suitability, mostly concentrated near mountainous landscapes. While altitude remains a critical determinant, with places above 3300 m showing increased habitat suitability, other factors such as soil type, human footprint, forest cover, prey availability, and human disturbance also play important roles. These variables influence ecological dynamics and are required to assess and manage snow leopard habitats. The MaxEnt model has helped us to better grasp these issues, particularly the enormous impact of human activities on habitat suitability. The current study highlights the importance of altitude in determining snow leopard habitat preferences and distribution patterns in the reserve. Furthermore, the study underscores the significance of considering elevation in conservation planning and management strategies for snow leopards, particularly in mountainous regions. By combining complete environmental data with innovative modeling tools, this study not only improves local conservation efforts but also serves as a model for similar wildlife conservation initiatives around the world. By understanding the environmental factors driving snow leopard distribution, conservation efforts can be more efficiently directed to ensure the long-term survival of this endangered species. This study provides valuable insights for evidence-based conservation efforts to safeguard the habitats of snow leopards amidst emerging anthropogenic pressure and environmental fluctuations.
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Sanyal, O., Bashir, T., Rana, M., Chandan, P. (2023). First photographic record of the snow leopard Panthera uncia in Kishtwar High Altitude National Park, Jammu and Kashmir, India. Oryx, , 1–5.
Abstract: The snow leopard Panthera uncia is categorized as Vulnerable on the IUCN Red List. It is the least well-known of the large felids because of its shy and elusive nature and the inaccessible terrain it inhabits across the mountains of Central and South Asia. We report the first photographic record of the snow leopard in Kishtwar High Altitude National Park, India. During our camera-trapping surveys, conducted using a grid-based design, we obtained eight photographs of snow leopards, the first at 3,280 m altitude on 19 September 2022 and subsequent photographs over 3,004-3,878 m altitude. We identified at least four different individuals, establishing the species’ occurrence in Kiyar, Nanth and Renai catchments, with a capture rate of 0.123 ± SE 0.072 captures/100 trap-nights. ghts. We also recorded the presence of snow leopard prey species, including the Siberian ibex Capra sibirica, Himalayan musk deer Moschus leucogaster, long-tailed marmot Marmota caudata and pika Ochotona sp., identifying the area as potential snow leopard habitat. Given the location of Kishtwar High Altitude National Park, this record is significant for the overall snow leopard conservation landscape in India. We recommend a comprehensive study across the Kishtwar landscape to assess the occupancy, abundance, demography and movement patterns of the snow leopard and its prey. In addition, interactions between the snow leopard and pastoral communities should be assessed to understand the challenges facing the conservation and management of this important high-altitude region.
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