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.

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.

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.

Abstract: Snow leopards (Panthera uncia) have long co-existed with livestock herding people across Asia’s high mountains. Multiple use landscapes however imply potential competition for shared resources, livestock predation, and the risk of retaliatory killing of predators. Community-based conservation is a central pillar for supporting people’s livelihoods and safeguarding predators and their habitat. Based on the theory of planned behavior, we examined the factors that shape herders’ tolerance of snow leopards. Our questionnaire-based study was conducted in the Sanjiangyuan Region, China, encompassing four communities with varying livelihoods, experiences with live- stock depredation and levels of exposure to community conservation interventions. Our results showed that respondents generally held positive views towards snow leopards, although women tended to have relatively more negative views towards snow leopards compared with men. Current household income was largely dependent on caterpillar fungus rather than livestock. Social norms around religion and the role of community leaders in our study area seemed to be the main determinants of the generally benign association of people with wildlife, overshadowing potential influences of community-based conservation interventions. Our work suggests that conservations programs will be aided through collaborations with communities and religious institutions, and that conservationists must proactively engage with women as significant actors in conservation.

Abstract: Disease cross-transmission between wild and domestic ungulates can negatively impact livelihoods and wildlife conservation. In Pin valley, migratory sheep and goats share pastures seasonally with the resident Asiatic ibex (Capra sibirica), leading to potential disease cross-transmission. Focussing on gastro-intestinal nematodes (GINs) as determinants of health in ungulates, we hypothesized that infection on pastures would increase over summer from contamination by migrating livestock. Consequently, interventions in livestock that are well-timed should reduce infection pressure for ibex. Using a parasite life-cycle model, that predicts infective larval availability, we investigated GIN transmission dynamics and evaluated potential interventions. Migratory livestock were predicted to contribute most infective larvae onto shared pastures due to higher density and parasite levels, driving infections in both livestock and ibex. The model predicted a c.30-day anti- parasitic intervention towards the end of the livestock’s time in Pin would be most effective at reducing GINs in both hosts. Albeit with the caveats of not being able to provide evidence of interspecific parasite trans- mission due to the inability to identify parasite species, this case demonstrates the usefulness of our predictive model for investigating parasite transmission in landscapes where domestic and wild ungulates share pastures. Additionally, it suggests management options for further investigation.

Abstract: Camera trapping is the most widely used data collection method for estimating snow leopard (Panthera uncia) abundance; however, the accuracy of this method is limited by human observer errors from misclassifying individuals in camera trap images. We evaluated the extent Whiskerbook (www.whiskerbook.org), an artificial intelligence (AI) software, could reduce this error rate and enhance the accuracy of capture-recapture abundance estimates. Using 439 images of 34 captive snow leopard individuals, classification was performed by five observers with prior experience in individual snow leopard ID (“experts”) and five observers with no such experience (“novices”). The “expert” observers classified 35 out of 34 snow leopard individuals, on average erroneously splitting one individual into two, thus resulting in a higher number than true individuals. The success rate of experts was 90 %, with less than a 3 % error in estimating the population size in capture-recapture modeling. However, the “novice” observers successfully matched 71 % of encounters, recognizing 25 out of 34 individuals, underestimating the population by 25 %. It was found that expert observers significantly outperformed novice observers, making statistically fewer errors (Mann Whitney U test P = 0.01) and finding the true number of individuals (P = 0.01). These differences were contrasted with a previous study by Johansson et al. 2020, using the same subset of 16 individuals from European zoos. With the help of AI and the Whiskerbook platform, “experts” were able to match 87 % of encounters and identify 15 out of 16 individuals, with modeled estimates of 16 ± 1 individuals. In contrast, “novices” were 63 % accurate in matching encounters and identified 12 out of 16 individuals, modeling 12 ± 1 individuals that underestimated the population size by 12 %. When comparing the performance of observers using AI and the Whiskerbook platform to observers performing the tasks manually, we found that observers using Whiskerbook made significantly fewer errors in splitting one individual into two (P = 0.04). However, there were also a significantly higher number of combination errors, where two individuals were combined into one (P = 0.01). Specifically, combination errors were found to be made by “novices” (P = 0.04). Although AI benefited both expert and novice observers, expert observers outperformed novices. Our results suggest that AI effectively reduced the misclassification of individual snow leopards in camera trap studies, improving abundance estimates. However, even with AI support, expert observers were needed to obtain the most accurate estimates.

Abstract: The Pallas’s cat (Otocolobus manul) is one of the most understudied taxa in the Felidae family. The species is currently assessed as being of “Least Concern” in the IUCN Red List, but this assessment is based on incomplete data. Additional ecological and genetic information is necessary for the long-term in situ and ex situ conservation of this species. We identified 29 microsatellite loci with sufficient diversity to enable studies into the individual identification, population structure, and phylogeography of Pallas’s cats. These microsatellites were genotyped on six wild Pallas’s cats from the Tibet Autonomous Region and Mongolia and ten cats from a United States zoo-managed population that originated in Russia and Mongolia. Additionally, we examined diversity in a 91 bp segment of the mitochondrial 12S ribosomal RNA (MT-RNR1) locus and a hypoxia-related gene, endothelial PAS domain protein 1 (EPAS1). Based on the microsatellite and MT-RNR1 loci, we established that the Pallas’s cat displays moderate genetic diversity. Intriguingly, we found that the Pallas’s cats had one unique nonsynonymous substitution in EPAS1 not present in snow leopards (Panthera uncia) or domestic cats (Felis catus). The analysis of the zoo-managed population indicated reduced genetic diversity compared to wild individuals. The genetic information from this study is a valuable resource for future research into and the conservation of the Pallas’s cat.

Abstract: Conservation strategies for apex predators, like the snow leopard (Panthera uncia), depend on a robust understanding of their dietary preferences, prey abundance, and adaptability to changing ecological conditions. To address these critical conservation concerns, this study presents a comprehensive evidence on prey availability and preferences for snow leopards in the Lapchi Valley in the Nepal Himalayas from November 2021 to March 2023. Field data were collected through the installation of twenty-six camera traps at 16 strategically chosen locations, resulting in the recording of 1228 events of 19 mammalian species, including domesticated livestock. Simultaneously, the collection of twenty snow leopard scat samples over 3800 m above sea level allowed for a detailed dietary analysis. Photo capture rate index and biomass composition analysis were carried out and seasonal prey availability and consumption were statistically analyzed. A total of 16 potential prey species for the snow leopard were documented during the study period. Himalayan musk deer (Moschus leucogaster) was the most abundant prey species, but infrequent in the diet suggesting that are not the best bet prey for the snow leopards. Snow leopards were found to exhibit a diverse diet, consuming eleven prey species, with blue sheep (Pseudois nayaur) being their most consumed wild prey and horses as their preferred livestock. The Pianka’s index of dietary niche overlap between the summer and winter seasons were 0.576, suggesting a pronounced seasonal variation in food preference corroborating with the prey availability. The scarcity of larger preys in winter is compensated by small and meso-mammals in the diet, highlighting the snow leopard’s capacity for dietary plasticity in response to the variation in resource availability. This research suggests for the utilization of genetic tools to further explore snow leopard diet composition. Additionally, understanding transboundary movements and conducting population assessments will be imperative for the formulation of effective conservation strategies.

Abstract: Animal-borne tracking devices have generated a wealth of new knowledge, allowing us to better understand, manage and conserve species. Fitting such tracking devices requires that animals are captured and often chemically immobilized. Such procedures cause stress and involve the risk of injuries and loss of life even in healthy individuals. For telemetry studies to be justifiable, it is vital that capture operations are planned and executed in an efficient and ethical way. Project objectives must be clearly articulated to address well-defined knowledge gaps, and studies designed to maximize the probability of achieving those goals. We provide guidelines for how to plan, design, and implement telemetry studies with a special emphasis on snow leopards that are typically captured using foot snares. We also describe the necessary steps to ensure that captures are conducted safely, and with minimal stress to animals.

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.

Abstract: 1. Community-based conservation, despite being more inclusive than fortress conservation, 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.

Abstract: Background
The endangered snow leopard is found throughout major mountain ranges of Central Asia, including the remote Himalayas. However, because of their elusive behavior, sparse distribution, and poor access to their habitat, there is a lack of reliable information on their population status and demography, particularly in Nepal. Therefore, we utilized noninvasive genetic techniques to conduct a preliminary snow leopard survey in two protected areas of Nepal.
Results
A total of 71 putative snow leopard scats were collected and analyzed from two different areas; Shey Phoksundo National Park (SPNP) in the west and Kangchanjunga Conservation Area (KCA) in the east. Nineteen (27%) scats were genetically identified as snow leopards, and 10 (53%) of these were successfully genotyped at 6 microsatellite loci. Two samples showed identical genotype profiles indicating a total of 9 individual snow leopards. Four individual snow leopards were identified in SPNP (1 male and 3 females) and five (2 males and 3 females) in KCA.
Conclusions
We were able to confirm the occurrence of snow leopards in both study areas and determine the minimum number present. This information can be used to design more in-depth population surveys that will enable estimation of snow leopard population abundance at these sites.