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.

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.

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: Mammalian communities inhabiting temperate grasslands are of conservation concern globally, especially in Central Asia, where livestock numbers have dramatically increased in recent decades, leading to overgrazing and land-use change. Yet, how this pervasive presence of livestock herds affects the community of wild mammals remains largely unstudied. We used systematic camera trapping at 216 sites across remote, mountainous areas of the Mongolian Altai Mountains to assess the spatial and temporal patterns of occurrence and the interspecific relationships within a mammalian community that includes different categories of livestock. By adopting a recently proposed multispecies occupancy model that incorporates interspecific correlation in occupancy, we found several statistically strong correlations in occupancy among species pairs, with the majority involving livestock. The sign of such associations was markedly species-dependent, with larger wild species of conservation concern, namely, snow leopard and Siberian ibex, avoiding livestock presence. As predicted, we found evidence of a positive correlation in occupancy between predators and their respective main prey. Contrary to our expectations, a number of intraguild species pairs also showed positive co-occurrence, with no evidence of spatiotemporal niche partitioning. Overall, our study suggests that livestock encroaching into protected areas influences the whole local community of wild mammals. Though pastoralism has coexisted with wildlife for millennia in central Asian grasslands, our findings suggest that policies and practices to decrease the pressure of livestock husbandry on wildlife are needed, with special attention on large species, such as the snow leopard and its wild prey, which seem to be particularly sensitive to this pervasive livestock presence.

Abstract: This paper uses remote sensing data from the Sanjiangyuan National Park (SNP) to explore the divergence between the boundaries of national parks and the distribution of natural habitats. Results are used to argue that these discrepancies evolve along with the potential impact of global warming. Using the example of the habitat change of snow leopards and the conflicts between local people and snow leopards, we reflect on the consequences of this divergence. Results show that divergence between the political boundaries and natural habitats as well as the consequent influence on the living conditions of local people are strikingly visible, and the effects of global warming on such conflicts are apparent. The authors conclude that both notions of ‘political boundaries’ and ‘natural habitats’ are expected to come together as the SNP region is spatially configured, while ‘global warming’ seems to be relevant as an essential reference when delimiting the region in the future. Finally, the proposal for the establishment of cooperative conservation areas is presented,
emphasizing the role of cooperative governance in/around national parks.

Abstract: The cycle of livestock depredation and retaliatory killing constitutes a major threat to large carnivores worldwide and imposes considerable hardships on human communities. Mitigation efforts are often undertaken with little knowledge of ecological underpinnings and patterns of depredation, limiting conservationists' ability to develop, prioritize, and evaluate solutions. Carnivore detection and depredation data from interviews in affected communities may help address this gap, but such data are often prone to false-positive uncertainty. To address these challenges in the Pamir Mountains of Tajikistan we collected snow leopard, lynx, wolf, and bear detection and depredation reports from local communities via semi-structured interviews. We used a novel hierarchical multi-species multi-state occupancy model that accounted for potential false-positives to investigate carnivore site use and depredation concurrently with respondents' apparent vulnerability to that risk. Estimated false-positive probabilities were small, but failure to account for them overstated site use probabilities and depredation risk for all species. Although individual vulnerability was low, depredation was nonetheless commonplace. Carnivore site use was driven by clear habitat associations, but we did not identify any clearly important large-scale spatial correlates of depredation risk despite considerable spatial variation in that risk. Respondents who sheltered livestock in household corrals reinforced with wire mesh were less likely to report snow leopard depredations. Reducing depredation and retaliation at adequately large scales in the Pamirs will likely require a portfolio of species-specific strategies, including widespread proactive corral improvements. Our approach expanded inference on the often-cryptic processes surrounding human-carnivore conflict even though structured wildlife data were scarce.

Abstract: Molecular markers that can effectively identify noninvasively collected samples and provide genetic
information are critical for understanding the distribution, status, and ecology of snow leopards (Panthera uncia). However, the low DNA quantity and quality in many
noninvasive samples such as scats makes PCR amplification and genotyping challenging. We therefore designed primers for 9 microsatellites loci previously isolated in the
domestic cat (Felis catus) specifically for snow leopard studies using noninvasive samples. The loci showed moderate levels of variation in two Mongolian snow leopard
populations. Combined with seven other loci that we previously described, they have sufficient variation (He = 0.504, An = 3.6) for individual identification and
population structure analysis. We designed a species species specific PCR assay using cytochrome b for identification of unknown snow leopard samples. These molecular markers
facilitate in depth studies to assess distribution, abundance, population structure, and landscape connectivity of this endangered species.

Abstract: Abstract There is a need for simple and robust techniques for assessment and monitoring of populations of the Endangered snow leopard Panthera uncia to inform the de- velopment of action plans for snow leopard conservation. We explored the use of occupancy modelling to evaluate the influence of environmental and anthropogenic features on snow leopard site-use patterns. We conducted a camera trap survey across  km in Gansu Province, China, and used data from  camera traps to estimate probabilities of site use and detection using the single season occupancy model. We assessed the influence of three covariates on site use by snow leopards: elevation, the presence of blue sheep Pseudois nayaur and the presence of human disturb- ance (distance to roads). We recorded  captures of snow leopards over , trap-days, representing a mean capture success of . captures per  trap-days. Elevation had the strongest influence on site use, with the probability of site use increasing with altitude, whereas the influence of presence of prey and distance to roads was relatively weak. Our findings indicate the need for practical and robust tech- niques to appraise determinants of site use by snow leo- pards, especially in the context of the limited resources available for such work.

Abstract: Successful conservation of the endangered snow leopard (Panthera uncia) relies on the effectiveness of monitoring programmes. We present the results of a 19-month camera trap survey effort, conducted as part of a longterm study of the snow leopard population in Qilianshan National Nature Reserve of Gansu Province, China. Weassessed the minimumnumber of individual snowleopards and population density across different sampling periods using spatial capture–recapture methods. Between 2013–2014, we deployed 34 camera traps across an area of 375 km2, investing a total of 7133 trap-days effort. Weidentified a total number of 17–19 unique individuals
from photographs (10–12 adults, five sub-adults and two cubs). The total number of individuals identified and estimated density varied across sampling periods, between 10–15 individuals and 1.46–3.29 snow leopards per 100 km2 respectively. We demonstrate that snow leopard surveys of limited scale and conducted over short sampling periods only present partial views of a dynamic and transient system.We also underline the challenges in achieving a sufficient sample size of captures and recaptures to assess trends in snow leopard population size and/or density for policy and conservation decision-making

Abstract: Declining prey populations are widely recognized as a primary threat to snow leopard (Panthera
uncia) populations throughout their range. Effective snow leopard conservation will depend upon reliable
knowledge of food habits. Unfortunately, past food-habit studies may be biased by inclusion of nontarget
species in fecal analysis, potentially misinforming managers about snow leopard prey requirements.
Differentiation between snow leopard and sympatric carnivore scat is now cost-effective and reliable using
genetics. We used fecal mitochondrial DNA sequencing to identify scat depositors and assessment bias in
snow leopard food-habit studies. We compared presumed, via field identification, and genetically confirmed
snow leopard scats collected during 2005 and 2012 from 4 sites in Central Asia, using standard forensic
microscopy to identify prey species. Field identification success varied across study sites, ranging from 21% to
64% genetically confirmed snow leopard scats. Our results confirm the importance of large ungulate prey for
snow leopards. Studies that fail to account for potentially commonplace misidentification of snow leopard
scat may mistakenly include a large percentage of scats originating from other carnivores and report
inaccurate dietary assessments. Relying on field identification of scats led to overestimation of percent
occurrence, biomass, and number of small mammals consumed, but underestimated values of these measures for large ungulates in snow leopard diet. This clarification suggests that the conservation value of secondary prey, such as marmots (Marmota spp.) and other small mammals, may be overstated in the literature; stable snow leopard populations are perhaps more reliant upon large ungulate prey than previously understood.

Abstract: Applied ecology lies at the intersection of human societies and natural systems. Consequently, applied ecologists are constantly challenged as to how best to use ecological knowledge to influence the management of ecosystems (Habel et al. 2013). As Hulme (2011) has pointed out, to do so effectively we must leave our ivory towers and engage with stakeholders. This engagement is especially important and challenging in areas of the world where poverty, weak institutions and poor governance structures conspire to limit the ability of local communities to contribute to biodiversity conservation. These communities often bear disproportionate costs in the form of curtailed access to natural resources, ecosystem services, and developmental
programmes, and also suffer wildlife-caused damage, including injuries or loss of human life, and economic
and psychological impacts (Madhusudan & Mishra 2003). It is well-recognized that conservation efforts in large parts of the world historically have been perceived to be discriminatory by local people (Mishra 2016). The need for engagement with local communities is therefore embedded in the 2020 Aichi biodiversity targets and is widely thought to be critical to the success of conservation efforts. However, although the need for engagement is clear, as ecologists and practitioners we often have little formal training in how we should engage with local communities and how we can recognize the pitfalls and opportunities provided by developing genuine partnerships. The practical challenges of achieving effective engagement are considerable (Agrawal & Gibson 1999; Waylen et al. 2010, 2013), and such forays are fraught with difficulties and ethical considerations (Chan et al. 2007). When they are done badly, conservation interventions
can damage relationships and trust, and lead to serious injustice to local people and setbacks for ecological
outcomes (Duffy 2010). Much has been written on knowledge exchange and participatory research approaches (e.g. Reed et al. 2014 and references therein). This Practitioner’s Perspective
seeks to focus on the next logical step: the elements that practitioners and researchers need to consider when
engaging with communities to effect conservation. Engagement around the management of protected areas
has been discussed and formalized (e.g. Dudley 2008). Considerable literature has also emerged, particularly
from Africa, on the use and co-management of natural resources, commonly referred to as community-based natural resource management or CBNRM (e.g. Fabricius 2004; Roe, Nelson & Sandbrook 2009; Child & Barnes
2010). There have been attempts to draw general principles for CBNRM (e.g. Thakadu 2005; Gruber 2010). In
the related field of community-based conservation, however, while there have been efforts to draw lessons (e.g. Berkes 2004), little exists in terms of frameworks or guidelines for effectively working with local communities to effect biodiversity conservation in multi-use landscapes
(Mishra 2016). The eight principles for community-based conservation outlined here (Fig. 1) build on ideas developed in fields as diverse as applied ecology, conservation and natural
resource management, community health, social psychology, rural development, negotiation theory, and ethics
(see Mishra 2016). They have been developed, challenged and tested through 20 years of community experience andour own research on the endangered snow leopard Panthera uncia and its mountain ecosystems, in South and Central Asia. We suspect that with contextual adaptations, their relevance for applied ecologists and practitioners may be universal.

Abstract: Pastoralism and predation are two major concomitantly known facts and matters of concern for conservation biologists worldwide. Pastoralist-predator conflict constitutes a major social-ecological concern in the Pamir mountain range encompassing Afghanistan, Pakistan, and Tajikistan, and affects community attitudes and tolerance toward carnivores. Very few studies have been conducted to understand the dynamics of livestock predation by large carnivores like snow leopards (Panthera uncia) and wolves (Canis
lupus), owing to the region�s remoteness and inaccessibility. This study attempts to assess the intensity of livestock predation (and resulting perceptions) by snow leopards and wolves across the Afghani, Pakistani, and Tajik Pamir range during the period January 2008�June 2012. The study found that livestock mortality due to disease is the most serious threat to livestock (an average 3.5 animal heads per household per year) and ultimately to the rural economy (an average of US$352 per household per year) as compared to
predation (1.78 animal heads per household per year, US$191) in the three study sites. Overall, 1419 (315 per year) heads of livestock were reportedly killed by snow leopards (47%) and wolves (53%) in the study sites. People with comparatively smaller landholdings and limited earning options, other than livestock rearing, expressed negative attitudes toward both wolves and snow leopards and vice versa. Education was found to be an effective solution to dilute people�s hatred for predators. Low public tolerance of the wolf and
snow leopard in general explained the magnitude of the threat facing predators in the Pamirs. This will likely continue unless tangible and informed conservation measures like disease control and predation compensation programs are taken among others.

Abstract: Among zoogeographical discoveries of the frontier of XXI century there is nothing more interesting
than discoveries of Rodion Sivolobov in Western Beringia. Beringia has surprised us by
paleontological discoveries many centuries ago, and also surprised by modern one. Somehow they
came out of attention of all International environmental foundations and Academies of the world, as
if on purpose to show their professional incompetence. It is the only way to describe the
organization, not to notice the appearance of such big cats as the Snow leopard and Amur tiger for
5,000 kilometers from the border of main range, as well as large Pleistocene relict � the Irkuyembear.
All three endangered species of mammals found by Sivolobov in Koryakia and Chukotka, and
for the snow leopard he took the world's first photo in Beringia.
New facts suggests two things: (1) the ancient refuges of big cats locate to Koryakia and
Chukotka much closer of main ranges, (2) global warming, changing natural environment on the
waves of hundred-year rhythms, periodically pushing irbis and tiger on the ways of ancient
Beringian migrations stored in their genetic memories. Irkuyem is a contemporary of the mammoth.
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Unlike it, this bear lived up to our days, but remained undetected even by the large “mammoths” of
science.