Abstract: There is an increasing emphasis in conservation strategies for large carnivores on facilitating their coexistence with humans. Justification for coexistence strategies should be based on a quantitative assessment of currently remaining large carnivores in human-dominated landscapes. An essential part of a carnivore’s coexistence strategy has to rely on its prey. In this research, we studied snow leopards Panthera uncia whose habitat mainly comprises human-dominated, unprotected areas, to understand how a large carnivore and its primary prey, the bharal Pseudois nayaur, could coexist with human land use activities in a large proportion of its range. Using a combination of livestock census, camera trapping and wildlife surveys, across a broad gradient of livestock grazing intensity in a 363 000 km2 landscape on the Tibetan Plateau, we found no evidence of livestock grazing impacts on snow leopard habitat use, bharal density and spatial distribution, even though livestock density was 13 times higher than bharal density. Bharal were found to prefer utilizing more rugged habitats at higher elevations with lower grass forage conditions, whereas livestock dominated in flat valleys at lower elevations with higher productivity, especially during the resource-scarce season. These findings suggest that the spatial niche separation between bharal and livestock, together with snow leopards’ specialized bharal diet, minimized conflicts and allowed snow leopards and bharal to coexist in landscapes dominated by livestock grazing. In recent years, reduced hunting and nomadic herder’s lifestyle changes towards permanent residence may have further reinforced this spatial separation. Our results indicated that, for developing conservation strategies for large carnivores, the niche of their prey in relation to human land-use is a key variable that needs to be evaluated.

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: 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: 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: 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.