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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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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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Rashid, W., Shi, J., Rahim, I. U., Dong, S., Ahmad, L. (2020). Research trends and management options in human-snow leopard conflict. Biological Conservation, 242(108413), 1–10.
Abstract: Conservation of the snow leopard (Panthera uncia) is challenging because of its threatened status and increase in human-snow leopard conflict (HSC). The area of occupancy of the snow leopard comprises mountainous regions of Asia that are confronted with various environmental pressures including climate change. HSCs have increased with a burgeoning human population and economic activities that enhance competition between human and snow leopard or its preys. Here we systematically review the peer-reviewed literature from 1994 to 2018 in Web of Science, Google Scholar, Science Direct and PubMed (30 articles), to evaluate the current state of scholarship about HSCs and their management. We determine: 1) the spatio-temporal distribution of relevant researches; 2) the methodologies to assess HSCs; 3) and evaluate existing interventions for conflict management; and 4) the potential options for HSC management. The aim of the current study is thus to identify key research gaps and future research requirements. Of the articles in this review, 60% evaluated the mitigation of HSCs, while only 37% provided actionable and decisive results. Compensation programs and livestock management strategies had high success rates for mitigating HSCs through direct or community-managed interventions. Further research is required to evaluate the efficacy of existing HSC mitigation strategies, many of which, while recommended, lack proper support. In spite of the progress made in HSC studies, research is needed to examine ecological and sociocultural context of HSCs. We suggest future work focus on rangeland management for HSC mitigation, thus ultimately fostering a co-existence between human and snow leopard.
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Bohnett, E., Faryabi, S. P., Lewison, R., An, L., Bian, X., Rajabi, A. M., Jahed, N., Rooyesh, H., Mills, E., Ramos, S., Mesnildrey, N., Perez, C. M. S., Taylor, J., Terentyev, V., Ostrowski, S. (2023). Human expertise combined with artificial intelligence improves performance of snow leopard camera trap studies. Global Ecology & Conservation, 41(e02350), 1–13.
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.
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Kachel, S., Bayrakcismith, R., Kubanychbekov, Z., Kulenbekov, R., McCarthy, T., Weckworth, B., Wirsing, A. (2022). Ungulate spatiotemporal responses to contrasting predation risk from wolves and snow leopards. Journal of Animal Ecology, , 1–16.
Abstract: 1. Spatial responses to risk from multiple predators can precipitate emergent consequences for prey (i.e. multiple-predator effects, MPEs) and mediate indirect interactions between predators. How prey navigate risk from multiple predators may therefore have important ramifications for understanding the propagation of predation-risk effects (PREs) through ecosystems.
2. The interaction of predator and prey traits has emerged as a potentially key driver of antipredator behaviour but remains underexplored in large vertebrate systems, particularly where sympatric prey share multiple predators. We sought to better generalize our understanding of how predators influence their ecosystems by considering how multiple sources of contingency drive prey distribution in a multi-predator–multi-prey system. 3. Specifically, we explored how two sympatric ungulates with different escape tactics—vertically agile, scrambling ibex Capra sibirica and sprinting argali Ovis ammon—responded to predation risk from shared predators with contrasting hunting modes—cursorial wolves Canis lupus and vertical-ambushing, stalking snow leopards Panthera uncia. 4. Contrasting risk posed by the two predators presented prey with clear trade-offs. Ibex selected for greater exposure to chronic long-term risk from snow leopards, and argali for wolves, in a nearly symmetrical manner that was predictable based on the compatibility of their respective traits. Yet, acute short-term risk from the same predator upended these long-term strategies, increasing each ungulates' exposure to risk from the alternate predator in a manner consistent with a scenario in which conflicting antipredator behaviours precipitate risk-enhancing MPEs and mediate predator facilitation. By contrast, reactive responses to wolves led ibex to reduce their exposure to risk from both predators—a risk-reducing MPE. Evidence of a similar reactive risk-reducing effect for argali vis-à-vis snow leopards was lacking. 5. Our results suggest that prey spatial responses and any resulting MPEs and prey-mediated interactions between predators are contingent on the interplay of hunting mode and escape tactics. Further investigation of interactions among various drivers of contingency in PREs will contribute to a more comprehensive understanding and improved forecasting of the ecological effects of predators. |
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Rode, J., Lambert, C., Marescot, L., Chaix, B., Beesau, J., Bastian, S., Kyrbashev, J., Cabanat, A.L. (2021). Population monitoring of snow leopards using camera trapping in Naryn State Nature Reserve, Kyrgyzstan, between 2016 and 2019. Global Ecology and Conservation, 31(e01850), 1–6.
Abstract: Four field seasons of snow leopard (Panthera uncia) camera trapping inside Naryn State Nature Reserve, Kyrgyzstan, performed thanks to citizen science expeditions, allowed detecting a minimal population of five adults, caught every year with an equilibrated sex ratio (1.5:1) and reproduction: five cubs or subadults have been identified from three litters of two different females. Crossings were observed one to three times a year, in front of most camera traps, and several times a month in front of one of them. Overlap of adults’ minimal territories was observed in front of several camera traps, regardless of their sex. Significant snow leopard presence was detected in the buffer area and at Ulan area which is situated at the reserve border. To avoid poaching on this apex predator and its preys, extending the more stringent protection measures of the core zone to both the Southern buffer area and land adjacent to Ulan is recommended.
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Thapa, K., Rayamajhi, S. (2023). Anti-predator strategies of blue sheep (naur) under varied predator compositions: a comparison of snow leopard-inhabited valleys with and without wolves in Nepal. Wildlife Research, , 1–9.
Abstract: In Nepal, naur are usually the staple wild prey for the snow leopard, a solitary stalker hunter, and in some cases, for the wolf who hunts in a pack. We assumed that naur would adapt their anti-predatory responses to the presence of chasing and ambushing predators in the Manang Valley, where there are snow leopards and wolves, and in the Nar Phu valley, an area where there is only the snow leopard.
Aims. The aim of this study was to determine if there were differences in anti-predator strategies (vigilance, habitat selection and escape terrain) of naur in two valleys over two seasons, spring and autumn. Methods. In spring 2019, we conducted a reconnaissance survey on the status of the naur and its habitat in the Manang and Nar Phu valleys of the Annapurna Conservation Area, Nepal. In spring and autumn 2020 and 2021, we observed 360 focal naur individuals (180 individuals in each valley), using the vigilance behaviour methodology to examine the behaviour of the naur. Key results. There was little difference in the size of the naur groups between the Manang and Nar Phu valleys. The naur were twice as vigilant in Manang (15%), where there are snow leopards and wolves, as they were in Nar Phu (9%), with only snow leopards. The distance from the naur to escape cover was significantly shorter in Manang than in Nar Phu valley. Naur used significantly more rolling terrain in Nar Phu than in Manang. Conclusions. The return of wolves to the Manang valley may have resulted in an increase in the level of naur vigilance. Most likely, the wolves in Manang have already had an effect on the female-to-young-ratio, and this effect will possibly have important consequences for the naur population, as well as at the ecosystem level in the future. Other key determining factors, such as the climate crisis and changes in local resources, could have a significant impact on the naur population, indicating the need for more research. Implications. The findings of this study would provide valuable baseline information for the design of a science-based conservation strategy for conservation managers and scientists on naur, snow leopards and wolves. |
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Thapa, K., Baral, S., Rahamajhi, S. (2023). Effectiveness of Human-Snow leopard co-existence measure- a systematic analysis. Journal for Nature Conservation, 76(126511), 1–11.
Abstract: Snow leopards and agropastoral communities have co-existed in snow leopard range countries for centuries. The vulnerable snow leopard forms and maintains the entire ecosystem, serving as an indicator species of a healthy alpine ecosystem. However, snow leopards, on the other hand, habitually kill livestock, occasionally killing 100 or more livestock in a single night, resulting in snow leopard retaliation. Thus, the snow leopard is becoming more threatened, so more attention should be paid. Therefore, numerous conservation mitigation strategies have been applied to maintain human-snow leopard coexistence in countries of the snow leopard range. However, such implemented conservation strategies lacked a thorough assessment of their achievements or shortcomings in protecting the snow leopard and enhancing community tolerance. Therefore, we systematically examined and evaluated peer-reviewed articles and book chapters on existing and implemented mitigation measures. We use the software Publish or Perish to achieve this, and we assess using the Preferred Reporting of Items for Systematic Review and Meta-Analysis (PRISMA) review approach. We thoroughly analyzed 42 papers and book chapters that were condensed human- snow leopard co-existence-related literature published in English from 2010 to 2023. Almost 90% of the papers were country-specific, with the remaining papers covering regional or snow leopard ranges countries. Nepal had the most papers, followed by China, India, and Mongolia; however, Afghanistan, Bhutan, Pakistan, Russia, and Tajikistan each had<10%, but there was no single document from Kazakhstan or Kyrgyzstan. Predator-proof corral, improved herding practices, and community-based insurance programs were three of the key recommendations that were more than 10 to 22 times proposed interventions. There are site-specific sociocultural situations and environments that require long-term action-oriented research that is area-specific rather than short-term and generic interventions. We identified a large knowledge gap in snow leopard research, specifically a lack of evidence that demonstrates and quantifies the effects of conservation actions, and strongly advise that it be further researched.
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Gao, Y., Wang, Y., Lee, A. T. L., Liu, Y., Luo, Y., Orrick, K., Alexander, J. S., Sangpo, J. T., Clark, S. G. (2023). Contextualizing sociodemographic differences in Tibetan attitudes toward large carnivores. Conservation Science and Practice, (e13049), 1–15.
Abstract: Fostering human–wildlife coexistence necessitates a thorough and nuanced grasp of local attitudes toward wildlife. Attitudes can vary substantially based on the sociodemographic backgrounds of individuals within a society. This study examines Tibetan attitudes toward large carnivores, emphasizing the importance of contextualization in discerning the effects of sociodemographic factors on attitudes. We began by analyzing existing research on Tibetan attitudes toward wildlife in China, identifying previously studied sociodemo- graphic variables. We then executed an online survey to evaluate the affective, behavioral, cognitive, and overall attitudes of ethnic Tibetans in China toward snow leopards (Panthera uncia), gray wolves (Canis lupus), and brown bears (Ursus arctos). Our findings show that while factors such as gender, age, religious identity, and level of education shape these attitudes, their influence differs depending on the specific attitude component and the target animal under examination. Therefore, making broad generalizations about sociodemographic differences in attitudes can be misleading. It is imperative for attitude research to clearly define the attitude component (what type of attitude), object (attitude toward what), and circumstance (attitude in which situation) being studied. Conducting ethnographic fieldwork in collaboration with local cultural experts can deepen our understanding of local perspectives and the ways sociodemographic factors influence attitudes. Such insights are pivotal for developing conservation strategies attuned to local sociocultural contexts.
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