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Author Johansson, O., Alexander, J. S., Lkhagvajav, P., Mishra, C., Samelius, G.
Title Natal dispersal and exploratory forays through atypical habitat in the mountain-bound snow leopard Type Journal Article
Year (down) 2024 Publication Ecology Abbreviated Journal
Volume 2024 Issue e4264 Pages 1-4
Keywords connectivity, Gobi Desert, landscape permeability, Mongolia, Panthera uncia, resistance, steppe
Abstract Understanding how landscapes affect animal movements is key to effective conservation and management (Rudnick et al., 2012; Zeller et al., 2012). Movement defines animal home ranges, where animals generally access resources such as food and mates, and also their dispersal and exploratory forays. These movements are important for individual survival and fitness through genetic exchange within and between populations and for colonization of unoccupied habitats (Baguette et al., 2013; MacArthur & Wilson, 1967). Dispersal and exploratory movements typically occur when young animals leave their natal range and establish more permanent home ranges (Greenwood, 1980; Howard, 1960). In mammals, natal dispersal of males is usually more frequent and happens over greater distances compared with that of females (Clobert et al., 2001; Greenwood, 1980).
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Call Number SLN @ rakhee @ Serial 1742
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Author Arias, M., Coals, P., Ardiantiono, Elves-Powell, J., Rizzolo, J. B., Ghoddousi, A., Boron, V., da Silva, M., Naude, V., Williams, V., Poudel, S., Loveridge, A., Payan, E., Suryawanshi, K., Dickman, A.
Title Reflecting on the role of human-felid conflict and local use in big cat trade Type Journal Article
Year (down) 2024 Publication Conservation Science and Practice Abbreviated Journal
Volume 6 Issue e13030 Pages 1-7
Keywords conflict, illegal trade, jaguar, leopard, lion, Panthera, snow leopard, tiger, wildlife crime
Abstract Illegal trade in big cat (Panthera spp.) body parts is a prominent topic in scientific and public discourses concerning wildlife conservation. While illegal trade is generally acknowledged as a threat to big cat species, we suggest that two enabling factors have, to date, been under-considered. To that end, we discuss the roles of human-felid conflict, and “local” use in illegal trade in big cat body parts. Drawing examples from across species and regions, we look at generalities, contextual subtleties, ambiguities, and definitional complexities. We caution against underestimating the extent of “local” use of big cats and highlight the potential of conflict killings to supply body parts.
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Call Number SLN @ rakhee @ Serial 1745
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Author Parker, B. G., Khanyari, M., Ambarli, H., Buuveibaatar, B., Kabir, M., Khanal, G., Mirzadeh, H. R., Onon, Y., Farhadinia, M. S.
Title A review of the ecological and socioeconomic characteristics of trophy hunting across Asia Type Journal Article
Year (down) 2023 Publication Animal Conservation Abbreviated Journal
Volume Issue Pages 1-16
Keywords Asia; conservation spending; communities; other effective area-based conservation measures (OECM); revenue sharing; trophy hunting; socioeconomics.
Abstract The continuing debates about trophy hunting should be underpinned by an understanding of at least the basic characteristics of the practice (e.g. species, quotas, areas, prices). Whilst many countries in Asia have established trophy hunting programmes of considerable importance to conservation and local livelihoods, there remains some ambiguity over the extent of trophy hunting in Asia as its basic characteristics in each country have not been compiled. In this study, we compile information on various ecological and socioeconomic characteristics of trophy hunting of mammals for countries across Asia by reviewing published and unpublished literature, analysing trade data, and obtaining contributions from in-country contacts. Across Asia, established trophy hunting programmes exist in at least 11 countries and target at least 30 species and one hybrid (incl., five Vulnerable and one Endangered species). Trophy hunting in these countries varies markedly in areas (e.g. >1 million km2 in Kazakhstan, 37% of country, vs. 1325 km2 in Nepal, <1% of country) and annual offtakes (e.g. Kazakhstan: 4500 individuals from 4 of 5 trophy species; Pakistan: 229 from 4 of 7; Mongolia: 155 from 6 of 9; Tajikistan: 126 from 3 of 6; Nepal: 22 from 3 of the 4 that are trophy hunted in practice). Permit prices also vary across species and countries, with domestic and international hunters sometimes charged different rates. Hunters from the USA appear overwhelmingly prominent among international clients. National legislations typically mandate a proportion of trophy hunting revenue to accrue locally (range: 40–100%). We provide five key recommendations for research to inform trophy hunting policy in Asia: (1) Ecological impact assessments; (2) Socioeconomic impact assessments; (3) Evaluations of the contributions of trophy hunting to conservation spending; (4) Evaluations of the contributions of trophy hunting to the post-2020 Global Biodiversity Framework; (5) Further examinations of perceptions of trophy hunting.
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Call Number SLN @ rakhee @ Serial 1714
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Author 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.
Title Human expertise combined with artificial intelligence improves performance of snow leopard camera trap studies Type Journal Article
Year (down) 2023 Publication Global Ecology & Conservation Abbreviated Journal
Volume 41 Issue e02350 Pages 1-13
Keywords Snow leopard, Artificial intelligence, Camera trap misclassification, individual ID, HotSpotter
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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Call Number SLN @ rakhee @ Serial 1715
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Author Chimed, O., Lkhagvasuren, D., Alexander, J. S., Barclay, D., Bayasgalan, N., Lkhagvajav, P., Nygren, E., Robinson, S. L., Samelius, G.
Title Delivery of educational material increased awareness of the elusive Pallas’s cat in Southern Mongolia Type Journal Article
Year (down) 2023 Publication Applied Environmental Education & Comunication Abbreviated Journal
Volume Issue Pages 1-13
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Abstract Public engagement and awareness programs are important components of many conservation programs today as such engagements are often critical for successful conservation. In this study, we examined if delivery of educational material increased awareness of the Pallas’s cat and its environment in a southern Mongolia herder community. We found that knowledge was greater and attitudes toward the Pallas’s cat and wildlife in general were more positive one year after the delivery of the educational material. This study thus suggests that educational material can be effective at increasing awareness of small and elusive species such as the Pallas’s cat.
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Call Number SLN @ rakhee @ Serial 1718
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Author Islam, M., Sahana, M., Areendran, G., Jamir, C., Raj, K., Sajjad, H.
Title 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 Type Journal Article
Year (down) 2023 Publication Geo: Geography and Environment Abbreviated Journal
Volume 10 Issue e00121 Pages 1-15
Keywords bioclimatic variables, habitat suitability, MaxEnt model, niche overlap, western Himalayan region
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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Call Number SLN @ rakhee @ Serial 1719
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Author Atzeni, L., Wang, J., Riordan, P., Shi, K., Cushman, S. A.
Title Landscape resistance to gene flow in a snow leopard population from Qilianshan National Park, Gansu, China Type Journal Article
Year (down) 2023 Publication Landscape Ecology Abbreviated Journal
Volume Issue Pages
Keywords Landscape genetics · MLPE · Gene flow · Genetic distance · Isolation by distance · Isolation by resistance · Landscape resistance · Snow leopard · Principal component analysis
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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Call Number SLN @ rakhee @ Serial 1720
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Author Allen, M. L., Rovero, F., Oberosler, V., Augugliaro, C., Krofel, M.
Title Effects of snow leopards (Panthera uncia) on olfactory communication of Pallas’s cats (Otocolobus manul) in the Altai Mountains, Mongolia Type Journal Article
Year (down) 2023 Publication Behaviour Abbreviated Journal
Volume Issue Pages 1-9
Keywords behaviour, camera trap, Mongolia, Otocolobus manul, Panthera uncia, scent marking.
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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Call Number SLN @ rakhee @ Serial 1721
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Author Golla, T. R., Tensen, L., Vipin, Kumar, K., Kumar, S., Gaur, A.
Title Neutral and adaptive genetic variation in Indian snow leopards, Panthera uncia Type Journal Article
Year (down) 2023 Publication Current Science Abbreviated Journal
Volume 125 Issue 2 Pages 204-209
Keywords Adaptive evolution, balancing selection, cap- tive breeding, genetic diversity, major histocompatibility complex.
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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Call Number SLN @ rakhee @ Serial 1722
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Author Bohnett, E., Holmberg, J., Faryabi, S. P., An, L., Ahmad, B., Rashid, W., Ostrowski, S.
Title Comparison of two individual identification algorithms for snow leopards (Panthera uncia) after automated detection Type Journal Article
Year (down) 2023 Publication Ecological Informatics Abbreviated Journal
Volume 77 Issue 102214 Pages 1-14
Keywords Background subtraction, Deep learning, Hotspotter, Individual identification, PIE v2, Snow leopards
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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Call Number SLN @ rakhee @ Serial 1723
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