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Sharma, R. (2010). Of Men and Mountain Ghosts: Glimpses from the Rooftop of the World. GEO, 3(6), 56–67.
Abstract: Catching a glimpse of a snow leopard is a rare and exciting event for anyone. For researchers, hideen camera traps have become a vital tool in their work.
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Jackson, R. M., & Ahlborn, G. (1988). Observations on the Ecology of Snow Leopard in West Nepal. In H.Freeman (Ed.), (pp. 65–87). India: Snow Leopard Trust and Wildlife Institute of India.
Abstract: This summary of a four year field study by Jackson and Ahlborn begging in 1982 and concluding in 1985, discusses behaviour, trapping and tracking techniques, home range, activity patterns, prey and habitat and survey methods.
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Schaller, G. B., Tserendeleg, J., & Amarsana, G. (1994). Observations on snow leopards in Mongolia. In J.Fox, & D.Jizeng (Eds.), (pp. 33–42). Usa: Islt.
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Augugliaro, C., Paniccia, C., Janchivlamdan, C., Monti, I. E., Boldbaatar, T., Munkhtsog, B. (2019). Mammal inventory in the Mongolian Gobi, with the southeasternmost documented record of the Snow Leopard, Panthera uncia (Schreber, 1775), in the country. Check List, 15(4), 575–578.
Abstract: Studies on mammal diversity and distribution are an important source to develop conservation and management strategies.
The area located in southern Mongolia, encompassing the Alashan Plateau Semi-Desert and the Eastern Gobi Desert-Steppe ecoregions, is considered strategic for the conservation of threatened species. We surveyed the non-volant mammals in the Small Gobi-A Strictly Protected Area (SPA) and its surroundings, by using camera trapping, live trapping, and occasional sightings. We recorded 18 mammal species belonging to 9 families and 6 orders. Among them, 4 are globally threatened or near-threatened, 2 are included in the CITES Appendix I, and 2 are listed in the Appendix II. Moreover, we provide the southeasternmost record for the Snow Leopard (Panthera uncia) in Mongolia, supported by photographic evidence. Our study highlights the importance of this protected area to preserve rare, threatened, and elusive species.
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Jackson, R. (2000). Linking Snow Leopard Conservation and People-Wildlife Conflict Resolution, Summary of a multi-country project aimed at developing grass-roots measures to protect the endangered snow leopard from herder retribution. Cat News, 33, 12–15.
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Henschel, P., & Ray, J. (2003). Leopards in African Rainforests: Survey and Monitoring Techniques (Wildlife Conservation Society, Ed.).
Abstract: Monitoring Techniques Forest leopards have never been systematically surveyed in African forests, in spite of their potentially vital ecological role as the sole large mammalian predators in these systems. Because leopards are rarely seen in this habitat, and are difficult to survey using the most common techniques for assessing relative abundances of forest mammals, baseline knowledge of leopard ecology and responses to human disturbance in African forests remain largely unknown. This technical handbook sums up the experience gained during a two-year study of leopards by Philipp Henschel in the Lop‚ Reserve in Gabon, Central Africa, in 2001/2002, supplemented by additional experience from carnivore studies conducted by Justina Ray in southwestern Central African Republic and eastern Congo (Zaire) . The main focus of this effort has been to develop a protocol that can be used by fieldworkers across west and central Africa to estimate leopard densities in various forest types. In developing this manual, Henschel tested several indirect methods to assess leopard numbers in both logged and unlogged forests, with the main effort devoted to testing remote photography survey methods developed for tigers by Karanth (e.g., Karanth 1995, Karanth & Nichols 1998; 2000; 2002), and modifying them for the specific conditions characterizing African forest environments. This handbook summarizes the results of the field testing, and provides recommendations for techniques to assess leopard presence/absence, relative abundance, and densities in African forest sites. We briefly review the suitability of various methods for different study objectives and go into particular detail on remote photography survey methodology, adapting previously developed methods and sampling considerations specifically to the African forest environment. Finally, we briefly discuss how camera trapping may be used as a tool to survey other forest mammals. Developing a survey protocol for African leopards is a necessary first step towards a regional assessment and priority setting exercise targeted at forest leopards, similar to those carried out on large carnivores in Asian and South American forests.
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Anonymous. (1992). International Specialists Discuss China's Threatened Cats.
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Bo, W. (2002). Illegal Trade of Snow Leopards in China: An Overview.. Islt: Islt.
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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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Thapa, K., Pradhan, N, M, B., Barker, J., Dhakal, M., Bhandari, A, R., Gurung, G, S., Rai, D, P., Thapa, G, J., Shrestha, S., Singh, G, R. (2013). High elevation record of a leopard cat in the Kangchenjunga Conservation Area, Nepal. Cat News, (No 58), 26–27.
Abstract: During a camera trapping survey in Khambachen valley of Kangchenjunga Conservation
Area KCA from 24 April to 26 May 2012 we camera trapped one leopard cat
Prionailurus bengalensis at an altitude of 4,474 meter. This is probably the highest
altitudinal record for the species in its range. Additionally, one melanistic leopard
Panthera pardus was captured at an altitude of 4,300 m, which is probably as well the
highest documented record in the country. Yet at this stage, no obvious reason can
explain these unusual high records for both species, thus more surveys are recommended
for this region.
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