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Kashkadarinskaya Pravda Newspaper. (1983). Snow leopard goes to Frunze (Vol. 79 (26-11)).
Abstract: In canyon Karakol of the Alatoo ridge, a snow leopard was caught for a zoo of Frunze.
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Matyushkin, E. N. (2000). Tracks and tracking techniques in studies of large carnivorous mammals. Zoologichesky Zhurnal, 79((4)), 412–429.
Abstract: In Russia, traditions of track observations and the use of tracking techniques in studying the ecology and behavior of mammals were founded by A.N. Formozov. An analytic review of his data on large carnivorous mammals (tiger, snow leopard, wolf, brown bear, wolverine, and others) is given. A special detailed observation of animals' tracks as a source of information on their life is shown only to start. The efficiency of track observations in various fields of studies, including counting animals, is estimated. The values of day and night distances for various animal species, given in literature, have never been properly substantiated methodically. The tracking method is the most effective in studying the use of the home range by animals, drawing the network of their movements and scent-marking behavior. The hunting behavior of large predators in dense forests is can only be deduced by observing their tracks. In some cases, the use of tracking has a distinct advantage over radio tracking. The main propositions are illustrated by the materials of the author obtained in various Russian regions (in forests of the northern Russian Plain and southern Far east) for 1958-1998.
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Green, M. (1981). A check-list and some notes concerning the mammlas of the Langtang National Park, Nepal. Journal of the Bombay Natural History Society, 78(1), 77–87.
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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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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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Oli, M. (1994). Snow leopards and blue sheep in Nepal: Densities and predator: Prey ratio (Vol. 75).
Abstract: I studied snow leopards (Panthera uncia) and blue sheep (Pseudois nayaur) in Manang District, Annapurna Conservation Area, Nepal, to estimate numbers and analyze predatorprey interactions. Five to seven adult leopards used the 105-km2 study area, a density of 4.8 to 6.7 leopards/100 km2. Density of blue sheep was 6.6-10.2 sheep/km2, and biomass density was 304 kg/km2. Estimated relative biomass consumed by snow leopards suggested that blue sheep were the most important prey; marmots (Marmota himalayana) also contributed significantly to the diet of snow leopards. Snow leopards in Manang were estimated to harvest 9-20% of total biomass and 11-24% of total number of blue sheep annually. Snow leopard :blue sheep ratio was 1 :1 14-1 :159 on a weight basis, which was considered sustainable given the importance of small mammals in the leopard's diet and the absence of other competing predators.
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Oli, M. K. (1994). Snow leopards and blue sheep in Nepal: Densities and predator: prey ratio. Journal of Mammalogy, 75(4), 998–1004.
Abstract: I studied snow leopards (Panthera uncia) and blue sheep (Pseudois nayaur) in Manang District, Annapurna Conservation Area, Nepal, to estimate numbers and analyze predator-prey interactions. Five to seven adult leopards used the 10-5-km-2 study area, a density of 4.8 to 6.7 leopards/100 km-2. Density of blue sheep was 6.6 10.2 sheep/km-2, and biomass density was 304 kg/km-2. Estimated relative biomass consumed by snow leopards suggested that blue sheep were the most important prey; marmots (Marmota himalayana) also contributed significantly to the diel of snow leopards Snow leopards in Manang were estimated to harvest 9-20% of total biomass and 11-24% of total number of blue sheep annually. Snow leopard: blue sheep ratio was 1:114-1:159 on a weight basis, which was considered sustainable given the importance of small mammals in the leopard's diet and the absence of other competing predators.
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Schaller, G. B. (1972). On meeting a Snow Leopard. Animal Kingdom, 75(1), 7–13.
Abstract: Discusses snow leopard distribution, ecology and conservation. Describes baiting (with a domestic goat) of a snow leopard and cub in a game reserve in Northern Pakistan. Incudes a description of the Leopard killing a goat, and observations over a week when the leopards were feeding on the goat baits.
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Kleinman, M. S., & Garman, R. H. (1978). An endoscopic approach to a snow leopard. Gastroenterology, 74(6), 1348.
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Olaf, R. P., Edmonds, B., Gittleman, J., & Purvis, A. (1999). Building large trees by combining phylogenetic information: a complete phylogeny of the extant Carnivora (Mammalia). Biological Reviews of the Cambridge Philosophical Society, 74, 143–175.
Abstract: One way to build larger, more comprehensive phylogenies is to combine the vast amount of phylogenetic information already available. We review the two main strategies for accomplishing this (combining raw data versus combining trees), but employ a relatively new variant of the latter: supertree construction. The utility of one supertree technique, matrix representation using parsimony analysis (MRP), is demonstrated by deriving a complete phylogeny for all 271 extant species of the Carnivora from 177 literature sources. Beyond providing a `consensus' estimate of carnivore phylogeny, the tree also indicates taxa for which the relationships remain controversial (e.g. the red panda; within canids, felids, and hyaenids) or have not been studied in any great detail (e.g. herpestids, viverrids, and intrageneric relationships in the procyonids). Times of divergence throughout the tree were also estimated from 74 literature sources based on both fossil and molecular data. We use the phylogeny to show that some lineages within the Mustelinae and Canidae contain significantly more species than expected for their age, illustrating the tree's utility for studies of macroevolution. It will also provide a useful foundation for comparative and conservational studies involving the carnivores.
(Received June 2 1998)(Revised November 27 1998)(Accepted December 16 1998)
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