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Wahlberg, C. (1980). Autopsy findings and causes of death in captive snow leopards (Panthera uncia): a preliminary report. In L. Blomqvist (Ed.), International Pedigree Book of Snow Leopards (Vol. 2, pp. 205–217). Helsinki: Helsinki Zoo.
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Sloane, A., Kelly, C., McDavitt, S., & Marples, N. (1998). Big cats in captivity: a quantitative analysis of enrichment. Adv.Etho, 33, 43.
Abstract: Studies on three species of big cats at Dublin Zoo have led to firm conclusions about the effects of certain forms of enrichment, some of which will be presented here. Lions, jaguars, and snow leopards were studied over two years and their behaviours quantified using focal animal sampling during selected hours during daylight. By comparison of these activity budgets with and without the enrichments being present, it was possible to identify the exact behavioural changes caused by each enrichment method, and to quantify these changes. In this contribution we present results showing that the presence of a platform in both lion and jaguar enclosures dramatically reduced stereotypic pacing behaviour. We will demonstrate that the effects of short term enrichment devices may have a wide range of effects on behaviours which outlast the presence of the stimulus. For instance scents added to the cage, or food/play items such as horse hides, hidden fish or ice-blocks often reduce pacing and increase resting later in the day, even after the cats have ceased using the enrichment items. This reduction in pacing and increase in resting time often meant that the amount of the enclosure used per hour was actually reduced with the presence of new stimuli, as result opposite to what might have been expected. The results of these studies will be discussed in relation to effective animal management.
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Rieger, I. (1982). Breeding ounces, Uncia uncia (Schreber, 1775) in zoological gardens. In L. Blomqvist (Ed.), International Pedigree Book of Snow Leopards, Vol. 3 (Vol. 3, pp. 49–50). Helsinki: Helsinki Zoo.
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Jackson, R., Roe, J., Wangchuk, R., & Hunter, D. (2005). Camera-Trapping of Snow Leopards. Cat News, 42(Spring), 19–21.
Abstract: Solitary felids like tigers and snow leopards are notoriously difficult to enumerate, and indirect techniques like pugmark surveys often produce ambiguous information that is difficult to interpret because many factors influence marking behavior and frequency (Ahlborn & Jackson 1988). Considering the snow leopard's rugged habitat, it is not surprising then that information on its current status and occupied range is very limited. We adapted the camera-trapping techniques pioneered by Ullas Karanth and his associates for counting Bengal tigers to the census taking of snow leopards in the Rumbak watershed of the India's Hemis High Altitude National Park (HNP), located in Ladakh near Leh (76ø 50' to 77ø 45' East; 33ø 15' to 34ø 20'North).
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Ming, M., Yun, G., & Bo, W. (2008). Chinese snow leopard team goes into action. Man & the Biosphere, 54(6), 18–25.
Abstract: China, the world's most populous country, also contains the largest number of Snow Leopards of any country in the world. But the survey and research of the snow leopard had been very little for the second half of the 20th century. Until recent years, the members of Xinjiang Snow Leopards Group (XSLG/SLT/XFC) , the Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences have been tracking down the solitary animal. The journal reporter does a face-to-face interview with professor Ma Ming who is a main responsible expert of the survey team. By the account of such conversation, we learn the achievements, advances and difficulty of research of snow leopards in the field, Tianshan and Kunlun, Xinjiang, the far west China, and we also know that why the team adopt the infrared camera to capture the animals. Last but not least professor talked about the survival menace faced by the Snow Leopards in Xinjiang.
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Worley, M. B. (1982). Chronic liver disease in snow leopards: A possible viral etiology. In L. Blomqvist (Ed.), International Pedigree Book of Snow Leopards, Vol. 3 (Vol. 3, pp. 131–133). Helsinki: Helsinki Zoo.
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Young, J. C., Alexander, J. S., Bijoor, A., Sharma, D., Dutta, A., Agvaantseren, B., Mijiddorj, T. N., Jumabay, K., Amankul, V., Kabaeva, B., Nawaz, A., Khan, S., Ali, H., Rullman, J. S., Sharma, K., Murali, R., Mishra, C. (2021). Community-Based Conservation for the Sustainable Management of Conservation Conflicts: Learning from Practitioners (Vol. 13).
Abstract: We explore the role of community-based conservation (CBC) in the sustainable management of conservation conflicts by examining the experiences of conservation practitioners trying to address conflicts between snow leopard conservation and pastoralism in Asian mountains. Practitioner experiences are examined through the lens of the PARTNERS principles for CBC (Presence, Aptness, Respect, Transparency, Negotiation, Empathy, Responsiveness, and Strategic Support) that represent an inclusive conservation framework for effective and ethical engagement with local communities. Case studies from India, Kyrgyzstan, Mongolia, and Pakistan show that resilient relationships arising from respectful engagement and negotiation with local communities can provide a strong platform for robust conflict management. We highlight the heuristic value of documenting practitioner experiences in on-the-ground conflict management and community-based conservation efforts.
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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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Schacter, A., Fitzgerald, K., & Doherty, J. (1980). Development of a snow leopard with and away from mother and siblings in the first six months. In L. Blomqvist (Ed.), International Pedigree Book of Snow Leopards (Vol. 2, pp. 112–126). Helsinki: Helsinki Zoo.
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Jack, R. (2008). DNA Testing and GPS positioning of snow leopard (Panthera uncia) genetic material in the Khunjerab National Park Northern Areas, Pakistan.
Abstract: The protection of Snow Leopards in the remote and economically disadvantaged Northern Areas of Pakistan needs local people equipped with the skills to gather and present information on the number and range of individual animals in their area. It is important for the success of a conservation campaign that the people living in the area are engaged in the conservation process. Snow Leopards are elusive and range through inhospitable terrain so direct study is difficult. Consequently the major goals for this project were twofold, to gather information on snow leopard distribution in this area and to train local university students and conservation management professionals in the techniques used for locating snow leopards without the need to capture or even see the animals. This project pioneered the use of DNA testing of field samples collected in Pakistan to determine the distribution of snow leopards and to attempt to identify individuals. These were collected in and around that country's most northerly national park, the Kunjurab National Park, which sits on the Pakistan China border. Though the Northern Areas is not a well developed part of Pakistan, it does possess a number of institutions that can work together to strengthen snow leopard conservation. The first of these is a newly established University with students ready to be trained in the skills needed. Secondly WWF-Pakistan has an office in the main town and a state of the art GIS laboratory in Lahore and already works closely with the Forest Department who manage the national park. All three institutions worked together in this project with WWF providing GIS expertise, the FD rangers, and the university students carrying out the laboratory work. In addition in the course of the project the University of the Punjab in Lahore also joined the effort, providing laboratory facilities for the students. As a result of this project maps have been produced showing the location of snow leopards in
two areas. Preliminary DNA evidence indicates that there is more than one animal in this
relatively small area, but the greatest achievement of this project is the training and
experience gained by the local students. For one student this has been life changing. Due to
the opportunities provided by this study the student, Nelofar gained significant scientific
training and as a consequence she is now working as a lecturer and research officer for the
Center for Integrated Mountain Research, New Campus University of the Punjab, Lahore
Pakistan
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