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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.
Keywords: abnormal-behavior; behavior; captive-animal-care; endangered; threatened-species; zoos; enrichment; abnormal; captive; Animal; care; threatened; species; browse; 1280; study; big; big cats; Cats; cat; zoo; effects; Lions; lion; jaguar; snow; snow leopards; snow leopard; snow-leopards; snow-leopard; leopards; leopard; behaviour; using; activity; activities; change; presence; enclosures; range; scent; cage; horse; hides; management
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Izold, J. (2008). Snow Leopard Enterprise: a conservation project that saves an endangered species and supports needy families. Anim.Keepers' Forum, 9(5), 359–364.
Abstract: The World Conservation Union listed the snow leopard (Uncia uncia) as endangered in 1974. With as few as 3,500 snow leopards left in the wild, scientists placed the snow leopard on the IUCN Red List of critically endangered species shared by animals such as the giant panda and tiger. In an effort to save the snow leopard from extinction, former zoo employee Helen Freeman founded the Snow Leopard Trust in 1981. The Snow Leopard Trust works to save this elusive cat by incorporating community-based conservation projects. One of these project Leopard Enterprise (SLE), impacts poverty stricken communities in Mongolia, Kyrgyz Republic, and Pakistan. It assists over 300 families in its conservation efforts. The economic incentives provided via SLE have led participating communities not to harm the snow leopard or its prey, and to practice sustainable herding. Since the project began in 1997, the number of snow leopards harmed around the communities' territories has dropped to near zero. Additionally, the annual income of families that utilize the benefits of SLE has increased by 25% to 40%. SLE creates this economic benefit by providing the training and equipment necessary to make desirable products from the wool of herd animals. Snow Leopard Trust then purchases these handicraft items from the local people and them globally. Zoos can expand their conservation efforts by simply offering these items in their gift shops. Woodland Park Zoo (WPZ) was the first zoological institution to sell the products, and WPZ continues to generate revenue from them. SLE is a golden opportunity for zoos to increase revenue, assist poor families, and save an endangered species and fragile ecosystem.
Keywords: snow; snow leopard; snow-leopard; leopard; conservation; project; endangered; endangered species; endangered-species; species; Support; union; uncia; Uncia uncia; Uncia-uncia; snow leopards; snow-leopards; leopards; wild; Iucn; Animals; Animal; tiger; extinction; former; zoo; Freeman; trust; work; cat; community-based; projects; Sle; impact; poverty; community; Mongolia; Kyrgyz; Kyrgyz-Republic; republic; Pakistan; 300; economic; incentives; prey; sustainable; herding; number; territory; income; training; products; wool; local; local people; people; zoos; Woodland-Park-Zoo; park; zoological; ecosystem
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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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Marma, B. B., & Yunchis, V. V. (1968). Observations on the breeding, management and physiology of Snow leopards (Panthera u. uncia) at Kaunas Zoo from 1962 to 1967. In C. Jarvis, & R. Biegler (Eds.), Canids and Felids in Captivity (pp. 66–73). Zoological Society of London.
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McCarthy, T., Khan, J., Ud-Din, J., & McCarthy, K. (2007). First study of snow leopards using GPS-satellite collars underway in Pakistan. Cat News, 46(Spring), 22–23.
Abstract: Snow leopards (Uncia uncia) are highly cryptic and occupy remote inaccessible habitat, making studying the cats difficult in the extreme. Yet sound knowledge of the cat's ecology, behavior and habitat needs is required to intelligently conserve them. This information is lacking for snow leopards, and until recently so was the means to fill that knowledge gap. Two long-term studies of snow leopards using VHF radio collars have been undertaken in Nepal (1980s) and Mongolia (1990s) but logistical and technological constraints made the findings of both studies equivocal. Technological advances in the interim, such as GPS collars which report data via satellite, make studies of snow leopards more promising, at least in theory.
Keywords: study; snow; snow leopards; snow leopard; snow-leopards; snow-leopard; leopards; leopard; using; collars; collar; Pakistan; uncia; Uncia uncia; Uncia-uncia; habitat; Cats; cat; sound; knowledge; ecology; behavior; conserve; information; radio; radio collars; radio collar; radio-collars; radio-collar; Nepal; 1980; Mongolia; 1990; Gps; Report; Data; Satellite
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Jackson, R. (1999). Snow Leopards, Local People and Livestock Losses: Finding solutions using Appreciative Participatory Planning and Action (APPA) in the Markha Valley of Hemis National Park, Ladakh, October 6-26, 1999. Cat News, 31(Autumn), 22–23.
Abstract: Livestock depredation is emerging as a significant issue across the Himalaya, including the Hemis National Park (HNP) in Ladakh. Some consider that this protected area harbors the best snow leopard population in India, but local herders perceive the endangered snow leopard as a serious threat to their livelihood.
Keywords: snow; snow leopards; snow leopard; snow-leopards; snow-leopard; leopards; leopard; local; local people; people; livestock; loss; using; participatory; planning; action; valley; Hemis; national; national park; National-park; park; Ladakh
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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).
Keywords: camera trapping; snow; snow leopards; snow leopard; snow-leopards; snow-leopard; leopards; leopard; felids; tigers; tiger; techniques; surveys; survey; information; factor; marking; behavior; Ahlborn; Jackson; habitat; status; range; census; India; Hemis; High; national; national park; National-park; park; Ladakh; leh
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Ming, M., Munkhtsog, B., Xu, F., Turghan, M., Yin, S. -jing, & Wei, S. - D. (2005). Markings as Indicator of Snow Leopard in Field Survey, in Xinjiang.
Abstract: The Snow Leopard (Uncia uncia) was a very rare species in China. The survey on the markings of Snow Leopard in Ahay and Tianshan Mountains is the major activity of the Project of Snow Leopard in Xinjiang, supported by International Snow Leopard Trust(ISLT)and Xinjiang Conservation Fund(XCF). During the field work from Sep to Nov 2004 the Xinjiang Snow Leopard Group(XSLG) set 67 transects of a total length of 47 776 m with mean transect length is 7 1 3 m at 9 locations.Total of 1 l 8 markings of Snow Leopards were found in 27 transects the mean density is 247km. The markings of Snow Leopard included the pug marks or footprints, scrapes, feces, bloodstain, scent spray, urine, hair or fur, claw rake, remains of prey corpse, sleep site, roar and others. From the quantity and locations of marks the XSLG got the information on habitat selection distribution region and relative abundance of the Snow Leopard in the study areas. The survey also provided knowledge on distribution and abundance of major prey potential conservation problems and human attitudes to Snow Leopards by taking 200 questionnaires in the study areas.
Keywords: markings; marking; snow leopard; leopard; field survey; Xinjiang; Chinese; Uncia uncia; Uncia-uncia; China; Tianshan Mountains; conservation; field work; length; snow leopards; snow-leopards; density; densities; pug; pug marks; marks; scrapes; scrape; feces; scent; spray; Hair; fur; prey; habitat; Habitat selection; selection; distribution; region; relative abundance; abundance; study; areas; knowledge; potential; conservation problems; Human; attitudes; attitude; 200
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Subbotin, A. E., & Istomov, S. V. (2009). The population status of snow leopards Uncia uncia (Felidae, Carnivora) in the western Sayan Mountain Ridge. Doklady Biologicl Sciences, 425, 183–186.
Abstract: The snow leopard (Uncia uncial Schreber, 1776) is the most poorly studied species of the cat family in the world and, in particular, in Russia, where the northern periphery of the species area (no more than 3% of it) is located in the Altai-Hangai-Sayan range [1]. It is generally known that the existing data on the Russian part of the snow leopard population have never been a result of targeted studies; at best, they have been based on recording the traces of the snow leopard vital activity [2]. This is explained by the snow leopard's elusive behavior, inaccessibility of its habitats for humans, and its naturally small total numbers in the entire species area. All published data on the population status of the snow leopard in Russia, from the first descriptions of the species [3-6] to the latest studies [7, 8] are subjective, often speculative, and are not confirmed by
quantitative estimates. It is obvious, however, that every accurate observation of this animal is of particular interest [9]. The purpose of our study was to determine the structure and size of the population group presumably inhabiting the Western Sayan mountain ridge at the northern boundary of the species area Keywords: population; status; snow; snow leopards; snow leopard; snow-leopards; snow-leopard; leopards; leopard; uncia; Uncia uncia; Uncia-uncia; Felidae; Carnivora; Sayan; mountain; Russian; Test; species; cat; Russia; area; range; Data; study; activity; activities; behavior; habitats; habitat; humans; Human; number; description; Animal; structure
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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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