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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Blomqvist, L. (1995). The snow leopard in captivity in 1992. International Zoo News, 42(3), 152–159.
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Egorov O.V. (1955). Enemies, infections, parasites and mortality rate of ibex (Vol. Vol. 42.).
Abstract: Reasons for ibex and argali mortality from natural enemies, parasites, infections, accidents, and hunters are analyzed. Snow leopard is one of the most dangerous enemies of ibex and argali, preying equally on both young and mature animals (mostly males). Snow leopard feeds upon ibex all year round. Unlike wolf, snow leopard would never kill several animals at a time, but only one selected victim. The food remains left by these predators are different in terms of the skull gnawing. Nasal bones and eye-sockets on the skull of ibex killed by snow leopard remain undamaged, while wolf gnaws off nasal part of the skull, breaks eye-sockets, eats lower jaw, widens occipital hole and pulls out brains. Snow leopard leaves large pieces of skin around the skeleton of the victim, whereas wolf tears it to shreds or eats up fully. Sometimes parts of the victim left by snow leopard are eaten by wolf. It is easy to mix the remains of snow leopard's or griffon vulture's food. The remains differ in skin being turned inside out rather than torn to large pieces.
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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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Schaller, G. B. (1987). Status of large mammals in the Taxkorgan Reserve, Xinjiang, China. Biological-Conservation, 42(1), 53–71.
Abstract: A status survey of large mammals was conducted in the W half of 14 000 km“SUP 2” Taxkorgan Reserve. Only one viable population of fewer than 150 Marco Polo sheep Ovis ammon poli survives; it appears to be augmented by adult males from Russia and Afghanistan during the winter rut. Asiatic ibex Capra ibex occur primarily in the western part of the reserve and blue sheep Pseudois nayaur – the most abundant wild ungulate – in the E and SE parts. The 2 species overlap in the area of contact. Counts revealed an average wild ungulate density of 0.34 animals km“SUP -2”. Snow leopard Panthera uncia were rare, with possibly 50-75 in the reserve, as were wolves Canis lupus and brown bear Ursus arctos. The principal spring food of snow leopard was blue sheep (60%) and marmot (29%). Local people have greatly decimated wildlife. Overgrazing by livestock and overuse of shrubs for fuelwood is turning this arid steppe habitat into desert. -from Authors
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Sulser, C. E., Steck, B. L., & Baur, B. (2008). Effects of construction noise on behaviour of and exhibit use by Snow leopards Uncia uncia at Basel zoo (Vol. 42).
Abstract: Noise caused by human activities can cause stress in animals. We examined whether noise from construction sites affects the behaviour of and exhibit use by three Snow leopards Uncia uncia at Basel zoo. The behaviour and location of the animals were recorded at 1 minute intervals, using the instantaneous scan sampling method over a period of 216 hours (104 hours on noisy days and 112 hours on quiet days). The animals differed individually in their responses to the construction noise. On noisy days, the Snow leopards generally spent less time in locomotion and more time resting, but even on quiet days, resting was the predominant behaviour performed. Under noisy conditions, they increased social resting and decreased resting alone. Walking and social walking were also reduced on noisy days. Furthermore, the Snow leopards spent considerably more time in the remote offexhibit enclosure under noisy conditions. Independent of background noise, they stayed more than half of the time in the caves and the forecourts of the outdoor enclosure. On quiet days, the Snow leopards used more sectors of their exhibit than on noisy days. The results indicate that the Snow leopards responded to construction noise by increasing the amount of time spent resting and by withdrawing to the remote parts of their exhibit.
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Xu, A., Jiang, Z., Li, C., Guo, J., Da, S., Cui, Q., et al. (2008). Status and conservation of the snow leopard Panthera uncia in the Gouli Region, Kunlun Mountains, China (Vol. 42).
Abstract: The elusive snow leopard Panthera unica is a rare and little studied species in China. Over 1 March-15 May 2006 we conducted a survey for the snow leopard in the Gouli Region, East Burhanbuda Mountain, Kunlun Mountains, Qinghai Province, China, in an area of c. 300 km2 at altitudes of 4,000-4,700 m. We surveyed 29 linear transects with a total length of c. 440 km, and located a total of 72 traces (pug marks, scrapes and urine marks) of snow leopard along four of the transects. We obtained eight photographs of snow leopard from four of six camera traps. We also recorded 1,369 blue sheep, 156 Tibetan gazelles, 47 argali, 37 red deer and one male white-lipped deer. We evaluated human attitudes towards snow leopard by interviewing the heads of 27 of the 30 Tibetan households living in the study area. These local people did not consider that snow leopard is the main predator of their livestock, and thus there is little retaliatory killing. Prospects for the conservation of snow leopard in this area therefore appear to be good. We analysed the potential threats to the species and propose the establishment of a protected area for managing snow leopard and the fragile alpine ecosystem of this region. (c) 2008 Fauna & Flora International.
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Roth, T. L., Swanson, W. F., & Wildt, D. E. (1995). Snow leopard (Panthera unica) sperm longevity in vitro is not influenced by protein or energy source supplements but is affected by buffer source. Theriogenology, 43(1), 309.
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Shi, K., Jun, Z. F. S., Zhigang, D., Riordan, P., & MacDonald, D. (2009). Reconfirmation of snow leopards in Taxkurgan Nature Reserve, Xinjiang, China. Oryx, 43(2), 169–170.
Abstract: China may hold a greater proportion of the global snow leopard Panthera uncia population than any other country, with the area of good quality suitable habitat, estimated at nearly 300,000 km2, comprising .50% of that available across the species' entire range. We can now reconfirm the presence of snow leopard in the Taxkurgan area of Xinjiang Province in north-west China after a period of 20 years.
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Mongolian News. (2011, 43 1142). 50 wild sheep will be hunted this year., 4.
Abstract: Notice that the Mongolian government will allow the taking of 4 snow leopards in 2011.
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