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Rode, J., Lambert, C., Marescot, L., Chaix, B., Beesau, J., Bastian, S., Kyrbashev, J., Cabanat, A.L. (2021). Population monitoring of snow leopards using camera trapping in Naryn State Nature Reserve, Kyrgyzstan, between 2016 and 2019. Global Ecology and Conservation, 31(e01850), 1–6.
Abstract: Four field seasons of snow leopard (Panthera uncia) camera trapping inside Naryn State Nature Reserve, Kyrgyzstan, performed thanks to citizen science expeditions, allowed detecting a minimal population of five adults, caught every year with an equilibrated sex ratio (1.5:1) and reproduction: five cubs or subadults have been identified from three litters of two different females. Crossings were observed one to three times a year, in front of most camera traps, and several times a month in front of one of them. Overlap of adults’ minimal territories was observed in front of several camera traps, regardless of their sex. Significant snow leopard presence was detected in the buffer area and at Ulan area which is situated at the reserve border. To avoid poaching on this apex predator and its preys, extending the more stringent protection measures of the core zone to both the Southern buffer area and land adjacent to Ulan is recommended.
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Oberosler, V., Tenan, S., Groff, C., Krofel, M., Augugliaro, C., Munkhtsog, B., Rovero, F. (2021). First spatially‐explicit density estimate for a snow leopard population in the Altai Mountains. Biodiversity and Conservation, , 15.
Abstract: The snow leopard Panthera uncia is an elusive and globally-threatened apex predator occurring in the mountain ranges of central Asia. As with other large carnivores, gaps in data on its distribution and abundance still persist. Moreover, available density estimates are often based on inadequate sampling designs or analytical approaches. Here, we used camera trapping across a vast mountainous area (area of the sampling frame 850 km2; analysed habitat extent 2600 km2) and spatially-explicit capture-recapture (SECR) models to provide, to our knowledge, the first robust snow leopard population density estimate for the Altai Mountains. This region is considered one of the most important conservation areas for snow leopards, representing a vast portion of suitable habitat and a key ecological corridor. We also provide estimates of the scale parameter (σ) that reflects ranging behaviour (activity range) and baseline encounter probability, and investigated potential drivers of density and related parameters by assessing their associations with anthropogenic and environmental factors. Sampling yielded 9729 images of snow leopards corresponding to 224 independent detections that belonged to a minimum of 23 identified adult individuals. SECR analysis resulted in an overall density of 1.31 individuals/100 km2 (1.15%–1.50 95% CI), which was positively correlated with terrain slope. This estimate falls within the mid-values of the range of density estimates for the species globally. We estimated significantly different activity range size for females and males (79 and 329 km2, respectively). Base- line encounter probability was negatively associated with anthropogenic activity. Our study contributes to on-going efforts to produce robust global estimates of population abundance for this top carnivore.
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Johansson, O., Kachel, S., Weckworth, B. (2022). Guidelines for Telemetry Studies on Snow Leopards. Animals, 12(1663), 1–12.
Abstract: Animal-borne tracking devices have generated a wealth of new knowledge, allowing us to better understand, manage and conserve species. Fitting such tracking devices requires that animals are captured and often chemically immobilized. Such procedures cause stress and involve the risk of injuries and loss of life even in healthy individuals. For telemetry studies to be justifiable, it is vital that capture operations are planned and executed in an efficient and ethical way. Project objectives must be clearly articulated to address well-defined knowledge gaps, and studies designed to maximize the probability of achieving those goals. We provide guidelines for how to plan, design, and implement telemetry studies with a special emphasis on snow leopards that are typically captured using foot snares. We also describe the necessary steps to ensure that captures are conducted safely, and with minimal stress to animals.
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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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Allen, M. L., Rovero, F., Oberosler, V., Augugliaro, C., Krofel, M. (2023). Effects of snow leopards (Panthera uncia) on olfactory communication of Pallas’s cats (Otocolobus manul) in the Altai Mountains, Mongolia. Behaviour, , 1–9.
Abstract: Olfactory communication is important for many solitary carnivores to delineate territories and communicate with potential mates and competitors. Pallas’s cats (Otocolobus manul) are small felids with little published research on their ecology and behaviour, including if they avoid or change behaviours due to dominant carnivores. We studied their olfactory communication and visitation at scent-marking sites using camera traps in two study areas in Mongolia. We documented four types of olfactory communication behaviours, and olfaction (sniffing) was the most frequent. Pallas’s cats used olfactory communication most frequently at sites that were not visited by snow leopards (Panthera uncia) and when they used communal scent-marking sites, they were more likely to use olfactory communication when a longer time had elapsed since the last visit by a snow leopard. This suggests that Pallas’s cats may reduce advertising their presence in response to occurrence of snow leopards, possibly to limit predation risk.
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Zhang, C., Ma, T., Ma, D. (2023). Status of the snow leopard Panthera uncia in the Qilian Mountains, Gansu Province, China. Oryx, , 1–6.
Abstract: Population density estimation is integral to the effective conservation and management of wildlife. The snow leopard Panthera uncia is categorized as Vulnerable on the IUCN Red List, and reliable information on its density is a prerequisite for its conservation and management. Little is known about the status of the snow leopard in the central and eastern Qilian Mountains, China. To address this, we estimated the population density of the snow leopard using a spatially explicit capture–recapture model based on camera trapping in Machang in the central and eastern Qilian Mountains during January–March 2019. We set up
40 camera traps and recorded 84 separate snow leopard captures over 3,024 trap-days. We identified 18 individual snow leopards and estimated their density to be 2.26/100 km. Our study provides baseline information on the snow leopard and the first population estimate for the species in the central and eastern Qilian Mountains.
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Sanyal, O., Bashir, T., Rana, M., Chandan, P. (2023). First photographic record of the snow leopard Panthera uncia in Kishtwar High Altitude National Park, Jammu and Kashmir, India. Oryx, , 1–5.
Abstract: The snow leopard Panthera uncia is categorized as Vulnerable on the IUCN Red List. It is the least well-known of the large felids because of its shy and elusive nature and the inaccessible terrain it inhabits across the mountains of Central and South Asia. We report the first photographic record of the snow leopard in Kishtwar High Altitude National Park, India. During our camera-trapping surveys, conducted using a grid-based design, we obtained eight photographs of snow leopards, the first at 3,280 m altitude on 19 September 2022 and subsequent photographs over 3,004-3,878 m altitude. We identified at least four different individuals, establishing the species’ occurrence in Kiyar, Nanth and Renai catchments, with a capture rate of 0.123 ± SE 0.072 captures/100 trap-nights. ghts. We also recorded the presence of snow leopard prey species, including the Siberian ibex Capra sibirica, Himalayan musk deer Moschus leucogaster, long-tailed marmot Marmota caudata and pika Ochotona sp., identifying the area as potential snow leopard habitat. Given the location of Kishtwar High Altitude National Park, this record is significant for the overall snow leopard conservation landscape in India. We recommend a comprehensive study across the Kishtwar landscape to assess the occupancy, abundance, demography and movement patterns of the snow leopard and its prey. In addition, interactions between the snow leopard and pastoral communities should be assessed to understand the challenges facing the conservation and management of this important high-altitude region.
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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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Bo, W. (2002). Illegal Trade of Snow Leopards in China: An Overview.. Islt: Islt.
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Harris, R. B. (1994). A note on snow leopards and local people in Nangqian County, Southern Qinghai Province. In J.L.Fox, & D. Jizeng (Eds.), (pp. 79–84). Usa: Islt.
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