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Maheshwari, A., Sharma, D., Sathyakumar, S. (2013). Snow Leopard (Panthera Uncia) surveys in the Western Himalayas, India. Journal of Ecology and Natural Environmnet, 5(10), 303–309.
Abstract: We conducted surveys above 3000 m elevation in eight protected areas of Uttarakhand and Himachal Pradesh. These surveys provide new information on snow leopard in Uttarakhand on the basis of indirect evidence such as pugmark and scat. Snow leopard evidence (n = 13) were found between 3190 and 4115 m elevation. On an average, scats (n = 09) of snow leopard were found for every 56 km walked and pugmarks (n = 04) for every 126 km walked. Altogether, about 39% of the evidence were found on the hill-slope followed by valley floor (30%), cliff (15%) and 8% from both stream bed and scree slope. Genetic analysis of the scats identified three different individuals by using snow leopard specific primers. Snow leopard-human conflicts were assessed through questionnaire based interviews of shepherds from Govind Pashu Vihar Wildlife Sanctuary, Askot Wildlife Sanctuary and Nanda Devi Biosphere Reserve areas of Uttarakhand. Surveys revealed that livestock depredation (mule, goat and sheep) is the only cause of snow leopard-human conflicts and contributed 36% of the diet of snow leopard. Blue sheep and rodents together comprised 36.4% of the total diet. We found that 68.1% of the surveyed area was used for pastoral activities in Uttarakhand and Himachal Pradesh and 12.3% area was under tourism, defence and developmental activities.
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Lyngdoh, S., Shrotriya, S., Goyal, S. P., Clements, H., Hayward, M. W., Habib, B. (2014). Prey Preferences of the Snow Leopard (Panthera uncia): Regional Diet Specificity Holds Global Significance for Conservation. Plos One, 9(2), 1–11.
Abstract: The endangered snow leopard is a large felid that is distributed over 1.83 million km2 globally. Throughout its range it relies on a limited number of prey species in some of the most inhospitable landscapes on the planet where high rates of human persecution exist for both predator and prey. We reviewed 14 published and 11 unpublished studies pertaining to snow leopard diet throughout its range. We calculated prey consumption in terms of frequency of occurrence and biomass consumed based on 1696 analysed scats from throughout the snow leopard’s range. Prey biomass consumed was calculated based on the Ackerman’s linear correction factor. We identified four distinct physiographic and snow leopard prey type zones, using cluster analysis that had unique prey assemblages and had key prey characteristics which supported snow leopard occurrence there. Levin’s index showed the snow leopard had a specialized dietary niche breadth. The main prey of the snow leopard were Siberian ibex (Capra sibrica), blue sheep (Pseudois nayaur), Himalayan tahr (Hemitragus jemlahicus), argali (Ovis ammon) and marmots (Marmota spp). The significantly preferred prey species of snow leopard weighed 5565 kg, while the preferred prey weight range of snow leopard was 36–76 kg with a significant preference for Siberian ibex and blue sheep. Our meta-analysis identified critical dietary resources for snow leopards throughout their distribution and illustrates the importance of understanding regional variation in species ecology; particularly prey species
that have global implications for conservation.
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Ale, S., Shrestha, B., and Jackson, R. (2014). On the status of Snow Leopard Panthera Uncia (Schreber 1775) in Annapurna, Nepal. Journal of Threatened Taxa, (6(3)), 5534–5543.
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Ferretti, F., Lovari, S., Minder, I., Pellizzi, B. (2014). Recovery of the snow leopard in Sagarmatha (Mt.Everest) National Park: effects on main prey. European Journal of Wildlife Research, (60), 559–562.
Abstract: Consequences of predation may be particularly
heavy on small populations of herbivores, especially if they
are threatened with extinction. Over the 2006–2010 period, we
documented the effects of the spontaneous return of the endangered
snow leopard on the population of the vulnerable
Himalayan tahr. The study area was an area of central
Himalaya where this cat disappeared c. 40 years before, because
of persecution by man. Snow leopards occurred mainly
in areas close to the core area of tahr distribution. Tahr was the
staple (56.3 %) of snow leopards. After the arrival of this cat,
tahr decreased by more than 2/3 from 2003 to 2010 (mainly
through predation on kids). Subsequently, the density of snow
leopards decreased by 60%from2007 to 2010. The main prey
of snow leopards in Asia (bharal, marmots) were absent in our
study area, forcing snow leopards to specialize on tahr. The
restoration of a complete prey spectrum should be favoured
through reintroductions, to conserve large carnivores and to
reduce exploitation of small populations of herbivores, especially
if threatened.
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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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Maheshwari, A., Sathyakumar, S. (2019). Snow leopard stewardship in mitigating human-wildlife conflict in Hemis National Park, Ladakh, India. Human Dimensions of Wildlife, , 1–5.
Abstract: Among large predators, snow leopards (Panthera uncia) and co-predators (e.g., wolves
Canis lupus, lynx Lynx lynx) often cause economic losses, engendering animosity from
local communities in the mountain ecosystem across south and central Asia (Din et al.,
2017; Jackson & Lama, 2016; Maheshwari, Takpa, Kujur, & Shawl, 2010; Schaller, 2012).
These economic losses range from around US $50 to nearly $300 per household,
a significant sum given per capita annual incomes of $250 – $400 (Jackson & Wangchuk,
2004; Mishra, 1997). Recent efforts such as improved livestock husbandry practices
(predator-proof livestock corrals – closed night shelters with covered roof with wiremesh
and a closely fitting iron or wooden door that can be securely locked at night) and
community-based ecotourism (e.g., home stays, guides, porters, pack animals, campsites)
are providing alternative livelihood opportunities and mitigating large carnivores – human
conflict in the snow leopard habitats (Hanson, Schutgens, & Baral, 2018; Jackson, 2015;
Jackson & Lama, 2016; Vannelli, Hampton, Namgail, & Black, 2019). Snow leopard-based
ecotourism provides an opportunity to secure livelihoods and reduce poverty of the
communities living in ecotourism sites across Ladakh (Chandola, 2012; Jackson, 2015).
To understand the role of snow leopard-based ecotourism in uplifting the financial profile
of local communities, mitigating large carnivore – human conflict and eventually changing
attitudes towards large carnivores in Hemis National Park, Ladakh, India, we compared
the estimated financial gains of a snow leopard-based ecotourism to stated livestock
predation losses by snow leopards and wolves.
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Poyarkov, A. D., Munkhtsog, B., Korablev, M. P., Kuksin, A. N., Alexandrov, D. Y., Chistopolova, M. D., Hernandez-Blanco, J. A., Munkhtogtokh, O., Karnaukhov, A. S., Lkhamsuren, N., Bayaraa, M., Jackson, R. M., Maheshwari, A., Rozhnov, V. V. (2020). Assurance of the existence of a trans-boundary population of the snow leopard (Panthera uncia) at Tsagaanshuvuut – Tsagan- Shibetu SPA at the Mongolia-Russia border. Integrative Zoology, (15), 224–231.
Abstract: The existence of a trans-boundary population of the snow leopard (Panthera uncia) that inhabits the massifs of Tsagaanshuvuut (Mongolia) – Tsagan-Shibetu (Russia) was determined through non-invasive genetic analysis of scat samples and by studying the structure of territory use by a collared female individual. The genetic analysis included species identification of samples through sequencing of a fragment of the cytochrome b gene and individual identification using a panel of 8 microsatellites. The home range of a female snow leopard marked with a satellite Global Positioning System (GPS) collar was represented by the minimum convex polygon method (MCP) 100, the MCP 95 method and the fixed kernel 95 method. The results revealed insignificant genetic differentiation between snow leopards that inhabit both massifs (minimal fixation index [FST]), and the data testify to the unity of the cross-border group. Moreover, 5 common individuals were identified from Mongolian and Russian territories. This finding clearly shows that their home range includes territories of both countries. In addition, regular movement of a collared snow leopard in Mongolia and Russia confirmed the existence of a cross-border snow leopard group. These data support that trans-boundary conservation is important for snow leopards in both countries. We conclude that it is crucial for Russia to study the northern range of snow leopards in Asia.
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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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Thapa, K., Schmitt, N., Pradhan, N. M. B., Acharya, H. R., Rayamajhi, S. (2021). No silver bullet? Snow leopard prey selection in Mt. Kangchenjunga, Nepal. Ecology and Evolution, , 1–13.
Abstract: In this study, we investigated the impact of domestic and wild prey availability on snow leopard prey preference in the Kangchenjunga Conservation Area of eastern Nepal-a region where small domestic livestock are absent and small wild ungulate prey are present. We took a comprehensive approach that combined fecal genetic sampling, macro- and microscopic analyses of snow leopard diets, and direct observation of blue sheep and livestock in the KCA. Out of the collected 88 putative snow leopard scat samples from 140 transects (290km) in 27 (4x4km2) sampling grid cells, 73 (83%) were confirmed to be from snow leopard. The genetic analysis accounted for 19 individual snow leopards (10 males and 9 females), with a mean population size estimate of 24 (95% CI: 19-29) and an average density of 3.9 snow leopards/100km2 within 609km2. The total available prey biomass of blue sheep and yak was estimated at 355,236 kg (505 kg yak/km2 and 78kg blue sheep/km2). From the available prey biomass, we estimated snow leopards consumed 7% annually, which comprised wild prey (49%), domestic livestock (45%). and 6% unidentified items. the estimated 47,736 kg blue sheep biomass gives a snow leopard-to-blue sheep ratio of 1:59 on a weight basis. The high preference of snow leopard to domestic livestock appears to be influenced by a much smaller available biomass of wild prey then in other regions of Nepal (e.g., 78kg/km2 in the KCA compared with a range of 200-300 kg/km2 in other regions of Nepal?. Along with livestock insurance scheme improvement, there needs to be a focus on improved livestock guarding, predator-proof corrals as well as engaging and educating local people to be citizen scientists on the importance of snow leopard conservation, involving them in long-term monitoring programs and promotion of ecotourism.
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Thapa, K., Jackson, R., Gurung, L, Acharya, H. B., Gurung, R. K.,. (2021). Applying the double observer methodology for assessing blue sheep population size in Nar Phu valley, Annapurna Conservation Area, Nepal. Wildlife Biology, , 1–11.
Abstract: This study was undertaken in spring, 2019 to assess the applicability of the double-observer survey method for estimating blue sheep Pseudois nayaur abundance in Nar-Phu valley of Manang District located in Annapurna Conservation Area of northern Nepal. Since counting large mammals in rugged mountain habitat poses a special challenge, we tested the efficacy of the double observer method for generating robust population estimates for this important protected area. The overall detection probability for observers (O1 and O2) was 0.94 and 0.91 for a total of 106 groups comprised of 2059 individual blue sheep. We estimated the area’s blue sheep population at 2070 (SE ± 168.77; 95% CI 2059–2405) for the 246.2 km2 of sampled habitat. We determined blue sheep to be widely distributed within the study area with a mean density of 8.4 individuals per km2 based on a total study area of 246.2 km2. We discuss demographic population structure and identify limitations when applying the double observer approach, along with recommending viewshed mapping for ensuring more robust density estimates of mountain-dwelling ungulates like blue sheep or ibex that inhabit extremely heterogeneous terrain which strongly influences sighting distances and overall animal detection rates.
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