Sharma, R. (2010). Of Men and Mountain Ghosts: Glimpses from the Rooftop of the World. GEO, 3(6), 56–67.
Abstract: Catching a glimpse of a snow leopard is a rare and exciting event for anyone. For researchers, hideen camera traps have become a vital tool in their work.
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Portland Zoological Society. (1976). Snow leopards, animals of the month (Vol. 5).
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Sharma, K. (2008). The mysterious irbis. Sanctuary Asia, 28(6), 52–57.
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Singh, R., Krausman, P. R., Pandey, P., Maheshwari, A., Rawal,
R. S., Sharma, S., Shekhar, S. (2020). Predicting Habitat Suitability of Snow Leopards in the Western
Himalayan Mountains, India. Biology bulletin, 47(6), 655–664.
Abstract: The population of snow leopard (Panthera uncia) is declining
across their range, due to poaching, habitat fragmentation, retaliatory
killing, and a decrease of wild prey species. Obtaining information on
rare and cryptic predators living in remote and rugged terrain is
important for making conservation and management strategies. We used the
Maximum Entropy (MaxEnt) ecological niche modeling framework to predict
the potential habitat of snow leopards across the western Himalayan
region, India. The model was developed using 34 spatial species
occurrence points in the western Himalaya, and 26 parameters including,
prey species distribution, temperature, precipitation, land use and land
cover (LULC), slope, aspect, terrain ruggedness and altitude. Thirteen
variables contributed 98.6% towards predicting the distribution of snow
leopards. The area under the curve (AUC) score was high (0.994) for the
training data from our model, which indicates pre- dictive ability of
the model. The model predicted that there was 42432 km2 of potential
habitat for snow leop- ards in the western Himalaya region. Protected
status was available for 11247 km2 (26.5%), but the other 31185 km2
(73.5%) of potential habitat did not have any protected status. Thus,
our approach is useful for predicting the distribution and suitable
habitats and can focus field surveys in selected areas to save
resources, increase survey success, and improve conservation efforts for
snow leopards.
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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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Johansson, O., Ullman, K., Lkhagvajav, P., Wiseman, M.,
Malmsten, J., Leijon, M. (2020). Detection and Genetic Characterization of Viruses Present in
Free-Ranging Snow Leopards Using Next-Generation Sequencing. Frontiers in Veterinary Science, 7(645), 1–9.
Abstract: Snow leopards inhabit the cold, arid environments of the high
mountains of South and Central Asia. These living conditions likely
affect the abundance and composition of microbes with the capacity to
infect these animals. It is important to investigate the microbes that
snow leopards are exposed to detect infectious disease threats and
define a baseline for future changes that may impact the health of this
endangered felid. In this work, next-generation sequencing is used to
investigate the fecal (and in a few cases serum) virome of seven snow
leopards from the Tost Mountains of Mongolia. The viral species to which
the greatest number of sequences reads showed high similarity was
rotavirus. Excluding one animal with overall very few sequence reads,
four of six animals (67%) displayed evidence of rotavirus infection. A
serum sample of a male and a rectal swab of a female snow leopard
produced sequence reads identical or closely similar to felid
herpesvirus 1, providing the first evidence that this virus infects snow
leopards. In addition, the rectal swab from the same female also
displayed sequence reads most similar to feline papillomavirus 2, which
is the first evidence for this virus infecting snow leopards. The rectal
swabs from all animals also showed evidence for the presence of small
circular DNA viruses, predominantly Circular Rep-Encoding
Single-Stranded (CRESS) DNA viruses and in one case feline anellovirus.
Several of the viruses implicated in the present study could affect the
health of snow leopards. In animals which are under environmental
stress, for example, young dispersing individuals and lactating females,
health issues may be exacerbated by latent virus infections.
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Mayo, J. G. (1967). Report on the tranquillisation of a male Snow leopard Panthera uncia for semen extraction. International Zoo Yearbook, VII(7), 148–150.
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Blomqvist, L. (1979). The 1978 register for the captive population of snow leopards, Panthera uncia. International Zoo News, 26(7-8), 17–23.
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McCarthy, K., Fuller, T., Ming, M., McCarthy, T., Waits, L., & Jumabaev, K. (2008). Assessing Estimators of Snow Leopard Abundance (Vol. 72).
Abstract: The secretive nature of snow leopards (Uncia uncia) makes them difficult to monitor, yet conservation efforts require accurate and precise methods to estimate abundance. We assessed accuracy of Snow Leopard Information Management System (SLIMS) sign surveys by comparing them with 4 methods for estimating snow leopard abundance: predator:prey biomass ratios, capture-recapture density estimation, photo-capture rate, and individual identification through genetic analysis. We recorded snow leopard sign during standardized surveys in the SaryChat Zapovednik, the Jangart hunting reserve, and the Tomur Strictly Protected Area, in the Tien Shan Mountains of Kyrgyzstan and China. During June-December 2005, adjusted sign averaged 46.3 (SaryChat), 94.6 (Jangart), and 150.8 (Tomur) occurrences/km. We used
counts of ibex (Capra ibex) and argali (Ovis ammon) to estimate available prey biomass and subsequent potential snow leopard densities of 8.7 (SaryChat), 1.0 (Jangart), and 1.1 (Tomur) snow leopards/100 km2. Photo capture-recapture density estimates were 0.15 (n = 1 identified individual/1 photo), 0.87 (n = 4/13), and 0.74 (n = 5/6) individuals/100 km2 in SaryChat, Jangart, and Tomur, respectively. Photo-capture rates
(photos/100 trap-nights) were 0.09 (SaryChat), 0.93 (Jangart), and 2.37 (Tomur). Genetic analysis of snow leopard fecal samples provided minimum population sizes of 3 (SaryChat), 5 (Jangart), and 9 (Tomur) snow leopards. These results suggest SLIMS sign surveys may be affected by observer bias and environmental variance. However, when such bias and variation are accounted for, sign surveys indicate relative abundances similar to photo rates and genetic individual identification results. Density or abundance estimates based on capture-recapture or ungulate biomass did not agree with other indices of abundance. Confidence in estimated densities, or even detection of significant changes in abundance of snow leopard, will require more effort and better documentation.
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