Roth, T. L., Armstrong, D. L., Barrie, M. T., & Wildt, D. E. (1997). Seasonal effects on ovarian responsiveness to exogenous gonadotrophins and successful artificial insemination in the snow leopard (Uncia uncia). Reprod Fertil Dev, 9(3), 285–295.
Abstract: Ovaries of the seasonally-breeding snow leopard (Uncia uncia) were examined to determine whether they were responsive to exogenous gonadotrophins throughout the year. The potential of laparoscopic artificial insemination (AI) also was assessed for producing offspring. During the non-breeding, pre-breeding, breeding and post-breeding seasons, females (n = 20) were treated with a standardized, dual- hormone regimen given intramuscularly (600 I.U. of equine chorionic gonadotrophin followed 80-84 h later with 300 I.U. of human chorionic gonadotrophin (hCG)). Laparoscopy was performed 45-50 h after administration of hCG, and all ovarian structures were described. Females with fresh corpora lutea (CL) were inseminated, and anovulatory females were subjected to follicular aspiration to examine oocyte quality. Snow leopards responded to exogenous gonadotrophins throughout the year. Mean number of total ovarian structures (distinct follicles mature in appearance plus CL) did not differ (P > or = 0.05) with season, but the proportion of CL: total ovarian structures was greater (P < 0.01) for the breeding season compared with all other seasons. The proportion of females ovulating was greater (P < 0.05) during the breeding and post-breeding seasons than during the pre-breeding and non- breeding seasons respectively. No Grade-1 quality oocytes were recovered from follicles of anovulatory females. Serum concentrations of oestradiol-17 beta appeared elevated in all females, and neither oestradiol-17 beta concentrations nor progesterone concentrations differed (P > or = 0.05) among seasons. Of 15 females artificially inseminated, the only one that was inseminated in the non-breeding season became pregnant and delivered a single cub. This is the first successful pregnancy resulting from AI in this endangered species.
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International Union for the Conservation of Nature. (1972). Snow leopard, Panthera uncia (Schreber 1776). In Red Data Book (Vol. 12).
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Anonymous. (1976). Red Data Book: Snow leopard, Schreber, 1776. In Red Data Book.
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Geits, A. V., Makarov, O.A. (1977). About the distribution of the snow leopard in the Altai. In V. E. Sokolov (Ed.), Rare Types of Mammals and Their Conservation (pp. 115–116).
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Portland Zoological Society. (1976). Snow leopards, animals of the month (Vol. 5).
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Freeman, H. (1979). Phantom cat. Puget Soundings, , 8–13.
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Jackson, R. M., Ahlborn, G., Gurung, M., & Ale, S. (1996). Reducing livestock depredation losses in the Nepalese Himalaya. Proc.Vertebr.Pest Conf, 17, 241–247.
Abstract: The authors investigated livestock depredation patterns of snow leopards on the northern slopes of the Himalayans near the villages of Manang and Khangshar, Nepal. Information is discussed on the relationships among livestock loss, endangered species management, public relations/conservation issues, and cooperative efforts among institutions involved in the decision making process. A plan is devised for alleviating livestock loss and protecting endangered species in the area. pcp
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Isenbugel, E., & Weilenmann, P. (1985). Colobomes of the Eyelid in an Ounce T (UNCIA-UNCIA, SCHREBER 1775) from the Zurich-Zoological-Garden. Praktische Tierarzt, 66(1), 61–62.
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Sharma, K., McCarthy, T. (2011). Counting cats: toward a framework for evaluating snow leopard (Panthera uncia) conservation efforts.
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Suryawanshi, K. R., Khanyari, M., Sharma, K., Lkhagvajav, P., Mishra, C. (2019). Sampling bias in snow leopard population estimation studies. Population Eccology, , 1–9.
Abstract: Accurate assessments of the status of threatened species and their conservation
planning require reliable estimation of their global populations and robust monitoring
of local population trends. We assessed the adequacy and suitability of studies
in reliably estimating the global snow leopard (Panthera uncia) population. We
compiled a dataset of all the peer-reviewed published literature on snow leopard
population estimation. Metadata analysis showed estimates of snow leopard density
to be a negative exponential function of area, suggesting that study areas have generally
been too small for accurate density estimation, and sampling has often been
biased towards the best habitats. Published studies are restricted to six of the
12 range countries, covering only 0.3�0.9% of the presumed global range of the
species. Re-sampling of camera trap data from a relatively large study site
(c.1684 km2) showed that small-sized study areas together with a bias towards
good quality habitats in existing studies may have overestimated densities by up to
five times. We conclude that current information is biased and inadequate for generating
a reliable global population estimate of snow leopards. To develop a rigorous
and useful baseline and to avoid pitfalls, there is an urgent need for
(a) refinement of sampling and analytical protocols for population estimation of
snow leopards (b) agreement and coordinated use of standardized sampling protocols
amongst researchers and governments across the range, and (c) sampling
larger and under-represented areas of the snow leopard's global range.
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