Abstract: International collaboration to ensure the long-term survival of snow leopards (Uncia uncia) in the wild is today more acutely needed than ever! Trade in live snow leopards, their skins and bones, has during the last decade reached such extensiveness that the species is in danger of being wiped out from many of its former habitats. All recent surveys support declining populations throughout most of their range.

Abstract: The endangered snow leopard Panthera uncia occurs in rugged, high-altitude regions of Central Asia. However, information on the status of this felid is limited in many areas. We conducted a pilot study to optimize molecular markers for the analysis of snow leopard scat samples and to examine the feasibility of using noninvasive genetic methods for monitoring this felid. We designed snow leopard-specific primers for seven microsatellite loci that amplified shorter segments and avoided flanking sequences shared with repetitive elements. By redesigning primers we maximized genotyping success and minimized genotyping errors. In addition, we tested a Y chromosome-marker for sex identification and designed a panel of mitochondrial DNA primers for examining genetic diversity of snow leopards using scat samples. We collected scats believed to be from snow leopards in three separate geographic regions including north-western India, central China and southern Mongolia. We observed snow leopard scats in all three sites despite only brief 2-day surveys in each area. There was a high rate of species misidentification in the field with up to 54% of snow leopard scats misidentified as red fox. The high rate of field misidentification suggests sign surveys incorporating scat likely overestimate snow leopard abundance. The highest ratio of snow leopard scats was observed in Ladakh (India) and South Gobi (Mongolia), where four and five snow leopards were detected, respectively. Our findings describe a species-specific molecular panel for analysis of snow leopard scats, and highlight the efficacy of noninvasive genetic surveys for monitoring snow leopards. These methods enable large-scale noninvasive studies that will provide information critical for conservation of snow leopards.

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.

Abstract: During 1984-1987, 1992-1995, and 1998-2001, the author researched snow leopard, white lipped deer, kiang, and argali in Qinghai, Gansu, Xingiang, and Sichuan. He collected 644 snow leopard droppings, and analyzed kinds of foods and sources from perch. Snow leopard's foods include most main foods, main foods, comparative foods and lesser foods. Studied one another
index of faunistic congruence of foods species that from various distribution and variation both perch vertical variety and foods of snow leopard.

Abstract: The snow leopard and it s p rey were investigated in Beita Mountain Region , Xinjiang in Sep . 2004.
Both the field survey and questionnaire were involved in this project which was supported by the International
Snow Leopard Trust and Xinjiang Conservation Fund. The signs marked by the snow leopard were used
to reflect the living condition of snow leopard and they were collected by running transects. The prey investigation was conducted by positioned observation and route survey. Fifteen transects were done in the
project and 67 signs leaved by snow leopard were discovered in total. 58. 2 % of them were scrapes ,
35.8 % of t hem were feces , 4.5 % of them were claw rakes and 1. 5 % of them were scent
spray. As to the prey resources , 4 herds of 23 ibex and 24 herds of 418 chukars were found during the survey. Also 81 local people of 5 different nationalities were interviewed during the field work , 13.
58 % of them had seen the snow leopard , 20. 99 % of them had heard of snow leopard but not seen. Among t hem , 10 herdsmen had sufferred from the loss of livestock attacked by snow leopard.