Snow Leopard Bibliography -- Query Results

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. Keywords: abundance; camera,capture-recapture,density,index,predator:prey ratios,techniques,Tien Shan,Uncia; leopard; SaryChat; sign surveys; Slims; snow; snow-leopard; snow leopard; Tomur https://snowleopardnetwork.org/b/show.php?record=653
Waits, L. P., Buckley-Beason, V. A., Johnson, W. E., Onorato, D., & McCarthy, T. (2006). A select panel of polymorphic microsatellite loci for individual identification of snow leopards (Panthera uncia) (Vol. 7). Abstract: Snow leopards (Panthera uncia) are elusive endangered carnivores found in remote mountain regions of Central Asia. New methods for identifying and counting snow leopards are needed for conservation and management efforts. To develop molecular genetic tools for individual identification of hair and faecal samples, we screened 50 microsatellite loci developed for the domestic cat (Felis catus) in 19 captive snow leopards. Forty-eight loci were polymorphic with numbers of alleles per locus ranging from two to 11. The probability of observing matching genotypes for unrelated individuals (2.1 x10-11) and siblings (7.5x10-5) using the 10 most polymorphic loci was low, suggesting that this panel would easily discriminate among individuals in the wild. Keywords: identification; leopard; leopards; microsatellites,noninvasive genetic sampling,Panthera uncia,snow leopard; panthera; Panthera-uncia; panthera uncia; snow; snow-leopard; snow-leopards; snow leopard; snow leopards; uncia; endangered; carnivores; carnivore; mountain; region; central; Central Asia; asia; methods; conservation; management; Molecular; individual identification; Hair; domestic; cat; felis; captive; number; probability; using; wild https://snowleopardnetwork.org/b/show.php?record=1001

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.

Keywords: abundance; camera,capture-recapture,density,index,predator:prey ratios,techniques,Tien Shan,Uncia; leopard; SaryChat; sign surveys; Slims; snow; snow-leopard; snow leopard; Tomur

https://snowleopardnetwork.org/b/show.php?record=653

Abstract: Snow leopards (Panthera uncia) are elusive endangered carnivores found in remote mountain regions of Central Asia. New methods for identifying and counting snow leopards are needed for conservation and management efforts. To develop molecular genetic tools for individual identification of hair and faecal samples, we screened 50 microsatellite loci developed for the domestic cat (Felis catus) in 19 captive snow leopards. Forty-eight loci were polymorphic with numbers of alleles per locus ranging from two to 11. The probability of observing matching genotypes for unrelated individuals (2.1 x10-11) and siblings (7.5x10-5) using the 10 most polymorphic loci was low, suggesting that this panel would easily discriminate among individuals in the wild.