Abstract: Reports on 1 summer survey and four winter surveys covering some 3100 km in Ladakh, India. Reports on snow leopard sign commonly found, distribution, prey, attacks on livestock and peoples reaction, mortality factors and conservation status. Suggest recomendations for preventing unnecessary killing of snow leopards and estimates population of 100 to 200 snow leopards in Ladakh

Abstract: The Chinese magazine <Man & the Biosphere> (Series No. 54, No. 6, 2008) -- A special series for the conservation of Snow Leopards was published by the Chinese National Committee for Man & the Biosphere in 15th December 2008. It is about 80 pages including ten articles with 200 color pictures. The special editors of this issue are the experts from SLT/XCF Prof. MaMing, Mrs. Ge Yun and Mr. Wen Bo. The first paper is “A King of Snow Peaks, Another Endangered Flagship Species” by Dr. Thomas McCarthy, Dr. Urs Breitenmmoser and Dr. Christine Breitenmoser-Wursten (Page 1-1). Another paper “ Conservation : Turning Awareness to Action ” is also from Dr. Thomas McCarthy (Pages from 6-17). There are four articles including the diary and story of the Surveys in Tomur Mountain and Kunlun Mountains written by Prof. MaMing, Mr. XuFeng, Miss Chen Ying and Miss Cheng Yun from the Xinjiang Snow Leopard Group and XCF, the Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences. The last is “Snow Leopard Enterprises ” -- A Story from Mongolia by Mrs. Jennifer Snell Rullman and Mrs. Agvaantseren Bayarjargal (Bayara). It is a very useful copy for the conservation in China. Cited as:
Ma Ming, GeYun and WenBo (Special editors of this issue). 2008. The special series for the conservation of Snow Leopards in China. Man & the Biosphere 2008(6): 1-80. Contents 1, A king of snow peaks, another endangered flagship species (Synopsis) ------------- 1-1 The contents --------------------------------------------- ( pages from 2-3 )
2, Protecting Snow Leopard means protecting a healthy eco-systems -------------- 4-5
3, Conservation: Turning awareness into action -------------- 6-17
4, Chinese Snow Leopard Team goes into action -------------- 18-25
5, A diary of infrared photography -------------- 26-35
6, Why have the snow leopards in the Tianshan Mountains begun to attack livestock? --- 36-43
7, The mystery of the Snow Leopards coming down the Tianshan Mountains ----------- 44-45
8, Snow leopards secluded Home on the Plateau ------------- 46-59
9, He saw Snow Leopards 30 years ago ------------- 60-69
10, Snow Leopard Enterprises -- A story from Mongolia ------------- 70-80

Abstract: Spatial capture–recapture (SCR) methods use the location of
detectors (camera traps, hair snares and live-capture traps) and the
locations at which animals were detected (their spatial capture
histories) to estimate animal density. Despite the often large expense
and effort involved in placing detectors in a landscape, there has been
relatively little work on how detectors should be located. A natural
criterion is to place traps so as to maximize the precision of density
estimators, but the lack of a closed-form expression for precision has
made optimizing this criterion computationally demanding. 2. Recent
results by Efford and Boulanger (2019) show that precision can be well
approximated by a function of the expected number of detected
individuals and expected number of recapture events, both of which can
be evaluated at low computational cost. We use these results to develop
a method for obtaining survey designs that optimize this approximate
precision for SCR studies using count or binary proximity detectors, or
multi-catch traps. 3. We show how the basic design protocol can be
extended to incorporate spatially varying distributions of activity
centres and animal detectability. We illustrate our approach by
simulating from a camera trap study of snow leopards in Mongolia and
comparing estimates from our designs to those generated by regular or
optimized grid designs. Optimizing detector placement increased the
number of detected individuals and recaptures, but this did not always
lead to more precise density estimators due to less precise estimation
of the effective sampling area. In most cases, the precision of density
estimators was comparable to that obtained with grid designs, with
improvement in some scenarios where approximate CV(¬D) < 20% and density
varied spatially. 4. Designs generated using our approach are
transparent and statistically grounded. They can be produced for survey
regions of any shape, adapt to known information about animal density
and detectability, and are potentially easier and less costly to
implement. We recommend their use as good, flexible candidate designs
for SCR surveys when reasonable knowledge of model parameters exists. We
provide software for researchers to construct their own designs, in the
form of updates to design functions in the r package oSCR.

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.