Abstract: The availability of wild prey is a critical predictor of carnivore density. However, few conservation pro- grammes have focused on the estimation and monitoring of wild ungulate populations and their trends, especially in the remote mountains of Central Asia. We conducted double-observer surveys to estimate the populations of ibex Capra sibirica and argali Ovis ammon in the mountain- ous regions of Tost Local Protected Area, South Gobi prov- ince, Mongolia, which is being considered for designation as a Nature Reserve. We also conducted demographic surveys of the more abundant ibex to examine their sex-ratio and the survival of young during –. The estimated ibex population remained stable in  and  and the es- timated argali population increased from  in  to  in . The biomass of wild ungulates was c. % that of live- stock. Mortality in young ibex appeared to increase after weaning, at the age of  months. We estimated the popula- tion of wild ungulates was sufficient to support – adult snow leopards Panthera uncia. The adult snow leopard population in our study area during –, estimated independently using camera-trap-based mark–recapture methods, was –. Based on our results we identify the Tost Local Protected Area as an important habitat for the conservation of these ungulates and their predator, the Endangered snow leopard, and recommend elevation of its status to a Nature Reserve.

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: Kyrgyzstan is a land of towering mountains, glaciers, rushing streams, wildflowercovered meadows, forests, snow leopards, soaring eagles, and yurt-dwelling nomads. The entire nation lies astride the Tian Shan1, Chinese for “Heavenly Mountains”, one of the world's highest mountain ranges, which is 7439 m (24,400 ft) in elevation at its highest point. The nation is the second smallest of the former Soviet Central Asian republics. In
spite of Kyrgyzstan's diverse wildlife and stunning natural beauty, the nation remains little known, and, as yet, still on the frontier of international conservation efforts. The following report is the product of 12 months of research into the state of conservation and land-use in Kyrgyzstan. This effort was funded by the Fulbright Commission of the U.S. State Department, and represents the most recent findings of the author's personal environmental journey through Inner Asia, which began in 1999. When I first started my preliminary research for this project, I was extremely surprised to learn that, even though the Tian Shan Range has tremendous ecological significance for conservation efforts in middle Asia, there wasn't a single major international conservation organization with an office in the former Soviet Central Asian republics. Even more surprising was how little awareness there is of conservation issues in the Tian Shan region amongst conservation workers in neighboring areas who are attempting to preserve similar species assemblages and ecosystems to those found in the Tian Shan. Given this lack of awareness, and the great potential for the international community to make a positive contribution towards improving the current state of biodiversity conservation in Kyrgyzstan and Central Asia, I have summarized my findings on protected areas and conservation in Kyrgyzstan and the Tian Shan of Kazakhstan, Uzbekistan, and Xinjiang in the chapters below. The report begins with some brief background information on geography and society in the Kyrgyz Republic, followed by an overview of biodiversity and the state of conservation in the nation, which at the present time closely parallels the state of conservation in the other former Soviet Central Asian republics. Part IV of the report provides a catalog of all major protected areas in Kyrgyzstan and the other Tian Shan nations, followed by a list of sites in Kyrgyzstan that are as yet unprotected but merit protection. In the appendices the reader will find fairly comprehensive species lists of flora and fauna found in the Kyrgyz Republic, including lists of mammals, birds, fish, reptiles, amphibians, trees and shrubs, wildflowers, and endemic plants. In addition, a
draft paper on the history and current practice of pastoral nomadism in Kyrgyzstan has been included in Appendix A. While the research emphasis for this study was on eastern Kyrgyzstan, over the course of the study the author did have the opportunity to make brief journeys to southern Kyrgyzstan, Uzbekistan, Kazakhstan, and Xinjiang. While falling short of being a definitive survey of protected areas of the Tian Shan, the informational review which
follows is the first attempt at bringing the details of conservation efforts throughout the entire Tian Shan Range together in one place. It is hoped that this summary of biodiversity and conservation in the Tian Shan will generate interest in the region amongst conservationists, and help increase efforts to protect this surprisingly unknown range that forms an island of meadows, rivers, lakes, and forests in the arid heart of Asia.

Abstract: This handbook provides an introduction to snow leopard population survey techniques, followed by a detailed account of camera trapping methods.During the 2002 through 2004 winter field seasons, the Snow Leopard Conservancy experimented with infrared camera trapping techniques to define a methodology suitable for the high altitude environment.
In 2001 and 2002, much of our time was spent familiarizing ourselves with various infrared camera traps, their operation and setup, and comparing the effectiveness of different models and sensor types. We placed infrared camera traps along frequently used travel corridors at or near scent-sprayed rocks (rock scents) and scrape sites within 16 km2 sampling cells between January and March in 2003 and 2004. A total of 66 and 49 captures of snow leopards were tallied during 2003 and 2004, resulting in an overall capture success of 8.91 and 5.63 individuals per 100 trap-nights, respectively. Capture probabilities ranged from 0.33 to 0.46. Density estimates ranged from 8.49 ± 0.22 individuals per 100 km2 in 2003 to 4.45 ± 0.16 in 2004, with the disparity between years largely attributed to different trapping densities. Snow leopard abundance estimates were calculated using the computer program CAPTURE.