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: In the 1960s, the endangered snow leopard was locally extirpated from the Sagarmatha (Mt. Everest) region of Nepal. In this Sherpa-inhabited high Himalaya, the flourishing tourism since the ascent of Mt Everest in 1953, has caused both prosperity and adverse impacts, the concern that catalyzed the establishment of Mt. Everest National Park in the region in 1976. In the late 1980s, there were reports that some transient snow leopards may have visited the area from adjoining Tibet, but no biological surveys exist to confirm the status of the cats and their prey. Have snow leopards finally returned to the top of the world? Exploring this question was the main purpose of this research project. We systematically walked altogether 24 sign transects covering over 13 km in length in three valleys, i.e. Namche, Phortse and Gokyo, of the park, and counted several snow leopard signs. The results indicated that snow leopards have made a comeback in the park in response to decades of protective measures, the virtual cessation of hunting and the recovery of the Himalayan tahr which is snow leopard's prey. The average sign density (4.2 signs/km and 2.5 sign sites/km) was comparable to that reported from other parts of the cats' range in the Himalaya. On this basis, we estimated the cat density in the Everest region between 1 to 3 cats per 100 sq km, a figure that was supported by different sets of pugmarks and actual sightings of snow leopards in the 60 km2 sample survey area. In the study area, tahr population had a low reproductive rate (e.g. kids-to-females ratio, 0.1, in Namche). Since predators can influence the size and the structure of prey species populations through mortality and through non-lethal effects or predation risk, snow leopards could have been the cause of the population dynamics of tahr in Sagarmtha, but this study could not confirm this speculation for which further probing may be required.

Abstract: The author discusses the distribution of snow leopards along the border of Russia and Mongolia. The range extension of the leopard indicates their ability to cross desert areas that separate mountain habitats.habitat; range extension; scat analysis; techniques; tracks/tracking | snow leopard

Abstract: Mankial is a sub-valley of the Swat Kohistan. Temperate ecosystem of the valley is intact to a greater extent, which provides habitat to a variety of species of plants, animals and birds. Snow leopard is reported from the valley. To confirm its occurrence, the HUJRA (Holistic Understanding for Justified Research and Action), conducted the study titled “Snow Leopard Survey in Mankial Valley, district Swat, NWFP”. The author provided technical support, while ISLT (The International Snow Leopard Trust) funded the project under its small grants program. The World Wide Fund for Nature-Pakistan (WWF-Pakistan) and the Mankial Community Organization (MCO) facilitated surveys under the project. Surveys revealed that Snow leopard visits parts of the Mankial valley in winter months. Information from the local community shows that Snow leopard remains in the Serai (an off-shoot of the Mankial Valley) from early winter to early spring. Intensive surveys of the prime snow leopard winter habitat in the valley found several snow leopard signs including pugmarks, feces, and scrapes. The study also found occurrence of prey species through indirect evidence though. However, information from the local community confirmed that in the recent past there was a good population of markhor in the valley, which is now reduced to less than 50, mostly due to hunting and habitat disturbance. Hunting is part of the local culture and lifestyle. During winter months hunting pressure is low, as most of the local community migrates to warmer plain areas than Mankial Valley. However, those who live in the area lop oak branches for feeding their livestock and cut trees for burning, in addition to hunting prey species of snow leopard. This has resulted in stunted oak vegetation in most of the lower reaches of the valley and decline of the markhor population.

Abstract: The snow leopard (Panthera uncia Schreber, 1776) population in Russia and Mongolia is situated at the northern edge of the range, where instability of ecological conditions and of prey availability may serve as prerequisites for demographic instability and, consequently, for reducing the genetic diversity. Moreover, this northern area of the species distribution is connected with the western and central parts by only a few small fragments of potential habitats in the Tian-Shan spurs in China and Kazakhstan. Given this structure of the range, the restriction of gene flow between the northern and other regions of snow leopard distribution can be expected. Under these conditions, data on population genetics would be extremely important for assessment of genetic diversity, population structure and gene flow both at regional and large-scale level. To investigate large-scale and fine-grain population structure and levels of genetic diversity we analyzed 108 snow leopards identified from noninvasively collected scat samples from Russia and Mongolia (the northern part of the range) as well as from Kyrgyzstan and Tajikistan (the western part of the range) using panel of eight polymorphic microsatellites. We found low to moderate levels of genetic diversity in the studied populations. Among local habitats, the highest heterozygosity and allelic richness were recorded in Kyrgyzstan (He = 0.66 ± 0.03, Ho = 0.70 ± 0.04, Ar = 3.17) whereas the lowest diversity was found in a periphery subpopulation in Buryatia Republic of Russia (He = 0.41 ± 0.12, Ho = 0.29 ± 0.05, Ar = 2.33). In general, snow leopards from the western range exhibit greater genetic diversity (He = 0.68 ± 0.04, Ho = 0.66 ± 0.03, Ar = 4.95) compared to those from the northern range (He = 0.60 ± 0.06, Ho = 0.49 ± 0.02, Ar = 4.45). In addition, we have identified signs of fragmentation in the northern habitat, which have led to significant genetic divergence between subpopulations in Russia. Multiple analyses of genetic structure support considerable genetic differentiation between the northern and western range parts, which may testify to subspecies subdivision of snow leopards from these regions. The observed patterns of genetic structure are evidence for delineation of several management units within the studied populations, requiring individual approaches for conservation initiatives, particularly related to translocation events. The causes for the revealed patterns of genetic structure and levels of genetic diversity are discussed.

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: 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.