Abstract: This study was carried out in the Kangchenjunga Conservation Area (KCA), Eastern Nepal from Feb – Nov 2007. We used the Snow Leopard Information Management System, SLIMS (second order survey technique) to determine the relative abundance of snow leopard in the upper part of KCA. Altogether, 36 transects (total length of 15.21 km) were laid down in the major three blocks of KCA. 104 Signs (77 scrapes, 20 feces, 2 Scent mark, 3 Pugmarks and 2 hairs) were recorded. Fixed-point count method was applied for blue sheep from appropriate vantage points. We counted total individual in each herd using 8x42 binocular and 15-60x spotting scope. A total of 43 herds and 1102 individuals were observed in the area. The standard SLIMS questionnaire was conducted to find out relevant information on livestock depredation patterns. Out of 35 households surveyed in KCA, 48% of herders lost livestock due to snow leopards. A total of 21 animals were reportedly lost due to snow leopards from August to September 2007.

Abstract: Livestock depredation by the endangered snow leopard (Panthera uncia) _is an increasingly contentious issue in Himalayan villages, especially in or near protected areas. Mass attacks in which as many as 100 sheep and goats are killed in a single incident inevitably result in retaliation by local villagers. This article describes a community-based conservation initiative to address this problem in Hemis National Park, India. Human-wildlife conflict is alleviated by predator-proofing villagers' nighttime livestock pens and by enhancing household incomes in environmentally sensitive and culturally compatible ways. The authors have found that the highly participatory strategy described here (Appreciative Participatory Planning and Action-APPA) leads to a sense of project ownership by local stakeholders, communal empowerment, self-reliance, and willingness to co-exist with
snow leopards. The most significant conservation outcome of this process is the protection from retaliatory poaching of up to five snow leopards for every village's livestock pens that are made predator-proof._

Abstract: Livestock depredation is emerging as a significant issue across the Himalaya, including the Hemis National Park (HNP) in Ladakh. Some consider that this protected area harbors the best snow leopard population in India, but local herders perceive the endangered snow leopard as a serious threat to their livelihood.

Abstract: The World Conservation Union listed the snow leopard (Uncia uncia) as endangered in 1974. With as few as 3,500 snow leopards left in the wild, scientists placed the snow leopard on the IUCN Red List of critically endangered species shared by animals such as the giant panda and tiger. In an effort to save the snow leopard from extinction, former zoo employee Helen Freeman founded the Snow Leopard Trust in 1981. The Snow Leopard Trust works to save this elusive cat by incorporating community-based conservation projects. One of these project Leopard Enterprise (SLE), impacts poverty stricken communities in Mongolia, Kyrgyz Republic, and Pakistan. It assists over 300 families in its conservation efforts. The economic incentives provided via SLE have led participating communities not to harm the snow leopard or its prey, and to practice sustainable herding. Since the project began in 1997, the number of snow leopards harmed around the communities' territories has dropped to near zero. Additionally, the annual income of families that utilize the benefits of SLE has increased by 25% to 40%. SLE creates this economic benefit by providing the training and equipment necessary to make desirable products from the wool of herd animals. Snow Leopard Trust then purchases these handicraft items from the local people and them globally. Zoos can expand their conservation efforts by simply offering these items in their gift shops. Woodland Park Zoo (WPZ) was the first zoological institution to sell the products, and WPZ continues to generate revenue from them. SLE is a golden opportunity for zoos to increase revenue, assist poor families, and save an endangered species and fragile ecosystem.

Abstract: Considerable efforts have been devoted to conserving the snow leopard Panthera uncia in recent years, but progress has inevitably been slow due to the difficulties of studying a sparsely distributed, secretive and endangered species in often isolated mountainous terrain. Although knowledge about the species overall distribution in the highlands of Central Asia still remains fragmenatry, it is important to briefly examine all the available information in order to review measures taken to date to conserve the species through the protected areas network. The purpose of this paper is to examine the distribution and status of protected areas inhabited or visited by snow leopard in relation to the species' distribution and highlight deficiences in the present network.

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: Photo-identification of individual snow leopards (Panthera uncia) is the primary data source for density estimation via capture-recapture statistical methods. To identify individual snow leopards in camera trap imagery, it is necessary to match individuals from a large number of images from multiple cameras and historical catalogues, which is both time-consuming and costly. The camouflaged snow leopards also make it difficult for machine learning to classify photos, as they blend in so well with the surrounding mountain environment, rendering applicable software solutions unavailable for the species. To potentially make snow leopard individual identification available via an artificial intelligence (AI) software interface, we first trained and evaluated image classification techniques for a convolutional neural network, pose invariant embeddings (PIE) (a triplet loss network), and compared the accuracy of PIE to that of the HotSpotter algorithm (a SIFT-based algorithm). Data were acquired from a curated library of free-ranging snow leopards taken in Afghanistan between 2012 and 2019 and from captive animals in zoos in Finland, Sweden, Germany, and the United States. We discovered several flaws in the initial PIE model, such as a small amount of background matching, that was addressed, albeit likely not fixed, using background subtraction (BGS) and left-right mirroring (LR) techniques which demonstrated reasonable accuracy (Rank 1: 74% Rank-5: 92%) comparable to the Hotspotter results (Rank 1: 74% Rank 2: 84%)The PIE BGS LR model, in conjunction with Hotspotter, yielded the following results: Rank-1: 85%, Rank-5: 95%, Rank-20: 99%. In general, our findings indicate that PIE BGS LR, in conjunction with HotSpotter, can classify snow leopards more accurately than using either algorithm alone.