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(1978). Miraki Reservation, Chatkal Reservation.
Abstract: It describes history of the Miraki and Chatkal nature reserves' establishment and provides data concerning area, landscapes, altitude zoning, flora and fauna as well as natural monuments.
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Alibekov L.A. (1978). Fauna.
Abstract: Represented is fauna of big salt-marsh valleys and pre-Kyzylkum area, a tier of low desert foothill valleys, tiers of lowland ridges, deeply cut hillside midlands, and cold highlands of the watershed ridge-top tier in the Jizak region of Uzbekistan. The highest tier of the Jizak region, a habitat of snow leopard, Menzbier's marmot, Siberian ibex, sometimes wild Tajik sheep coming from the East, bear ascending from lower elevations, and wolf in summer, has the most adverse living conditions. Central Asia argali and stone marten inhabit in central part of the North Nurata ridge.
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Allen, P., & Macray, D. (2002). Snow Leopard Enterprises Description and Summarized Business Plan.. Seattle: Islt.
Abstract: The habitat for both humans and snow leopards in Central Asia is marginal, the ecosystem fragile. The struggle for humans to survive has often, unfortunately, brought them into conflict with the region's dwindling snow leopard populations. Herders commonly see leopards as a threat to their way of life and well-being. Efforts to improve the living conditions of humans must consider potential impacts on the environment. Likewise, conservation initiatives cannot ignore humans as elements of the landscape with a right to live with dignity and pride. Based on these principles, the International Snow Leopard Trust has developed a new conservation model that addresses the needs of all concerned.
We call it Snow Leopard Enterprises..
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Atzeni, L., Wang, J., Riordan, P., Shi, K., Cushman, S. A. (2023). Landscape resistance to gene flow in a snow leopard population from Qilianshan National Park, Gansu, China. Landscape Ecology, .
Abstract: Context: The accurate estimation of landscape resistance to movement is important for ecological understanding and conservation applications. Rigorous estimation of resistance requires validation and optimization. One approach uses genetic data for the optimization or validation of resistance models. Objectives We used a genetic dataset of snow leopards from China to evaluate how landscape genetics resistance models varied across genetic distances and spatial scales of analysis. We evaluated whether landscape genetics models were superior to models of resistance derived from habitat suitability or isolation-by-distance.
Methods: We regressed genetically optimized, habitat-based, and isolation-by-distance hypotheses against genetic distances using mixed effect models. We explored all subset combinations of genetically optimized variables to find the most supported resistance scenario for each genetic distance.
Results: Genetically optimized models always out-performed habitat-based and isolation-by-distance hypotheses. The choice of genetic distances influenced the apparent influence of variables, their spatial scales and their functional response shapes, producing divergent resistance scenarios. Gene flow in snow leopards was largely facilitated by areas of intermediate ruggedness at intermediate elevations corresponding to small-to-large valleys within and between the mountain ranges.
Conclusions: This study highlights that landscape genetics models provide superior estimation of functional dispersal than habitat surrogates and suggests that optimization of genetic distance should be included as an optimization routine in landscape genetics, along with variables, scales, effect size and functional response shape. Furthermore, our study provides new insights on the ecological conditions that promote gene flow in snow leopards, which expands ecological knowledge, and we hope will improve conservation planning.
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Changxi, X., Bai, D., Lambert, J. P., Li, Y., Cering, L., Gong, Z., Riordan, P., Shi, K. (2022). How Snow Leopards Share the Same Landscape with Tibetan Agro-pastoral Communities in the Chinese Himalayas. Journal of Resources and Ecology, 13(3), 483–500.
Abstract: The snow leopard (Panthera uncia) inhabits a human-altered alpine landscape and is often tolerated by residents in regions where the dominant religion is Tibetan Buddhism, including in Qomolangma NNR on the northern side of the Chinese Himalayas. Despite these positive attitudes, many decades of rapid economic development and population growth can cause increasing disturbance to the snow leopards, altering their habitat use patterns and ultimately impacting their conservation. We adopted a dynamic landscape ecology perspective and used multi-scale technique and occupancy model to better understand snow leopard habitat use and coexistence with humans in an 825 km2 communal landscape. We ranked eight hypothetical models containing potential natural and anthropogenic drivers of habitat use and compared them between summer and winter seasons within a year. HABITAT was the optimal model in winter, whereas ANTHROPOGENIC INFLUENCE was the top ranking in summer (AICcw≤2). Overall, model performance was better in the winter than in the summer, suggesting that perhaps some latent summer covariates were not measured. Among the individual variables, terrain ruggedness strongly affected snow leopard habitat use in the winter, but not in the summer. Univariate modeling suggested snow leopards prefer to use rugged land in winter with a broad scale (4000 m focal radius) but with a lesser scale in summer (30 m); Snow leopards preferred habitat with a slope of 22° at a scale of 1000 m throughout both seasons, which is possibly correlated with prey occurrence. Furthermore, all covariates mentioned above showed inextricable ties with human activities (presence of settlements and grazing intensity). Our findings show that multiple sources of anthropogenic activity have complex connections with snow leopard habitat use, even under low human density when anthropogenic activities are sparsely distributed across a vast landscape. This study is also valuable for habitat use research in the future, especially regarding covariate selection for finite sample sizes in inaccessible terrain.
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Chetri, M., Odden, M., Sharma, K., Flagstad, O., Wegge, P. (2019). Estimating snow leopard density using fecal DNA in a large landscape in north-central Nepal. Global Ecology and Conservation, (17), 1–8.
Abstract: Although abundance estimates have a strong bearing on the conservation status of a
species, less than 2% of the global snow leopard distribution range has been sampled
systematically, mostly in small survey areas. In order to estimate snow leopard density
across a large landscape, we collected 347 putative snow leopard scats from 246 transects
(490 km) in twenty-six 5 5km sized sampling grid cells within 4393 km2 in Annapurna-
Manaslu, Nepal. From 182 confirmed snow leopard scats, 81 were identified as belonging
to 34 individuals; the remaining were discarded for their low (<0.625) quality index. Using
maximum likelihood based spatial capture recapture analysis, we developed candidate
model sets to test effects of various covariates on density and detection of scats on transects.
The best models described the variation in density as a quadratic function of
elevation and detection as a linear function of topography. The average density estimate of
snow leopards for the area of interest within Nepal was 0.95 (SE 0.19) animals per 100 km2
(0.66e1.41 95% CL) with predicted densities varying between 0.1 and 1.9 in different parts,
thus highlighting the heterogeneity in densities as a function of habitat types. Our density
estimate was low compared to previous estimates from smaller study areas. Probably,
estimates from some of these areas were inflated due to locally high abundances in overlap
zones (hotspots) of neighboring individuals, whose territories probably range far beyond
study area borders. Our results highlight the need for a large-scale approach in snow
leopard monitoring, and we recommend that methodological problems related to spatial
scale are taken into account in future snow leopard research.
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Hacker, C., Atzeni, L., Munkhtsog, B., Munkhtsog, B., Galsandorj, N., Zhang, Y., Liu, Y., Buyanaa, C., Bayandonoi, G., Ochirjav, M., Farrington, J. D., Jevit, M., Zhang, Y., Wu, L. Cong, W., Li, D., Gavette, C., Jackson, R., Janecka, J. E. (2022). Genetic diversity and spatial structures of snow leopards (Panthera uncia) reveal proxies of connectivity across Mongolia and northwestern China. Landscape Ecology, , 1–19.
Abstract: Understanding landscape connectivity and population genetic parameters is imperative for threatened species management. However, such information is lacking for the snow leopard (Panthera uncia). This study sought to explore hierarchical snow leopard gene flow patterns and drivers of genetic structure in Mongolia and China. A total of 97 individuals from across Mongolia and from the north-eastern edge of the Qinghai-Tibetan Plateau in Gansu Province to the middle of Qinghai Province in China were genotyped across 24 microsatellite loci. Distance-based frameworks were used to determine a landscape scenario best explaining observed genetic structure. Spatial and non-spatial methods were used to investigate fine-scale autocorrelation and similarity patterns as well as genetic structure and admixture. A genetic macro-division between populations in China and Mongolia was observed, suggesting that the Gobi Desert is a substantial barrier to gene flow. However, admixture and support for a resistance-based mode of isolation suggests connective routes that could facilitate movement. Populations in Mongolia had greater connectivity, indicative of more continuous habitat. Drivers of genetic structure in China were difficult to discern, and fine-scale sampling is needed. This study elucidates snow leopard landscape connectivity and helps to prioritize conservation areas. Although contact zones may have existed and occasional crossings can occur, establishing corridors to connect these areas should not be a priority. Focus should be placed on maintaining the relatively high connectivity for snow leopard populations within Mongolia and increasing research efforts in China.
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Johansson, O., Alexander, J. S., Lkhagvajav, P., Mishra, C., Samelius, G. (2024). Natal dispersal and exploratory forays through atypical habitat in the mountain-bound snow leopard. Ecology, 2024(e4264), 1–4.
Abstract: Understanding how landscapes affect animal movements is key to effective conservation and management (Rudnick et al., 2012; Zeller et al., 2012). Movement defines animal home ranges, where animals generally access resources such as food and mates, and also their dispersal and exploratory forays. These movements are important for individual survival and fitness through genetic exchange within and between populations and for colonization of unoccupied habitats (Baguette et al., 2013; MacArthur & Wilson, 1967). Dispersal and exploratory movements typically occur when young animals leave their natal range and establish more permanent home ranges (Greenwood, 1980; Howard, 1960). In mammals, natal dispersal of males is usually more frequent and happens over greater distances compared with that of females (Clobert et al., 2001; Greenwood, 1980).
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Johnsingh, A. J. T. (2006). A roadmap for conservation in Uttaranchal.
Abstract: The enchanting state of Uttaranchal, carved out of Uttar Pradesh on 9th November 2000, has a total area of ca. 53,485 km2 with a population density of 160 persons/ km2, much lower than the national average of 324/km2. This young state can take pride in the fact that 13.42% of its area is under protected areas. The state has varied landscapes: snow-capped and conifer forest covered mountains in the north, forest covered foothills with numerous perennial rivers and streams, locally known as the bhabar tract which includes the Himalayan foothills and the Shivalik range. As a result, the land is home to a variety of fascinating wildlife such as the golden mahseer (Tor putitora), king cobra (Ophiophagus hanna), Himalayan monal (Lophophorus impejanus), great hornbill (Buceros bicornis), Himalayan tahr (Hemitragus jemlahicus), bharal (Pseudois nayaur), Himalayan musk deer (Moschus chrysogaster), goral (Nemorhaedus goral), elephant (Elephas maximus), snow leopard (Panthera uncia), leopard (P. pardus), black bear (Ursus thibetanus), and tiger (P. tigris). All across their range, most of these species are endangered. The potential of this state, with about 800 kilometers of riverine habitat, can only be surpassed by Arunachal Pradesh in terms of golden mahseer conservation. The mountains, bedecked with the scarlet flowers of rhododendron (Rhododendron arboreum) in the summer months, can be a veritable home to many forms of pheasants, mountain ungulates and carnivores, provided poaching for trade is eliminated and hunting for the pot is brought under control. The bhabar forests of this state, ca. 7,500 km2, extending between Yamuna and Sharda rivers (Fig. 1.), can easily support a population of about 1000 elephants and 200 tigers as long as this large habitat, now fragmented in three blocks, is managed and protected as one continuous habitat for wildlife. Six villages, gujjar settlements and encroachments need to be moved away from the main wildlife habitat which goes along the bhabar tract. Although the conservation of these habitats can eventually bring in immense benefits through well-planned ecotourism programmes that are rapidly catching up in the state, initial conservation efforts would need a substantial amount of funds.
Keywords: carnivores, conservation, forest, habitat, hunting, landscape, Panthera uncia, poaching, snow leopard, species, tiger, Uncia uncia, ungulates, Uttar Pradesh, Uttaranchal
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Kachel, S., Bayrakcismith, R., Kubanychbekov, Z., Kulenbekov, R., McCarthy, T., Weckworth, B., Wirsing, A. (2022). Ungulate spatiotemporal responses to contrasting predation risk from wolves and snow leopards. Journal of Animal Ecology, , 1–16.
Abstract: 1. Spatial responses to risk from multiple predators can precipitate emergent consequences for prey (i.e. multiple-predator effects, MPEs) and mediate indirect interactions between predators. How prey navigate risk from multiple predators may therefore have important ramifications for understanding the propagation of predation-risk effects (PREs) through ecosystems.
2. The interaction of predator and prey traits has emerged as a potentially key driver of antipredator behaviour but remains underexplored in large vertebrate systems, particularly where sympatric prey share multiple predators. We sought to better generalize our understanding of how predators influence their ecosystems by considering how multiple sources of contingency drive prey distribution in a multi-predator–multi-prey system.
3. Specifically, we explored how two sympatric ungulates with different escape tactics—vertically agile, scrambling ibex Capra sibirica and sprinting argali Ovis ammon—responded to predation risk from shared predators with contrasting hunting modes—cursorial wolves Canis lupus and vertical-ambushing, stalking snow leopards Panthera uncia.
4. Contrasting risk posed by the two predators presented prey with clear trade-offs. Ibex selected for greater exposure to chronic long-term risk from snow leopards, and argali for wolves, in a nearly symmetrical manner that was predictable based on the compatibility of their respective traits. Yet, acute short-term risk from the same predator upended these long-term strategies, increasing each ungulates' exposure to risk from the alternate predator in a manner consistent with a scenario in which conflicting antipredator behaviours precipitate risk-enhancing MPEs and mediate predator facilitation. By contrast, reactive responses to wolves led ibex to reduce their exposure to risk from both predators—a risk-reducing MPE. Evidence of a similar reactive risk-reducing effect for argali vis-à-vis snow leopards was lacking.
5. Our results suggest that prey spatial responses and any resulting MPEs and prey-mediated interactions between predators are contingent on the interplay of hunting mode and escape tactics. Further investigation of interactions among various drivers of contingency in PREs will contribute to a more comprehensive understanding and improved forecasting of the ecological effects of predators.
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