Abstract: Replicated multiple scale species distribution models (SDMs)
have become increasingly important to identify the correct variables
determining species distribution and their influences on ecological
responses. This study explores multi-scale habitat relationships of the
snow leopard (Panthera uncia) in two study areas on the Qinghai–Tibetan
Plateau of western China. Our primary objectives were to evaluate the
degree to which snow leopard habitat relationships, expressed by
predictors, scales of response, and magnitude of effects, were
consistent across study areas or locally landcape-specific. We coupled
univariate scale optimization and the maximum entropy algorithm to
produce multivariate SDMs, inferring the relative suitability for the
species by ensembling top performing models. We optimized the SDMs based
on average omission rate across the top models and ensembles’ overlap
with a simulated reference model. Comparison of SDMs in the two study
areas highlighted landscape-specific responses to limiting factors.
These were dependent on the effects of the hydrological network,
anthropogenic features, topographic complexity, and the heterogeneity of
the landcover patch mosaic. Overall, even accounting for specific local
differences, we found general landscape attributes associated with snow
leopard ecological requirements, consisting of a positive association
with uplands and ridges, aggregated low-contrast landscapes, and large
extents of grassy and herbaceous vegetation. As a means to evaluate the
performance of two bias correction methods, we explored their effects on
three datasets showing a range of bias intensities. The performance of
corrections depends on the bias intensity; however, density kernels
offered a reliable correction strategy under all circumstances. This
study reveals the multi-scale response of snow leopards to environmental
attributes and confirms the role of meta-replicated study designs for
the identification of spatially varying limiting factors. Furthermore,
this study makes important contributions to the ongoing discussion about
the best approaches for sampling bias correction.

Abstract: In this study, we investigated the impact of domestic and wild prey availability on snow leopard prey preference in the Kangchenjunga Conservation Area of eastern Nepal-a region where small domestic livestock are absent and small wild ungulate prey are present. We took a comprehensive approach that combined fecal genetic sampling, macro- and microscopic analyses of snow leopard diets, and direct observation of blue sheep and livestock in the KCA. Out of the collected 88 putative snow leopard scat samples from 140 transects (290km) in 27 (4x4km2) sampling grid cells, 73 (83%) were confirmed to be from snow leopard. The genetic analysis accounted for 19 individual snow leopards (10 males and 9 females), with a mean population size estimate of 24 (95% CI: 19-29) and an average density of 3.9 snow leopards/100km2 within 609km2. The total available prey biomass of blue sheep and yak was estimated at 355,236 kg (505 kg yak/km2 and 78kg blue sheep/km2). From the available prey biomass, we estimated snow leopards consumed 7% annually, which comprised wild prey (49%), domestic livestock (45%). and 6% unidentified items. the estimated 47,736 kg blue sheep biomass gives a snow leopard-to-blue sheep ratio of 1:59 on a weight basis. The high preference of snow leopard to domestic livestock appears to be influenced by a much smaller available biomass of wild prey then in other regions of Nepal (e.g., 78kg/km2 in the KCA compared with a range of 200-300 kg/km2 in other regions of Nepal?. Along with livestock insurance scheme improvement, there needs to be a focus on improved livestock guarding, predator-proof corrals as well as engaging and educating local people to be citizen scientists on the importance of snow leopard conservation, involving them in long-term monitoring programs and promotion of ecotourism.

Abstract: The Katun River originates in the steppe of the Altai Mountains in Siberia. One of the major headwaters of the Ob River, the Katun is considered central to the culture of the indigenous Altaians. The Katun Valley contains large numbers of important cultural sites, dating from the Neolithic and representing some of the earliest human settlement in Russia. Modern-day Altaians still observe traditional ceremonies honoring the river and springs throughout the watershed and utilize traditional ecological knowledge in their management of the land and water resources. Russian and international scientists have identified the Altai Mountains as a region of high plant diversity and endemism, and as important habitat for endangered species such as the snow leopard. The Katun River itself contains species of threatened and endangered fishes, and its headwaters are part of the unusual Mongolian ichthyofaunal province that is characterized by high levels of endemism. The same regions are considered by the Altaian people to be special or sacred and are recognized by Western scientists as having great value for conservation. During the era of perestroika, a hydroelectric dam was to be built on the Katun. The large dam, a vestige of the earlier Soviet plan for the Project of the Century, would have devastated significant agricultural, ecological, recreational, and cultural resources. The indigenous Altaian people would have lost much of their sacred and cultural landscape. The Katun dam project united indigenous people, well-known Siberian writers, and scientists in protest, which became so heated that it engaged the international community, with lasting effects on Russian society. The magnitude of the protest illustrates the importance of the Altai Mountain region to all of Russia. The active participation of indigenous Altaians reflected their traditional willingness to take action against political decisions that negatively impacted the environmental, cultural, and religious values of their homeland. Their involvement also reflected the new wave of awareness under perestroika that underscored a greater respect and autonomy for indigenous peoples in Russia.

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.

Abstract: Abstract: Assesses foreign investment laws adopted by the government of Mongolia which have been deemed extremely flexible and favorable for Americans. Economic benefits presented by the big game hunt industry; Consultation with Secretary of State James Baker in the formulation of said laws during his July The Mongolian government is trying its best to make the country attractive to foreign investors. Big game hunts are still Mongolia's primary source of foreign cash. European and American hunters are willing to pay as much as $90,000 for rare game such as the ibex or the snow leopard. However, a recent US Fish and Wildlife Service ruling giving protection to the Argal, a wild sheep, could mean the cutting of cash inflows from foreign hunters.