Abstract: Abstract There is a need for simple and robust techniques for assessment and monitoring of populations of the Endangered snow leopard Panthera uncia to inform the de- velopment of action plans for snow leopard conservation. We explored the use of occupancy modelling to evaluate the influence of environmental and anthropogenic features on snow leopard site-use patterns. We conducted a camera trap survey across  km in Gansu Province, China, and used data from  camera traps to estimate probabilities of site use and detection using the single season occupancy model. We assessed the influence of three covariates on site use by snow leopards: elevation, the presence of blue sheep Pseudois nayaur and the presence of human disturb- ance (distance to roads). We recorded  captures of snow leopards over , trap-days, representing a mean capture success of . captures per  trap-days. Elevation had the strongest influence on site use, with the probability of site use increasing with altitude, whereas the influence of presence of prey and distance to roads was relatively weak. Our findings indicate the need for practical and robust tech- niques to appraise determinants of site use by snow leo- pards, especially in the context of the limited resources available for such work.

Abstract: Describes the range, behaviour and ecology of lion Panthera leo, tiger P. tigris, leopard P. pardus, snow leopard P. uncia, clouded leopard Neofelis nebylosa and cheetah Acinonyx jubatus. -P.J.Jarvis

Abstract: Illegal trade in big cat (Panthera spp.) body parts is a prominent topic in scientific and public discourses concerning wildlife conservation. While illegal trade is generally acknowledged as a threat to big cat species, we suggest that two enabling factors have, to date, been under-considered. To that end, we discuss the roles of human-felid conflict, and “local” use in illegal trade in big cat body parts. Drawing examples from across species and regions, we look at generalities, contextual subtleties, ambiguities, and definitional complexities. We caution against underestimating the extent of “local” use of big cats and highlight the potential of conflict killings to supply body parts.

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: It gives the description of genus Panthera: lion, tiger, leopard, jaguar and snow leopard. The mountains of Central Asia and South Siberia limit the habitat of snow leopard in the USSR. This species is also distributed in the Himalayas, Tibet, and mountains of Mongolia. In summer, it lives at 3,660 3,970 m above sea level, while in winter, following the ungulates; snow leopard descends to 1,800 m. In the Himalayas, it ascends up to 5,500 m above sea level in summer. In Djungar and Talas Ala-Tau, snow leopard keeps at 600 1,200 m. It takes refuge in caves and cracks of rocks. Snow leopard is mostly active in twilights and night, rarer in daylight, and preys on ungulates, hares, marmots, and others. The coupling period is winter or early spring. A gestation is about 90 days. It has 3 5 cubs in a litter.

Abstract: 1. Camera trapping, paired with analytical methods for estimating occupancy, abundance and other ecological parameters, can yield information with direct consequences for wildlife management and conservation. Although ecological information is the primary target of most camera trap studies, detectability influences every aspect from design to interpretation.
2. Concepts and methods of time-toevent analysis are directly applicable to camera trapping, yet this statistical field has thus far been ignored as a way to analyze photographic capture data. to illustrate the use to time-to-event statistics and to better understand how photographic evidence accumulates, we explored patterns in tow related measure of detectability: Detection probability and time to detection. We analyzed camera trap data for three sympatric carnivores ( snow Leopard, red fox and stone marten) in the mountains of northern Pakistan and tested predictions about patterns in detectability across species, sites and time.
3. We found species-specific differences in the magnitude of detectability and the factors influencing it, reinforcing the need to consider determinants of detectability in study design and to account for them during analysis. Photographic detectability of snow leopard was noticeably lower than that of red fox, but comparable to detectability of stone marten. Site-specific attributes such as the presence of carnivore sign ( snow Leopard), terrain ( snow leopard and red fox) and application for lures ( red fox) influenced detectability. For the most part, detection probability was constant over time.
4. Species- specific differences in factors determining detectability make camera trap studies targeting multiple species particularly vulnerable to misinterpretation if the hierarchical origin of the data is ignored. Investigators should consider not only the magnitude of detectability, but also the shape of the curve describing the cumulative process of photographic detection, as this has consequences for both determining survey effort and the election of analytical models. Weighted time-to -event analysis can complement occupancy analysis and other hierarchal methods by providing additional tools for exploring camera trap data and testing hypotheses regarding the temporal aspect of photographic evidence accumulation.

Abstract: The snow leopard Panthera uncia coexists with the wolf Canis lupus throughout most of its distribution range.
We analysed the food habits of snow leopards and wolves in their sympatric range in the Karakoram mountains of Pakistan. A total of 131 genotyped scats (N = 74, snow leopard; N = 57, Tibetan wolf) were collected during the cold periods (i.e. winter and spring) of 2011 and 2012 in the Hushey valley. Large mammals, i.e. livestock and ibex, accounted for 84.8 and 83.1% of the diet (relative frequency) of the snow leopard and the wolf, respectively. Domestic prey was the staple of the diet of both snow leopards (66.6%) and wolves (75.1%). Ibex Capra ibex, the only wild ungulate in our study area, contributed 18.2 and 16.9%of relative frequencies in the
diets of the snow leopard and the wolf, respectively. In winter, the snowleopard heavily relied on domestic sheep (43.3%) for food, whereas the wolf preyed mainly on domestic goats (43.4%). Differently from other study areas, both snow leopards and wolves showed no apparent prey preference (Jacobs
index: snow leopard min. − 0.098, max. 0.102; Tibetan wolf min. − 0.120, max. 0.03). In human depauperate areas, with livestock and only a few wild prey, should competitive interactions arise, two main scenarios could be expected, with either predator as a winner. In both cases, the best solution
could primarily impinge on habitat restoration, so that a balance could be found between these predators, who have already coexisted for thousands of years.

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.

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.