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Author Sharma, R. K., Sharma, K., Borchers, D., Bhatnagar, Y. V., Suryawanshi, K. S., Mishra, C. url 
  Title Spatial variation in population-density, movement and detectability of snow leopards in 2 a multiple use landscape in Spiti Valley, Trans-Himalaya Type Journal Article
  Year (down) 2020 Publication bioRxiv Abbreviated Journal  
  Volume Issue Pages  
  Keywords Co-existence; land sharing; population-density; spatial capture recapture; Pseudois nayaur Capra sibirica; ungulates; livestock.  
  Abstract The endangered snow leopard Panthera uncia occurs in human use landscapes in the mountains of South and Central Asia. Conservationists generally agree that snow leopards must be conserved through a land-sharing approach, rather than land-sparing in the form of strictly protected areas. Effective conservation through land-sharing requires a good understanding of how snow leopards respond to human use of the landscape. Snow leopard density is expected to show spatial variation within a landscape because of variation in the intensity of human use and the quality of habitat. However, snow leopards have been difficult to enumerate and monitor. Variation in the density of snow leopards remains undocumented, and the impact of human use on their populations is poorly understood. We examined spatial variation in snow leopard density in Spiti Valley, an important snow leopard landscape in India, via spatially explicit capture recapture analysis of camera trap data. We camera trapped an area encompassing a minimum convex polygon of 953 km . We estimated an overall density of 0.49 (95% CI: 0.39-0.73) adult snow leopards per 100 km . Using AIC, our best model showed the density of snow leopards to depend on wild prey density, movement about activity centres to depend on altitude, and the expected number of encounters at the activity centre to depend on topography. Models that also used livestock biomass as a density covariate ranked second, but the effect of livestock was weak. Our results highlight the importance of maintaining high density pockets of wild prey populations in multiple use landscapes to enhance snow leopard conservation.  
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  Call Number Serial 1620  
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Author Zhang, L., Lian, X., Yang, X url 
  Title Population density of snow leopards (Panthera Uncia) in the Yage Valley Region of the Sanjiangyuan National Park: Conservation Implications and future directions Type Journal Article
  Year (down) 2020 Publication Artic, Antartic and Alpine Research Abbreviated Journal  
  Volume 52 Issue 1 Pages 541-550  
  Keywords Snow leopard; population density; camera trapping; Tibetan Plateau; alpine ecosystem  
  Abstract Population-based studies on snow leopard (Panthera uncia) are of theoretical and practical sig- nificance for the conservation of alpine ecosystems, though geographic remoteness and isolation hinder surveys in many promising regions. The Sanjiangyuan National Park on the Tibetan Plateau is acknowledged as a main snow leopard habitat, but most of the region remains unexplored and unknown. We adopted a combined approach of route survey and camera trapping survey to explore the population density of snow leopard in the Yage Valley region of the Sanjiangyuan National Park. Results indicated that (1) large populations of blue sheep contributed to the major food supply for snow leopards, along with diverse prey species as dietary supplementations, and (2) a population density of four to six snow leopards per 100 km2 on the north bank was estimated, and nine to fourteen individuals within the valley core areas were identified. We also argue that under the potential impacts of hydropower dams, this valley ecosystem should be symbolized as a conservation hotspot and therefore merits prioritized conservation. We recommend further surveys combined with novel methods/techniques and advocate a sustainable ecotourism model for the first V-shaped valley along the Yangtze mainstream.  
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  Call Number Serial 1619  
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Author Durbach, I., Borchers, D., Sutherland, C., Sharma, K. url 
  Title Fast, flexible alternatives to regular grid designs for spatial capture–recapture. Type Research Article
  Year (down) 2020 Publication Methods in Ecology and Evolution Abbreviated Journal  
  Volume Issue Pages 1-13  
  Keywords camera trap, population ecology,sampling, spatial capture-recapture, surveys  
  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.
 
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  Notes Approved no  
  Call Number Serial 1618  
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Author Hameed, S., Din, J. U., Ali, H., Kabir, M., Younas, M., Rehman, E. U., Bari, F., Hao, W., Bischof, R., Nawaz, M. A. url 
  Title Identifying priority landscapes for conservation of snow leopards in Pakistan Type Journal Article
  Year (down) 2020 Publication Plos One Abbreviated Journal  
  Volume Issue Pages 1-20  
  Keywords  
  Abstract Pakistan’s total estimated snow leopard habitat is about

80,000 km2 of which about half is considered prime habitat. However,

this preliminary demarcation was not always in close agreement with the

actual distribution the discrepancy may be huge at the local and

regional level. Recent technological developments like camera trapping

and molecular genetics allow for collecting reliable presence records

that could be used to construct realistic species distribution based on

empirical data and advanced mathematical approaches like MaxEnt. The

current study followed this approach to construct an accurate

distribution of the species in Pakistan. Moreover, movement corridors,

among different landscapes, were also identified through circuit theory.

The probability of habitat suitability, generated from 98 presence

points and 11 environmental variables, scored the snow leopard’s assumed

range in Pakistan, from 0 to 0.97. A large portion of the known range

represented low-quality habitat, including areas in lower Chitral, Swat,

Astore, and Kashmir. Conversely, Khunjerab, Misgar, Chapursan, Qurumber,

Broghil, and Central Karakoram represented high-quality habitats.

Variables with higher contributions in the MaxEnt model were

precipitation during the driest month (34%), annual mean temperature

(19.5%), mean diurnal range of temperature (9.8%), annual precipitation

(9.4%), and river density (9.2). The model was validated through

receiver operating characteristic (ROC) plots and defined thresholds.

The average test AUC in Maxent for the replicate runs was 0.933 while

the value of AUC by ROC curve calculated at 0.15 threshold was 1.00.

These validation tests suggested a good model fit and strong predictive

power. The connectivity analysis revealed that the population in the

Hindukush landscape appears to be more connected with the population in

Afghani- stan as compared to other populations in Pakistan. Similarly,

the Pamir-Karakoram population is better connected with China and

Tajikistan, while the Himalayan population was connected with the

population in India. Based on our findings we propose three model

landscapes to be considered under the Global Snow Leopard Ecosystem

Protection Program (GSLEP) agenda as regional priority areas, to

safeguard the future of the snow leopard in Pakistan and the region.

These landscapes fall within mountain ranges of the Himalaya, Hindu Kush

and Karakoram-Pamir, respectively. We also identified gaps in the

existing protected areas network and suggest new protected areas in

Chitral and Gilgit-Baltistan to protect critical habitats of snow

leopard in Pakistan.
 
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  Notes Approved no  
  Call Number Serial 1617  
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Author Atzeni, L., Cushman, S. A., Bai, D., Wang, J., Chen, P., Shi, K., Riordan, P. url 
  Title Meta-replication, sampling bias, and multi-scale model selection: A case study on snow leopard (Panthera uncia) in western China. Type Journal Article
  Year (down) 2020 Publication Ecology and Evolution Abbreviated Journal  
  Volume Issue Pages 1-27  
  Keywords MaxEnt, meta-replication, multi-scale, Panthera uncia, sampling bias, scale selection, snow leopard, species distribution model  
  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.
 
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  Notes Approved no  
  Call Number Serial 1616  
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Author Chetri, M., Odden, M., Devineau, O., McCarthy, T., Wegge, P. url 
  Title Multiple factors influence local perceptions of snow leopards and Himalayan wolves in the central Himalayas, Nepal. Type Journal Article
  Year (down) 2020 Publication PeerJ Abbreviated Journal  
  Volume Issue Pages 1-18  
  Keywords Panthera uncia, Canis lupus chanco, Perceptions, Large carnivores, Trans-Himalayas  
  Abstract An understanding of local perceptions of carnivores is

important for conservation and management planning. In the central

Himalayas, Nepal, we interviewed 428 individuals from 85 settlements

using a semi-structured questionnaire to quantitatively assess local

perceptions and tolerance of snow leopards and wolves. We used

generalized linear mixed effect models to assess influential factors,

and found that tolerance of snow leopards was much higher than of

wolves. Interestingly, having experienced livestock losses had a minor

impact on perceptions of the carnivores. Occupation of the respondents

had a strong effect on perceptions of snow leopards but not of wolves.

Literacy and age had weak impacts on snow leopard perceptions, but the

interaction among these terms showed a marked effect, that is, being

illiterate had a more marked negative impact among older respondents.

Among the various factors affecting perceptions of wolves, numbers of

livestock owned and gender were the most important predictors. People

with larger livestock herds were more negative towards wolves. In terms

of gender, males were more positive to wolves than females, but no such

pattern was observed for snow leopards. People’s negative perceptions

towards wolves were also related to the remoteness of the villages.

Factors affecting people’s perceptions could not be generalized for the

two species, and thus need to be addressed separately. We suggest future

conservation projects and programs should prioritize remote settlements.
 
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  Notes Approved no  
  Call Number Serial 1615  
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Author Filla, M., Lama, R. P., Ghale, T. R., Signer, J., Filla, T., Aryal, R. R., Heurich, M., Waltert, M., Balkenhol, N., Khorozyan, I. pdf 
  Title In the shadows of snow leopards and the Himalayas: density and habitat selection of blue sheep in Manang, Nepal Type Journal Article
  Year (down) 2020 Publication Ecology and Evolution Abbreviated Journal  
  Volume 2021 Issue 11 Pages 108-122  
  Keywords Annapurna Conservation Area, bharal, Panthera uncia, predator-prey, Pseudois nayaur  
  Abstract There is a growing agreement that conservation needs to be proactive and pay increased attention to common species and to the threats they face. The blue sheep (Pseudois nayaur) plays a key ecological role in sensitive high-altitude ecosystems of Central Asia and is among the main prey species for the globally vulnerable snow leopard (Panthera uncia). As the blue sheep has been increasingly exposed to human pressures, it is vital to estimate its population dynamics, protect the key populations, identify important habitats, and secure a balance between conservation and local livelihoods. We conducted a study in Manang, Annapurna Conservation Area (Nepal), to survey blue sheep on 60 transects in spring (127.9 km) and 61 transects in autumn (134.7 km) of 2019, estimate their minimum densities from total counts, compare these densities with previous estimates, and assess blue sheep habitat selection by the application of generalized additive models (GAMs). Total counts yielded minimum density estimates of 6.0–7.7 and 6.9–7.8 individuals/km2 in spring and autumn, respectively, which are relatively high compared to other areas. Elevation and, to a lesser extent, land cover indicated by the normalized difference vegetation index (NDVI) strongly affected habitat selection by blue sheep, whereas the effects of anthropogenic variables were insignificant. Animals were found mainly in habitats associated with grasslands and shrublands at elevations between 4,200 and 4,700 m. We show that the blue sheep population size in Manang has been largely maintained over the past three decades, indicating the success of the integrated conservation and development efforts in this area. Considering a strong dependence of snow leopards on blue sheep, these findings give hope for the long-term conservation of this big cat in Manang. We suggest that long-term population monitoring and a better understanding of blue sheep–livestock interactions are crucial to maintain healthy populations of blue sheep and, as a consequence, of snow leopards.  
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  Call Number SLN @ rakhee @ Serial 1683  
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Author Rashid, W., Shi, J., Rahim, I. U., Dong, S., Ahmad, L. pdf 
  Title Research trends and management options in human-snow leopard conflict Type Journal Article
  Year (down) 2020 Publication Biological Conservation Abbreviated Journal  
  Volume 242 Issue 108413 Pages 1-10  
  Keywords Snow leopards, Systematic review, Compensation, Co-existence, Livestock, Human-wildlife conflict, Mitigation  
  Abstract Conservation of the snow leopard (Panthera uncia) is challenging because of its threatened status and increase in human-snow leopard conflict (HSC). The area of occupancy of the snow leopard comprises mountainous regions of Asia that are confronted with various environmental pressures including climate change. HSCs have increased with a burgeoning human population and economic activities that enhance competition between human and snow leopard or its preys. Here we systematically review the peer-reviewed literature from 1994 to 2018 in Web of Science, Google Scholar, Science Direct and PubMed (30 articles), to evaluate the current state of scholarship about HSCs and their management. We determine: 1) the spatio-temporal distribution of relevant researches; 2) the methodologies to assess HSCs; 3) and evaluate existing interventions for conflict management; and 4) the potential options for HSC management. The aim of the current study is thus to identify key research gaps and future research requirements. Of the articles in this review, 60% evaluated the mitigation of HSCs, while only 37% provided actionable and decisive results. Compensation programs and livestock management strategies had high success rates for mitigating HSCs through direct or community-managed interventions. Further research is required to evaluate the efficacy of existing HSC mitigation strategies, many of which, while recommended, lack proper support. In spite of the progress made in HSC studies, research is needed to examine ecological and sociocultural context of HSCs. We suggest future work focus on rangeland management for HSC mitigation, thus ultimately fostering a co-existence between human and snow leopard.  
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  Call Number SLN @ rakhee @ Serial 1716  
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Author Suryawanshi, K. R., Khanyari, M., Sharma, K., Lkhagvajav, P., Mishra, C. url 
  Title Sampling bias in snow leopard population estimation studies Type Journal Article
  Year (down) 2019 Publication Population Eccology Abbreviated Journal  
  Volume Issue Pages 1-9  
  Keywords camera trap, Central Asia, Himalaya, meta-analysis, monitoring, Panthera uncia, population ecology  
  Abstract Accurate assessments of the status of threatened species and their conservation

planning require reliable estimation of their global populations and robust monitoring

of local population trends. We assessed the adequacy and suitability of studies

in reliably estimating the global snow leopard (Panthera uncia) population. We

compiled a dataset of all the peer-reviewed published literature on snow leopard

population estimation. Metadata analysis showed estimates of snow leopard density

to be a negative exponential function of area, suggesting that study areas have generally

been too small for accurate density estimation, and sampling has often been

biased towards the best habitats. Published studies are restricted to six of the

12 range countries, covering only 0.3&#65533;0.9% of the presumed global range of the

species. Re-sampling of camera trap data from a relatively large study site

(c.1684 km2) showed that small-sized study areas together with a bias towards

good quality habitats in existing studies may have overestimated densities by up to

five times. We conclude that current information is biased and inadequate for generating

a reliable global population estimate of snow leopards. To develop a rigorous

and useful baseline and to avoid pitfalls, there is an urgent need for

(a) refinement of sampling and analytical protocols for population estimation of

snow leopards (b) agreement and coordinated use of standardized sampling protocols

amongst researchers and governments across the range, and (c) sampling

larger and under-represented areas of the snow leopard's global range.
 
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  Call Number SLN @ rakhee @ Serial 1477  
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Author Chetri, M, Odden, M., Sharma, K., Flagstad, O., Wegge, P url 
  Title Estimating snow leopard density using fecal DNA in a large landscape in north-central Nepal Type Journal Article
  Year (down) 2019 Publication Global Ecology and Conservation Abbreviated Journal  
  Volume Issue 17 Pages 1-8  
  Keywords Panthera uncia, Density, Annapurna-Manaslu landscape, Noninvasive, Spatial scale  
  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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  Notes Approved no  
  Call Number SLN @ rakhee @ Serial 1478  
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