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Rashid, W., Shi, J., Rahim, I. U., Dong, S., Sultan, H. (2020). Issues and Opportunities Associated with Trophy Hunting and Tourism in Khunjerab National Park, Northern Pakistan. Animals, 10(597), 1–20.
Abstract: Trophy hunting and mass tourism are the two major interventions designed to provide various socioeconomic and ecological benefits at the local and regional levels. However, these interventions have raised some serious concerns that need to be addressed. This study was conducted in Khunjerab National Park (KNP) with an aim to analyze comparatively the socioeconomic and ecological impacts of trophy hunting and mass tourism over the last three decades within the context of sustainability. Focus Group Discussions (FGDs) with key stakeholders and household interviews were conducted to collect data on trophy hunting and mass tourism, and on local attitudes towards these two interventions in and around KNP. The results revealed that 170 Ibex (Capra sibirica) and 12 Blue sheep (Pseudois nayaur) were hunted in the study area over the past three decades, and trophy hunting was not based on a sustainable harvest level. Trophy hunting on average generated USD 16,272 annual revenue, which was invested in community development. However, trophy hunting has greatly changed the attitudes of local residents towards wildlife: a positive attitude towards the wild ungulates and strongly negative attitude towards wild carnivores. In addition, trophy hunting has reduced the availability of ungulate prey species for Snow leopards (Panthera uncia), and consequently, Snow leopards have increased their predation on domestic livestock. This has, in turn, increased human–snow leopard conflict, as negative attitudes towards carnivores result in retaliatory killing of Snow leopards. Furthermore, according to ocial record data, the number of tourists to KNP has increased tremendously by 10,437.8%, from 1382 in 1999 to 145,633 in 2018. Mass tourism on average generated USD 33,904 annually and provided opportunities for locals to earn high incomes, but it caused damages to the environment and ecosystem in KNP through pollution generation and negative impacts on wildlife. Considering the limited benefits and significant problems created by trophy hunting and mass tourism, we suggest trophy hunting should be stopped and mass tourism should be shifted to ecotourism in and around KNP. Ecotourism could mitigate human–Snow leopard conflicts and help conserve the fragile ecosystem, while generating enough revenue incentives for the community to protect biodiversity and compensate for livestock depredation losses to Snow leopards. Our results may have implications for management of trophy hunting and mass tourism in other similar regions that deserve further investigation.
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Sharma, R. K., Sharma, K., Borchers, D., Bhatnagar, Y. V., Suryawanshi, K. S., Mishra, C. (2020). Spatial variation in population-density, movement and detectability of snow leopards in
2 a multiple use landscape in Spiti Valley, Trans-Himalaya. bioRxiv, .
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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Zhang, L., Lian, X., Yang, X. (2020). Population density of snow leopards (Panthera Uncia) in the Yage Valley Region of the Sanjiangyuan National Park: Conservation Implications and future directions. Artic, Antartic and Alpine Research, 52(1), 541–550.
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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Durbach, I., Borchers, D., Sutherland, C., Sharma, K. (2020). Fast, flexible alternatives to regular grid designs for spatial
capture–recapture..
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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Hameed, S., Din, J. U., Ali, H., Kabir, M., Younas, M., Rehman,
E. U., Bari, F., Hao, W., Bischof, R., Nawaz, M. A. (2020). Identifying priority landscapes for conservation of snow
leopards in Pakistan. Plos One, , 1–20.
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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Atzeni, L., Cushman, S. A., Bai, D., Wang, J., Chen, P., Shi,
K., Riordan, P. (2020). Meta-replication, sampling bias, and multi-scale model selection:
A case study on snow leopard (Panthera uncia) in western China. Ecology and Evolution, , 1–27.
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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Chetri, M., Odden, M., Devineau, O., McCarthy, T., Wegge, P. (2020). Multiple factors influence local perceptions of snow leopards and
Himalayan wolves in the central Himalayas, Nepal. PeerJ, , 1–18.
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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Sharma, R. K., Sharma, K., Borchers, D., Bhatnagar, Y V., Suryawanshi, K. R., Mishra, C. (2021). Spatial variation in population-density of snow leopards in a multiple use landscape in Spiti Valley, Trans-Himalaya.
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 km2. Our best model estimated an overall density of 0.5 (95% CI: 0.31–0.82) mature snow leopards per 100 km2. Using AIC, our best model showed the density of snow leopards to depend on estimated 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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Lewis, M., Songster, E.E. (2016). Studying the snow leopard: reconceptualizing conservation across the China–India border. BJHS, Themes 1(1), 169–198.
Abstract: The snow leopard is a highly charismatic megafauna that elicits admiration, concern and donations from individuals and NGOs in the West. In its home territories, however, it is a threat to local communities’ livestock and a potential source of income for its pelt and parts. Conservation and study are further challenged by its range; snow leopards traverse the borders separating China, India and ten other countries with long histories of tension with each other as well as internal political and economic struggles. This transnational animal provides an ideal case study for the consideration of transnational conservation science in the recent past.
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Weckworth, B. (2021). Snow Leopard (Panthera uncia) Genetics: The Knowledge Gaps, Needs, and Implications for Conservation. Journal of the Indian Institute of Science, , 1–12.
Abstract: Conservation geneticists apply genetic theory and techniques to preserve endangered species as dynamic entities, capable of coping with environmental change and thus minimizing their risk of extinction. Snow leopards are an umbrella species of High Asia, and a keystone for maintaining biodiversity within this fragile ecosystem. A clear understanding of patterns of snow leopard genetic diversity is critical for guiding conservation initiatives that will ensure their long-term persistence. Yet, a comprehensive analysis of snow leopard genetic variation is lacking. The number of published snow leopard genetic studies is far fewer than for other imperiled big cats. Here, I review the limited genetic work to date on snow leopards and the significant knowledge gaps to be filled. An emphasis must be placed on describing and understanding population genetic dynamics within and among meta-populations to provide information about the interactions between landscapes and the micro-evolutionary processes of gene flow and genetic drift. These results can be used to evaluate the levels and dynamics of genetic and demographic connectivity. A lack of connectivity, particularly in the low density, small populations that typify snow leopards, can lead to multiple demographic and genetic consequences, including inbreeding depression, loss of adaptive potential, and heightened susceptibility to demographic and environmental stochasticity. New efforts in conservation research on snow leopards should focus on this line of inquiry, and the opportunities and challenges for that are outlined and discussed to encourage the required, and considerable, transboundary partnerships and collaborations needed to be successful.
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