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Karnaukhov А. S., K. М. P., Kuksin А. N., Malykh S. V., Poyarkov А. D., Spitsyn S. V., Chistopolova М. D., Hernandez-Blanco J. A. (2020). Snow Leopard Population Monitoring Guidebook (English).
Abstract: The “Snow Leopard Population Monitoring Guidebook” is the result of a multiyear effort to study and monitor the status of key snow leopard populations in the Russian Federation conducted by WWF Russia specialists alongside colleagues in protected areas and the Severtsov Institute for Ecology and Evolution (Russian Academy of Sciences). The book provides the most recent data regarding the distribution and population of the snow leopard in three administrative subjects of the Russian Federation – Republics of Altai, Tyva, and Buryatiya. Optimal survey routes and a grid network for camera-trapping stations are discussed and are based on a previously-developed program for standardized monitoring and surveying of the snow leopard population. The most important part of this publication is the analysis of methodologies for evaluating the status of population groups of this rare cat – from the traditional route census approach to innovative systems for automated collection of field data. In addition, the results of multi-year work analyze snow leopard nutrition and evaluate the genetic diversity of the snow leopard population in Russia.
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Karnaukhov А. S., K. М. P., Kuksin А. N., Malykh S. V., Poyarkov А. D., Spitsyn S. V., Chistopolova М. D., Hernandez-Blanco J. A. (2020). Snow Leopard Population Monitoring Guidebook (Russian).
Abstract: The “Snow Leopard Population Monitoring Guidebook” is the result of a multiyear effort to study and monitor the status of key snow leopard populations in the Russian Federation conducted by WWF Russia specialists alongside colleagues in protected areas and the Severtsov Institute for Ecology and Evolution (Russian Academy of Sciences). The book provides the most recent data regarding the distribution and population of the snow leopard in three administrative subjects of the Russian Federation – Republics of Altai, Tyva, and Buryatiya. Optimal survey routes and a grid network for camera-trapping stations are discussed and are based on a previously-developed program for standardized monitoring and surveying of the snow leopard population. The most important part of this publication is the analysis of methodologies for evaluating the status of population groups of this rare cat – from the traditional route census approach to innovative systems for automated collection of field data. In addition, the results of multi-year work analyze snow leopard nutrition and evaluate the genetic diversity of the snow leopard population in Russia.
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Singh, R., Krausman, P. R., Pandey, P., Maheshwari, A., Rawal,
R. S., Sharma, S., Shekhar, S. (2020). Predicting Habitat Suitability of Snow Leopards in the Western
Himalayan Mountains, India. Biology bulletin, 47(6), 655–664.
Abstract: The population of snow leopard (Panthera uncia) is declining
across their range, due to poaching, habitat fragmentation, retaliatory
killing, and a decrease of wild prey species. Obtaining information on
rare and cryptic predators living in remote and rugged terrain is
important for making conservation and management strategies. We used the
Maximum Entropy (MaxEnt) ecological niche modeling framework to predict
the potential habitat of snow leopards across the western Himalayan
region, India. The model was developed using 34 spatial species
occurrence points in the western Himalaya, and 26 parameters including,
prey species distribution, temperature, precipitation, land use and land
cover (LULC), slope, aspect, terrain ruggedness and altitude. Thirteen
variables contributed 98.6% towards predicting the distribution of snow
leopards. The area under the curve (AUC) score was high (0.994) for the
training data from our model, which indicates pre- dictive ability of
the model. The model predicted that there was 42432 km2 of potential
habitat for snow leop- ards in the western Himalaya region. Protected
status was available for 11247 km2 (26.5%), but the other 31185 km2
(73.5%) of potential habitat did not have any protected status. Thus,
our approach is useful for predicting the distribution and suitable
habitats and can focus field surveys in selected areas to save
resources, increase survey success, and improve conservation efforts for
snow leopards.
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Rashid, W., Shi, J., Rahim, I. U., Dong, S., Ahmad, L. (2020). Research trends and management options in human-snow leopard conflict. Biological Conservation, 242(108413), 1–10.
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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Filla, M., Lama, R. P., Ghale, T. R., Signer, J., Filla, T., Aryal, R. R., Heurich, M., Waltert, M., Balkenhol, N., Khorozyan, I. (2020). In the shadows of snow leopards and the Himalayas: density and habitat selection of blue sheep in Manang, Nepal. Ecology and Evolution, 2021(11), 108–122.
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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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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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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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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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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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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