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Johansson, O., Ullman, K., Lkhagvajav, P., Wiseman, M.,
Malmsten, J., Leijon, M. (2020). Detection and Genetic Characterization of Viruses Present in
Free-Ranging Snow Leopards Using Next-Generation Sequencing. Frontiers in Veterinary Science, 7(645), 1–9.
Abstract: Snow leopards inhabit the cold, arid environments of the high
mountains of South and Central Asia. These living conditions likely
affect the abundance and composition of microbes with the capacity to
infect these animals. It is important to investigate the microbes that
snow leopards are exposed to detect infectious disease threats and
define a baseline for future changes that may impact the health of this
endangered felid. In this work, next-generation sequencing is used to
investigate the fecal (and in a few cases serum) virome of seven snow
leopards from the Tost Mountains of Mongolia. The viral species to which
the greatest number of sequences reads showed high similarity was
rotavirus. Excluding one animal with overall very few sequence reads,
four of six animals (67%) displayed evidence of rotavirus infection. A
serum sample of a male and a rectal swab of a female snow leopard
produced sequence reads identical or closely similar to felid
herpesvirus 1, providing the first evidence that this virus infects snow
leopards. In addition, the rectal swab from the same female also
displayed sequence reads most similar to feline papillomavirus 2, which
is the first evidence for this virus infecting snow leopards. The rectal
swabs from all animals also showed evidence for the presence of small
circular DNA viruses, predominantly Circular Rep-Encoding
Single-Stranded (CRESS) DNA viruses and in one case feline anellovirus.
Several of the viruses implicated in the present study could affect the
health of snow leopards. In animals which are under environmental
stress, for example, young dispersing individuals and lactating females,
health issues may be exacerbated by latent virus infections.
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Sharma, K., Fiechter, M., George, T., Young, J., Alexander, J.
S., Bijoor, Suryawanshi, K., Mishra, C. (2020). Conservation and people: Towards an ethical code of conduct for
the use of camera traps in wildlife research. Ecological Solutions and Evidence, , 1–6.
Abstract: 1. Camera trapping is a widely employed tool in wildlife
research, used to estimate animal abundances, understand animal
movement, assess species richness and under- stand animal behaviour. In
addition to images of wild animals, research cameras often record human
images, inadvertently capturing behaviours ranging from innocuous
actions to potentially serious crimes.
2. With the increasing use of camera traps, there is an urgent need to
reflect on how researchers should deal with human images caught on
cameras. On the one hand, it is important to respect the privacy of
individuals caught on cameras, while, on the other hand, there is a
larger public duty to report illegal activity. This creates ethical
dilemmas for researchers.
3. Here, based on our camera-trap research on snow leopards Panthera
uncia, we outline a general code of conduct to help improve the practice
of camera trap based research and help researchers better navigate the
ethical-legal tightrope of this important research tool.
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Poyarkov, A. D., Munkhtsog, B., Korablev, M. P., Kuksin, A. N., Alexandrov, D. Y., Chistopolova, M. D., Hernandez-Blanco, J. A., Munkhtogtokh, O., Karnaukhov, A. S., Lkhamsuren, N., Bayaraa, M., Jackson, R. M., Maheshwari, A., Rozhnov, V. V. (2020). Assurance of the existence of a trans-boundary population of the snow leopard (Panthera uncia) at Tsagaanshuvuut – Tsagan- Shibetu SPA at the Mongolia-Russia border. Integrative Zoology, (15), 224–231.
Abstract: The existence of a trans-boundary population of the snow leopard (Panthera uncia) that inhabits the massifs of Tsagaanshuvuut (Mongolia) – Tsagan-Shibetu (Russia) was determined through non-invasive genetic analysis of scat samples and by studying the structure of territory use by a collared female individual. The genetic analysis included species identification of samples through sequencing of a fragment of the cytochrome b gene and individual identification using a panel of 8 microsatellites. The home range of a female snow leopard marked with a satellite Global Positioning System (GPS) collar was represented by the minimum convex polygon method (MCP) 100, the MCP 95 method and the fixed kernel 95 method. The results revealed insignificant genetic differentiation between snow leopards that inhabit both massifs (minimal fixation index [FST]), and the data testify to the unity of the cross-border group. Moreover, 5 common individuals were identified from Mongolian and Russian territories. This finding clearly shows that their home range includes territories of both countries. In addition, regular movement of a collared snow leopard in Mongolia and Russia confirmed the existence of a cross-border snow leopard group. These data support that trans-boundary conservation is important for snow leopards in both countries. We conclude that it is crucial for Russia to study the northern range of snow leopards in Asia.
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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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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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Farrington, J., Tsering, D. (2020). Snow leopard distribution in the Chang Tang region of Tibet, China. Global Ecology and Conservation, 23.
Abstract: In 2006 and 2007, the authors conducted human-wildlife conflict surveys in the Tibet Autonomous Region’s (TAR) Shainza, Nyima, and Tsonyi Counties, located in the TAR’s remote Chang Tang region. At this time, prior knowledge of the snow leopard in this vast 700,000 km2 region was limited to just eight firsthand snow leopard sign and conflict location records and 15 secondhand records. These surveys revealed a previously undocumented and growing problem of human-snow leopard conflict. The 2007 survey also yielded 39 new snow leopard conflict incident locations and 24 new snow leopard sign locations. Next, snow leopard telephone interviews and mapping exercises were conducted with Tibet Forestry Bureau staff that yielded an additional 63 and 144 new snow leopard conflict and sighting location records, respectively. These 270 new snow leopard location records, together with 39 records collected by other observers from 1988 to 2009, were compiled into a snow leopard distribution map for the Chang Tang. This effort greatly expanded knowledge of the snow leopard’s distribution in this region which remains one of the least understood of the snow leopard’s key range areas. New knowledge gained on snow leopard distribution in the Chang Tang through this exercise will help identify human-snow leopard conflict hot spots and inform design of human-snow leopard conflict mitigation and conservation strategies for northwest Tibet. Nevertheless, extensive additional field verification work will be required to definitively delineate snow leopard distribution in the Chang Tang. Importantly, since 2006, a number of major transportation infrastructure projects have made the Chang Tang more accessible, including paving of highways, new railroads, and new airports. This has led to a greatly increased number of tourists visiting western Tibet, particularly Mt. Kailash and Lake Manasarovar. At the same time, large areas of the Chang Tang have been fenced for livestock pastures as part of government initiatives to allocate pasturelands to individual families. All three of these developments have a large potential to cause disturbance to snow leopards and their prey species, including by hindering their movements and degrading their habitat. Therefore, future conservation measures in the Chang Tang will need to insure that development activities and the growing number of visitors to the Chang Tang do not adversely affect the distribution of snow leopards and their prey species or directly degrade their habitat.
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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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Koju. N. P,, Bashyal, B., Pandey, B. P., Shah, S. N., Thami, S., Bleisch, W. V. (2020). First camera-trap record of the snow leopard Panthera uncia in Gaurishankar Conservation Area, Nepal. Oryx, , 1–4.
Abstract: The snow leopard Panthera uncia is the flagship species of the high mountains of the Himalayas. There is po- tentially continuous habitat for the snow leopard along the northern border of Nepal, but there is a gap in information about the snow leopard in Gaurishankar Conservation Area. Previous spatial analysis has suggested that the Lamabagar area in this Conservation Area could serve as a transbound- ary corridor for snow leopards, and that the area may con- nect local populations, creating a metapopulation. However, there has been no visual confirmation of the species in Lamabagar. We set !! infrared camera traps for " months in Lapchi Village of Gaurishankar Conservation Area, where blue sheep Pseudois nayaur, musk deer Moschus leucogaster and Himalayan tahr Hemitragus jemlahicus, all snow leopard prey species, had been observed. In November #$!% at &,!$$ m, ' km south-west of Lapchi Village, one camera recorded three images of a snow leopard, the first photographic evidence of the species in the Conservation Area. Sixteen other species of mammals were also recorded. Camera-trap records and sightings indicated a high abun- dance of Himalayan tahr, blue sheep and musk deer. Lapchi Village may be a potentially important corridor for snow leopard movement between the east and west of Nepal and northwards to Quomolongma National Park in China. However, plans for development in the region present in- creasing threats to this corridor. We recommend develop- ment of a transboundary conservation strategy for snow leopard conservation in this region, with participation of Nepal, China and international agencies.
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