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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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Bagchi, S., Sharma, R. K., Bhatnagar, Y.V. (2020). Change in snow leopard predation on livestock after revival of wild prey in the Trans-Himalaya. Wildlife Biology, , 1–11.
Abstract: Human–wildlife conflict arising from livestock-losses to large carnivores is an important challenge faced by conservation. Theory of prey–predator interactions suggests that revival of wild prey populations can reduce predator’s dependence on livestock in multiple-use landscapes. We explore whether 10-years of conservation efforts to revive wild prey could reduce snow leopard’s Panthera uncia consumption of livestock in the coupled human-and-natural Trans-Himalayan ecosystem of northern India. Starting in 2001, concerted conservation efforts at one site (intervention) attempted recovery of wild- prey populations by creating livestock-free reserves, accompanied with other incentives (e.g. insurance, vigilant herding). Another site, 50km away, was monitored as status quo without any interventions. Prey remains in snow leopard scats were examined periodically at five-year intervals between 2002 and 2012 to determine any temporal shift in diet at both sites to evaluate the effectiveness of conservation interventions. Consumption of livestock increased at the status quo site, while it decreased at the intervention-site. At the intervention-site, livestock-consumption reduced during 2002–2007 (by 17%, p = 0.06); this effect was sustained during the next five-year interval, and it was accompanied by a persistent increase in wild prey populations. Here we also noted increased predator populations, likely due to immigration into the study area. Despite the increase in the predator population, there was no increase in livestock-consumption. In contrast, under status quo, dependence on livestock increased during both five-year intervals (by 7%, p=0.08, and by 16%, p=0.01, respectively). These contrasts between the trajectories of the two sites suggest that livestock-loss can potentially be reduced through the revival of wild prey. Further, accommodating counter-factual scenarios may be an important step to infer whether conservation efforts achieve their targets, or not.
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Johansson, O., Samelius, G., Wikberg, E, Chapron, G., Mishra, C., Low, M. (2020). Identification errors in camera- trap studies result in systematic population overestimation. Scientific Reports, 10(6393), 1–10.
Abstract: Reliable assessments of animal abundance are key for successful conservation of endangered species. For elusive animals with individually-unique markings, camera-trap surveys are a benchmark standard for estimating local and global population abundance. Central to the reliability of resulting abundance estimates is the assumption that individuals are accurately identified from photographic captures. To quantify the risk of individual misidentification and its impact on population abundance estimates we performed an experiment under controlled conditions in which 16 captive snow leopards (Panthera uncia) were camera-trapped on 40 occasions and eight observers independently identified individuals and recaptures. Observers misclassified 12.5% of all capture occasions, resulting in systematically inflated population abundance estimates on average by one third (mean ± SD = 35 ± 21%). Our results show that identifying individually-unique individuals from camera-trap photos may not be as reliable as previously believed, implying that elusive and endangered species could be less abundant than current estimates indicate.
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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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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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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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Samelius, G., Suryawanshi, K., Frank, J., Agvaantseren, B., Baasandamba, E., Mijiddorj, T., Johansson, O., Tumursukh, L., Mishra, C. (2020). Keeping predators out: testing fences to reduce livestock depredation at night-time corrals. Oryx, , 1–7.
Abstract: Livestock depredation by large carnivores is a global conservation challenge, and mitigation measures to reduce livestock losses are crucial for the coexistence of large carnivores and people. Various measures are employed to reduce livestock depredation but their effectiveness has rarely been tested. In this study, we tested the effectiveness of tall fences to reduce livestock losses to snow leopards Panthera uncia and wolves Canis lupus at night-time corrals at the winter camps of livestock herders in the Tost Mountains in southern Mongolia. Self-reported livestock losses at the fenced corrals were reduced from a mean loss of 3.9 goats and sheep per family and winter prior to the study to zero losses in the two winters of the study. In contrast, self-reported livestock losses in winter pastures, and during the rest of the year, when herders used different camps, remained high, which indicates that livestock losses were reduced because of the fences, not because of temporal variation in predation pressure. Herder attitudes towards snow leopards were positive and remained positive during the study, whereas attitudes towards wolves, which attacked livestock also in summer when herders moved out on the steppes, were negative and worsened during the study. This study showed that tall fences can be very effective at reducing night-time losses at corrals and we conclude that fences can be an important tool for snow leopard conservation and for facilitating the coexistence of snow leopards and people.
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Shrestha, B., Kindlmann, P. (2020). Implications of landscape genetics and connectivity of snow
leopard in the Nepalese Himalayas for its conservation. (Vol. 10).
Abstract: The snow leopard is one of the most endangered large mammals.
Its population, already low, is declining, most likely due to the
consequences of human activity, including a reduction in the size and
number of suitable habitats. With climate change, habitat loss may
escalate, because of an upward shift in the tree line and concomitant
loss of the alpine zone, where the snow leopard lives. Migration between
suitable areas, therefore, is important because a decline in abundance
in these areas may result in inbreeding, fragmentation of populations,
reduction in genetic variation due to habitat fragmentation, loss of
connectivity, bottlenecks or genetic drift. Here we use our data
collected in Nepal to determine the areas suitable for snow leopards, by
using habitat suitability maps, and describe the genetic structure of
the snow leopard within and between these areas. We also determine the
influence of landscape features on the genetic structure of its
populations and reveal corridors connecting suitable areas. We conclude
that it is necessary to protect these natural corridors to maintain the
possibility of snow leopards' migration between suitable areas, which
will enable gene flow between the diminishing populations and thus
maintain a viable metapopulation of snow leopards.
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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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