Author: Editorial Team

Title: Implications of landscape genetics and connectivity of snow
leopard in the Nepalese Himalayas for its conservation.

Authors: Shrestha, B., Kindlmann, P.

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.

URL: https://snowleopardnetwork.org/bibliography/Shrestha_et_al_2020.pdf

Please find details of new articles added to the Bibliography:

Title: Patterns of human interaction with snow leopard and co-predators in the Mongolian western Altai: Current issues and perspectives

Authors: Augugliaro, C., Christe, P., Janchivlamdan, C., Baymanday, H., Zimmermann, F.

Abstract: Large carnivores can cause considerable economic damage, mainly due to livestock depredation. These conficts instigate negative attitude towards their conservation, which could in the extreme case lead to retaliatory killing. Here we focus on the snow leopard (Panthera uncia), a species of conservation concern with particularly large spatial requirements. We conducted the study in the Bayan Olgii province, one of the poorest provinces of Mongolia, where the majority of the human population are traditional herders. We conducted a survey among herders (N  261) through a semi-structured questionnaire with the aim to assess: the current and future herding practices and prevention measures, herders’ perceptions and knowledge of the environmental protection and hunting laws; the perceived livestock losses to snow leopard, wolf (Canis lupus), and wolverine (Gulo gulo), as well as to non-predatory factors; the key factors affecting livestock losses to these three large carnivores; and, finally, the attitudes towards these three large carnivores. Non-predatory causes of mortality were slightly higher than depredation cases, representing 4.5% and 4.3% of livestock holdings respectively. While no depredation of livestock was reported from wolverines, snow leopard and wolf depredation made up 0.2% and 4.1% of total livestock holdings, respectively. Herders’ attitudes towards the three large carnivores were negatively affected by the magnitude of the damages since they had a positive overall attitude towards both snow leopard and wolverine, whereas the attitude towards wolf was negative. We discuss conservation and management options to mitigate herder-snow leopard impacts. To palliate the negative consequences of the increasing trend in livestock numbers, herd size reduction should be encouraged by adding economic value to the individual livestock and/or by promoting alternative income and/or ecotourism. Furthermore, co-management between government and stakeholders would help tackle this complex problem, with herders playing a major role in the development of livestock management strategies. Traditional practices, such as regularly shifting campsites and using dogs and corrals at night, could reduce livestock losses caused by snow leopards.

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Title: Conservation and people: Towards an ethical code of conduct for the use of camera traps in wildlife research

Authors: Sharma, K., Fiechter, M., George, T., Young, J., Alexander, J. S., Bijoor, Suryawanshi, K., Mishra, C.

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.

URL: https://snowleopardnetwork.org/bibliography/Sharma_et_al_2020.pdf

Snow Leopard Trust press release via Mirage News

New research published in Ecological Evidence and Solutions explores the ethical and legal responsibilities of capturing humans on wildlife camera traps.

Camera traps set out for wildlife research often capture images of people including local community members and suspected poachers. A new article, published today in the peer-reviewed scientific journal Ecological Evidence and Solutions, calls for respecting the privacy of people photographed by remote cameras, and also lays out principles for fulfilling the public responsibility of reporting illegal activity caught on wildlife cameras.

Please find details below of a new article added to our Bibliography:

Title: What Factors Predispose Households in Trans-Himalaya (Central Nepal) to Livestock Predation by Snow Leopards?

Authors: Tiwari, M. P., Devkota, B. P., Jackson, R. M., Chhetri, B. B. K., Bagale, S.

Abstract: Livestock depredation across the trans-Himalaya causes significant economic losses to pastoralist communities. Quantification of livestock predation and the assessment of variables associated with depredation are crucial for designing effective long-term mitigation measures. We investigated the patterns and factors of livestock depredation by snow leopards (Panthera uncia) using semi-structured questionnaires targeting herders in the Narphu valley of the Annapurna Conservation Area, Nepal. During the two years (2017/18 and 2018/19), 73.9% of the households interviewed (n = 65) lost livestock to snow leopards, with an annual average loss of two livestock per household. Of the total depredation attributed to snow leopards, 55.4% were yak (mainly female: 79%), 31.7% goat, 6.8% sheep, 3.2% horse and 2.8% cattle. Results from applying Generalized Linear Mixed Models (GLMMs) revealed the total number of livestock owned and the number of larger bodied livestock species as the main explanatory covariates explaining livestock depredation. Forty-one (41%) of all herders considered snow leopard’s preference for domestic livestock as the main factor in livestock predation, whereas only 5% perceived poor herding practice as the main reason for the loss. Our study found poor and changing herding practices in the valley, whereby 71% herders reported careful herding as a solution to snow leopard depredation, and 15% of herders considered the complete extermination of snow leopards as the best solution to the problem. Tolerance levels and awareness among herders towards snow leopard conservation is increasing, mainly due to the Buddhist religion and strict law enforcement within this protected area. We recommend the effective implementation of a community-based livestock insurance scheme to compensate the economic loss of herders due to predation and improved herding practices as the recommended mitigation measures for ensuring livestock security and snow leopards’ conservation in the valley.

URL: https://snowleopardnetwork.org/bibliography/Tiwari_et_al.pdf

Please find below, details of new articles, added to the bibliography:

Title:  Identifying priority landscapes for conservation of snow leopards in Pakistan

Authors: Hameed, S., Din, J. U., Ali, H., Kabir, M., Younas, M., Rehman, E. U., Bari, F., Hao, W., Bischof, R., Nawaz, M. A.

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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Title: Fast, flexible alternatives to regular grid designs for spatial capture–recapture.

Authors: Durbach, I., Borchers, D., Sutherland, C., Sharma, K.

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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