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Esson, C., Skerratt, L. F., Berger, L., Malmsten, J., Strand, T., Lundkvist, A., Järhult, J. D., Michaux, J., Mijiddorj, T. N.,, Bayrakçısmith, R., Mishra, C., Johansson, O. (2019). Health and zoonotic Infections of snow leopards Panthera unica in the South Gobi desert of Mongolia. Infection Ecology & Epidemiology, 9(1604063), 1–11.
Abstract: Background: Snow leopards, Panthera uncia, are a threatened apex predator, scattered across the mountains of Central and South Asia. Disease threats to wild snow leopards have not been investigated.
Methods and Results: Between 2008 and 2015, twenty snow leopards in the South Gobi desert of Mongolia were captured and immobilised for health screening and radio-collaring. Blood samples and external parasites were collected for pathogen analyses using enzyme- linked immunosorbent assay (ELISA), microscopic agglutination test (MAT), and next- generation sequencing (NGS) techniques. The animals showed no clinical signs of disease, however, serum antibodies to significant zoonotic pathogens were detected. These patho- gens included, Coxiella burnetii, (25% prevalence), Leptospira spp., (20%), and Toxoplasma gondii (20%). Ticks collected from snow leopards contained potentially zoonotic bacteria from the genera Bacillus, Bacteroides, Campylobacter, Coxiella, Rickettsia, Staphylococcus and Streptococcus. Conclusions: The zoonotic pathogens identified in this study, in the short-term did not appear to cause illness in the snow leopards, but have caused illness in other wild felids. Therefore, surveillance for pathogens should be implemented to monitor for potential longer- term disease impacts on this snow leopard population. Keywords: Snow leopard; zoonoses; conservation; one health; Mongolia; ticks
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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. |
Din, J. U., Nawaz, M. A., Norma-Rashid, Y., Ahmad, F., Hussain, K., Ali, H., Adli, D., S., H. (2020). Ecosystem Services in a Snow Leopard Landscape: A Comparative Analysis of Two High-elevation National Parks in the Karakoram-Pamir. Bio One, , 11–19.
Abstract: The high-elevation mountain ecosystems in the Karakoram and Pamir mountain ranges encompass enchanting landscapes, harbor unique biodiversity, and are home to many indigenous pastoral societies that rely onecosystem services for their survival. However, our understanding of the value of ecosystem services to a household economy is limited. This information is essential in devising sustainable development strategies and thus merits consideration. In this preliminary study, we attempted to assess and compare the value of selected ecosystem Khunjerab and Qurumbar National Parks (KNP and QNP) in the services of the KNP and QNP) in the Karakoram–Pamir in northern Pakistan using market-based and value transfer methods. Our results indicated that the economic benefits derived from the 2 high-elevation protected areas were US$ 4.6 million (QNP) and US$ 3.8 million (KNP) per year, translating into US$ 5955 and US$ 8912 per household per year, respectively. The monetary benefits from provisioning services constituted about 93% in QNP and 48% in KNP, which vividly highlights the prominence of the economic benefits generated from the protected areas for the welfare of disadvantaged communities. Together with the regulatory and cultural services valued
in this study, the perceived economic impact per household per year was 10–15 times higher than the mean household income per year. Considering the limited livelihood means and escalating poverty experienced by buffer zone communities, these values are substantial. We anticipate that communities’ dependency on resources will contribute to increased degradation of ecosystems. We propose reducing communities’ dependency on natural resources by promoting sustainable alternative livelihood options and recognizing ecosystem services in cost–benefit analyses when formulating future policies. Keywords: ecosystem services; economic value; Karakoram; Pamir; Khunjerab; national park; Qurumbar
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Din, J. U., Bari, F., Ali, H., Rehman, E. U., Adli, D. S. H., Abdullah, N. A., Norma-Rashid, Y., Kabir, M., Hameed, S., Nawaz, D. A., Nawaz, M. A. (2022). Drivers of snow leopard poaching and trade in Pakistan and implications for management. Nature Conservation, 46, 49–62.
Abstract: The snow leopard is one of the highly valued species from high-altitude mountain ecosystems of Central and Southeast Asia, including Pakistan. This keystone species is facing a myriad of conventional and emerging threats, including poaching and trade, that are poorly documented in Pakistan. To understand the dynamics and drivers of the poaching and trading of snow leopards in Pakistan, we investigated the issue in depth through a multifaceted survey in the snow leopard range of the country. We recorded 101 snow leopard poaching incidences from 11 districts during 2005–2017. The reported poaching incidences varied spatially (‒x = 9 ± 2.6 [95% Cl: 3–15]) and temporally (‒x = 7.8 ± 1.09) and accounted for 2–4% annual population loss (n = 200–420) in a period of 13 years. Poaching and trade together constituted 89% of the total incidence reported and animals were mostly shot (66%), poisoned (12%), snared (12%) and captured (4%), respectively. Only a fraction (3%) of the incidences were reported to the relevant law enforcement agencies. Trade routes included large cities and neighbouring countries, even the Middle East and Europe. The average base and end prices for each item were 245 ± 36 USD and 1,736 ± 520 USD, respectively, while maximum monetary fines set as per the law were 275 USD. Our results establish the need for developing multi-stakeholder coordination mechanisms at regional, national and international levels and information sharing to curb this menace. Improving the existing laws and surveillance system, while taking the local communities onboard, will further help to this end.
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Chimed, O., Lkhagvasuren, D., Alexander, J. S., Barclay, D., Bayasgalan, N., Lkhagvajav, P., Nygren, E., Robinson, S. L., Samelius, G. (2023). Delivery of educational material increased awareness of the elusive Pallas’s cat in Southern Mongolia. Applied Environmental Education & Comunication, , 1–13.
Abstract: Public engagement and awareness programs are important components of many conservation programs today as such engagements are often critical for successful conservation. In this study, we examined if delivery of educational material increased awareness of the Pallas’s cat and its environment in a southern Mongolia herder community. We found that knowledge was greater and attitudes toward the Pallas’s cat and wildlife in general were more positive one year after the delivery of the educational material. This study thus suggests that educational material can be effective at increasing awareness of small and elusive species such as the Pallas’s cat.
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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. |
Changxi, X., Bai, D., Lambert, J. P., Li, Y., Cering, L., Gong, Z., Riordan, P., Shi, K. (2022). How Snow Leopards Share the Same Landscape with Tibetan Agro-pastoral Communities in the Chinese Himalayas. Journal of Resources and Ecology, 13(3), 483–500.
Abstract: The snow leopard (Panthera uncia) inhabits a human-altered alpine landscape and is often tolerated by residents in regions where the dominant religion is Tibetan Buddhism, including in Qomolangma NNR on the northern side of the Chinese Himalayas. Despite these positive attitudes, many decades of rapid economic development and population growth can cause increasing disturbance to the snow leopards, altering their habitat use patterns and ultimately impacting their conservation. We adopted a dynamic landscape ecology perspective and used multi-scale technique and occupancy model to better understand snow leopard habitat use and coexistence with humans in an 825 km2 communal landscape. We ranked eight hypothetical models containing potential natural and anthropogenic drivers of habitat use and compared them between summer and winter seasons within a year. HABITAT was the optimal model in winter, whereas ANTHROPOGENIC INFLUENCE was the top ranking in summer (AICcw≤2). Overall, model performance was better in the winter than in the summer, suggesting that perhaps some latent summer covariates were not measured. Among the individual variables, terrain ruggedness strongly affected snow leopard habitat use in the winter, but not in the summer. Univariate modeling suggested snow leopards prefer to use rugged land in winter with a broad scale (4000 m focal radius) but with a lesser scale in summer (30 m); Snow leopards preferred habitat with a slope of 22° at a scale of 1000 m throughout both seasons, which is possibly correlated with prey occurrence. Furthermore, all covariates mentioned above showed inextricable ties with human activities (presence of settlements and grazing intensity). Our findings show that multiple sources of anthropogenic activity have complex connections with snow leopard habitat use, even under low human density when anthropogenic activities are sparsely distributed across a vast landscape. This study is also valuable for habitat use research in the future, especially regarding covariate selection for finite sample sizes in inaccessible terrain.
Keywords: habitat use; landscape ecology; occupancy model; Qomolangma; Panthera uncia
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Bohnett, E., Holmberg, J., Faryabi, S. P., An, L., Ahmad, B., Rashid, W., Ostrowski, S. (2023). Comparison of two individual identification algorithms for snow leopards (Panthera uncia) after automated detection. Ecological Informatics, 77(102214), 1–14.
Abstract: Photo-identification of individual snow leopards (Panthera uncia) is the primary data source for density estimation via capture-recapture statistical methods. To identify individual snow leopards in camera trap imagery, it is necessary to match individuals from a large number of images from multiple cameras and historical catalogues, which is both time-consuming and costly. The camouflaged snow leopards also make it difficult for machine learning to classify photos, as they blend in so well with the surrounding mountain environment, rendering applicable software solutions unavailable for the species. To potentially make snow leopard individual identification available via an artificial intelligence (AI) software interface, we first trained and evaluated image classification techniques for a convolutional neural network, pose invariant embeddings (PIE) (a triplet loss network), and compared the accuracy of PIE to that of the HotSpotter algorithm (a SIFT-based algorithm). Data were acquired from a curated library of free-ranging snow leopards taken in Afghanistan between 2012 and 2019 and from captive animals in zoos in Finland, Sweden, Germany, and the United States. We discovered several flaws in the initial PIE model, such as a small amount of background matching, that was addressed, albeit likely not fixed, using background subtraction (BGS) and left-right mirroring (LR) techniques which demonstrated reasonable accuracy (Rank 1: 74% Rank-5: 92%) comparable to the Hotspotter results (Rank 1: 74% Rank 2: 84%)The PIE BGS LR model, in conjunction with Hotspotter, yielded the following results: Rank-1: 85%, Rank-5: 95%, Rank-20: 99%. In general, our findings indicate that PIE BGS LR, in conjunction with HotSpotter, can classify snow leopards more accurately than using either algorithm alone.
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Bohnett, E., Faryabi, S. P., Lewison, R., An, L., Bian, X., Rajabi, A. M., Jahed, N., Rooyesh, H., Mills, E., Ramos, S., Mesnildrey, N., Perez, C. M. S., Taylor, J., Terentyev, V., Ostrowski, S. (2023). Human expertise combined with artificial intelligence improves performance of snow leopard camera trap studies. Global Ecology & Conservation, 41(e02350), 1–13.
Abstract: Camera trapping is the most widely used data collection method for estimating snow leopard (Panthera uncia) abundance; however, the accuracy of this method is limited by human observer errors from misclassifying individuals in camera trap images. We evaluated the extent Whiskerbook (www.whiskerbook.org), an artificial intelligence (AI) software, could reduce this error rate and enhance the accuracy of capture-recapture abundance estimates. Using 439 images of 34 captive snow leopard individuals, classification was performed by five observers with prior experience in individual snow leopard ID (“experts”) and five observers with no such experience (“novices”). The “expert” observers classified 35 out of 34 snow leopard individuals, on average erroneously splitting one individual into two, thus resulting in a higher number than true individuals. The success rate of experts was 90 %, with less than a 3 % error in estimating the population size in capture-recapture modeling. However, the “novice” observers successfully matched 71 % of encounters, recognizing 25 out of 34 individuals, underestimating the population by 25 %. It was found that expert observers significantly outperformed novice observers, making statistically fewer errors (Mann Whitney U test P = 0.01) and finding the true number of individuals (P = 0.01). These differences were contrasted with a previous study by Johansson et al. 2020, using the same subset of 16 individuals from European zoos. With the help of AI and the Whiskerbook platform, “experts” were able to match 87 % of encounters and identify 15 out of 16 individuals, with modeled estimates of 16 ± 1 individuals. In contrast, “novices” were 63 % accurate in matching encounters and identified 12 out of 16 individuals, modeling 12 ± 1 individuals that underestimated the population size by 12 %. When comparing the performance of observers using AI and the Whiskerbook platform to observers performing the tasks manually, we found that observers using Whiskerbook made significantly fewer errors in splitting one individual into two (P = 0.04). However, there were also a significantly higher number of combination errors, where two individuals were combined into one (P = 0.01). Specifically, combination errors were found to be made by “novices” (P = 0.04). Although AI benefited both expert and novice observers, expert observers outperformed novices. Our results suggest that AI effectively reduced the misclassification of individual snow leopards in camera trap studies, improving abundance estimates. However, even with AI support, expert observers were needed to obtain the most accurate estimates.
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Bhatia, S., Suryawanshi, K., Redpath, S., Namgail, S., Mishra, C. (2021). Understanding People's Relationship With Wildlife in Trans-Himalayan Folklore. Frontiers in Environmental Science, 9(595169), 1–10.
Abstract: People's views and values for wild animals are often a result of their experiences and traditional knowledge. Local folklore represents a resource that can enable an understanding of the nature of human-wildlife interactions, especially the underlying cultural values. Using archival searches and semi-structured interviews, we collected narratives about the ibex (Capra sibirica) (n = 69), and its predators, the wolf (Canis lupus) (n = 52) and the snow leopard (Panthera uncia) (n = 43), in Ladakh, India. We compared these stories to those of a mythical carnivore called seng ge or snow lion (n = 19), frequently referenced in local Tibetan Buddhist folklore and believed to share many of the traits commonly associated with snow leopards (except for livestock depredation). We then categorized the values along social-cultural, ecological and psychological dimensions. We found that the ibex was predominantly associated with utilitarianism and positive symbolism. Both snow leopard and wolf narratives referenced negative affective and negative symbolic values, though more frequently in the case of wolves. Snow leopard narratives largely focused on utilitarian and ecologistic values. In contrast, snow lion narratives were mostly associated with positive symbolism. Our results suggest that especially for snow leopards and wolves, any potentially positive symbolic associations appeared to be overwhelmed by negative sentiments because of their tendency to prey on livestock, unlike in the case of the snow lion. Since these values reflect people's real and multifarious interactions with wildlife, we recommend paying greater attention to understanding the overlaps between natural and cultural heritage conservation to facilitate human-wildlife coexistence.
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