Johansson, O., Mishra, C., Chapron, G., Samelius, G., Lkhagvajav, P., McCarthy, T., Low, M. (2022). Seasonal variation in daily activity patterns of snow leopards and their prey. Nature Portfolio, 12(21681), 1–11.
Abstract: The daily and seasonal activity patterns of snow leopards (Panthera uncia) are poorly understood, limiting our ecological understanding and hampering our ability to mitigate threats such as climate change and retaliatory killing in response to livestock predation. We fitted GPS-collars with activity loggers to snow leopards, Siberian ibex (Capra sibirica: their main prey), and domestic goats (Capra hircus: common livestock prey) in Mongolia between 2009 and 2020. Snow leopards were facultatively nocturnal with season-specific crepuscular activity peaks: seasonal activity shifted towards night- sunrise during summer, and day-sunset in winter. Snow leopard activity was in contrast to their prey, which were consistently diurnal. We interpret these results in relation to: (1) darkness as concealment for snow leopards when stalking in an open landscape (nocturnal activity), (2) low-intermediate light preferred for predatory ambush in steep rocky terrain (dawn and dusk activity), and (3) seasonal activity adjustments to facilitate thermoregulation in an extreme environment. These patterns suggest that to minimise human-wildlife conflict, livestock should be corralled at night and dawn in summer, and dusk in winter. It is likely that climate change will intensify seasonal effects on the snow leopard’s daily temporal niche for thermoregulation in the future.
|
Johansson, O., Agvaantseren, B., Jackson, R., Kachel, S., Kubanychbekov, Z., McCarthy, T., Mishra, C., Ostrowski, S., Kulenbekov, R., Rajabi, A. M., Subba, S. (2022). Body measurements of free-ranging snow leopards across their range. Snow Leopard Reports, 1, 1–6.
Abstract: We provide body measurements of snow leopards collected from 55 individuals sampled in five of the major mountain ranges within the species distribution range; the Altai, Hindu Kush, Himalayas, Pamirs and Tien Shan mountains. Snow leopards appear to be similarly sized across their distribution range with mean body masses of 36 kg and 42 kg for adult females and adult males, respectively. In contrast to other large felids, we found little variation in body size and body mass between the sexes; adult males were on average 5% longer and 15% heavier than adult females.
|
Johansson, O., Kachel, S., Weckworth, B. (2022). Guidelines for Telemetry Studies on Snow Leopards. Animals, 12(1663), 1–12.
Abstract: Animal-borne tracking devices have generated a wealth of new knowledge, allowing us to better understand, manage and conserve species. Fitting such tracking devices requires that animals are captured and often chemically immobilized. Such procedures cause stress and involve the risk of injuries and loss of life even in healthy individuals. For telemetry studies to be justifiable, it is vital that capture operations are planned and executed in an efficient and ethical way. Project objectives must be clearly articulated to address well-defined knowledge gaps, and studies designed to maximize the probability of achieving those goals. We provide guidelines for how to plan, design, and implement telemetry studies with a special emphasis on snow leopards that are typically captured using foot snares. We also describe the necessary steps to ensure that captures are conducted safely, and with minimal stress to animals.
|
Piaopiao, T., Suryawanshi, K. R., Lingyun, X., Mishra, C., Zhi, L., Alexander, J. S. (2022). Factors shaping the tolerance of local Tibetan herders toward snow leopards. Journal for Nature Conservation, 71 (2023)(126305), 1–8.
Abstract: Snow leopards (Panthera uncia) have long co-existed with livestock herding people across Asia’s high mountains. Multiple use landscapes however imply potential competition for shared resources, livestock predation, and the risk of retaliatory killing of predators. Community-based conservation is a central pillar for supporting people’s livelihoods and safeguarding predators and their habitat. Based on the theory of planned behavior, we examined the factors that shape herders’ tolerance of snow leopards. Our questionnaire-based study was conducted in the Sanjiangyuan Region, China, encompassing four communities with varying livelihoods, experiences with live- stock depredation and levels of exposure to community conservation interventions. Our results showed that respondents generally held positive views towards snow leopards, although women tended to have relatively more negative views towards snow leopards compared with men. Current household income was largely dependent on caterpillar fungus rather than livestock. Social norms around religion and the role of community leaders in our study area seemed to be the main determinants of the generally benign association of people with wildlife, overshadowing potential influences of community-based conservation interventions. Our work suggests that conservations programs will be aided through collaborations with communities and religious institutions, and that conservationists must proactively engage with women as significant actors in conservation.
|
Parker, B. G., Khanyari, M., Ambarli, H., Buuveibaatar, B., Kabir, M., Khanal, G., Mirzadeh, H. R., Onon, Y., Farhadinia, M. S. (2023). A review of the ecological and socioeconomic characteristics of trophy hunting across Asia. Animal Conservation, , 1–16.
Abstract: The continuing debates about trophy hunting should be underpinned by an understanding of at least the basic characteristics of the practice (e.g. species, quotas, areas, prices). Whilst many countries in Asia have established trophy hunting programmes of considerable importance to conservation and local livelihoods, there remains some ambiguity over the extent of trophy hunting in Asia as its basic characteristics in each country have not been compiled. In this study, we compile information on various ecological and socioeconomic characteristics of trophy hunting of mammals for countries across Asia by reviewing published and unpublished literature, analysing trade data, and obtaining contributions from in-country contacts. Across Asia, established trophy hunting programmes exist in at least 11 countries and target at least 30 species and one hybrid (incl., five Vulnerable and one Endangered species). Trophy hunting in these countries varies markedly in areas (e.g. >1 million km2 in Kazakhstan, 37% of country, vs. 1325 km2 in Nepal, <1% of country) and annual offtakes (e.g. Kazakhstan: 4500 individuals from 4 of 5 trophy species; Pakistan: 229 from 4 of 7; Mongolia: 155 from 6 of 9; Tajikistan: 126 from 3 of 6; Nepal: 22 from 3 of the 4 that are trophy hunted in practice). Permit prices also vary across species and countries, with domestic and international hunters sometimes charged different rates. Hunters from the USA appear overwhelmingly prominent among international clients. National legislations typically mandate a proportion of trophy hunting revenue to accrue locally (range: 40–100%). We provide five key recommendations for research to inform trophy hunting policy in Asia: (1) Ecological impact assessments; (2) Socioeconomic impact assessments; (3) Evaluations of the contributions of trophy hunting to conservation spending; (4) Evaluations of the contributions of trophy hunting to the post-2020 Global Biodiversity Framework; (5) Further examinations of perceptions of trophy hunting.
|
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.
|
Flora and Fauna International. (2006). Central Asia Snow Leopard Workshop. Author.
Abstract: Meeting report for the Central Asia Snow Leopard Workshop, held in Bishkek in June 2006.
|
Andriuskevicius, A. (1980). Occurrance of Snow Leopards in the Soviet Union. International Pedigree Book of Snow Leopards, 2, 59–69.
Abstract: Outlines status and distribution of snow leopard in USSR, including comments on reserves created for the species.
|
|
Anonymous. (1990). In Mongolia, Taking Stock of Rare Animals.
|
|
Anonymous. (1992). The 7th International Snow Leopard Symposium Presentation Abstracts. In International Snow Leopard Trust, & Northwest Plateau Institute of Biology (Eds.), The 7th International Snow Leopard Symposium Presentation Abstracts (pp. 1–15). 7th International Snow Leopard Symposium.
|
