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Pathak, A., Lamichhane, S., Dhakal, M., Karki, A., Dhakal, B. D., Chetri, M., Mintz, J., Pun, P., Neupane, P., Dahal, T. P., Rayamajhi, T., Paudel, P., Thapa, A., Regmi, P. R., Thami, S., Thapa, G., Khanal, S., Lama, S., Karki, J., Khanal, S., Ferdin, A. E. J. (2024). Human-wildlife conflict at high altitude: A case from Gaurishankar conservation area, Nepal. Ecology and Evolution, 14(e11685), 1–9.
Abstract: Human–wildlife conflict studies of high-altitude areas are rare due to budget constraints and the challenging nature of research in these remote environments. This study investigates the prevalence and increasing trend of human–wildlife conflict (HWC) in the mountainous Gaurishankar Conservation Area (GCA) of Nepal, with a specific focus on leopard (Panthera pardus) and Himalayan black bear (Ursus thibetanus laniger). The study analyzes a decade of HWC reports and identifies goats as the livestock most targeted by leopards. The Dolakha district of GCA received the highest number of reports, highlighting the need for mitigation measures in the area. In GCA, livestock attacks accounted for 85% of compensation, with the remaining 15% for human injuries. We estimate that the number of reported wildlife attacks grew on average by 33% per year, with an additional increase of 57 reports per year following the implementation of a new compensation policy during BS 2076 (2019 AD). While bear attacks showed no significant change post-rule alteration, leopard attack reports surged from 1 to 60 annually, indicating improved compensation may have resulted in increased leopard-attack reporting rates. The findings emphasize the economic impact of HWC on local communities and suggest strategies such as increasing prey populations, promoting community education and awareness, enhancing alternative livelihood options, developing community-based insurance programs, and implementing secure enclosures (corrals) to minimize conflicts and foster harmonious coexistence. This research addresses a knowledge gap in HWC in high- altitude conservation areas like the GCA, providing valuable insights for conservation stakeholders and contributing to biodiversity conservation and the well-being of humans and wildlife.
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Karki, A., Panthi, S. (2021). Factors affecting livestock depredation by snow leopards (Panthera uncia) in the Himalayan region of Nepal. PeerJ, 9(e11575), 1–14.
Abstract: The snow leopard (Panthera uncia) found in central Asia is classified as vulnerable species by the International Union for Conservation of Nature (IUCN). Every year, large number of livestock are killed by snow leopards in Nepal, leading to economic loss to local communities and making human-snow leopard conflict a major threat to snow leopard conservation. We conducted formal and informal stakeholder’s interviews to gather information related to livestock depredation with the aim to map the attack sites by the snow leopard. These sites were further validated by district forest office staffs to assess sources of bias. Attack sites older than 3 years were removed from the survey. We found 109 attack sites and visited all the sites for geo location purpose (GPS points of all unique sites were taken). We maintained at least a 100 m distance between attack locations to ensure that each attack location was unique, which resulted in 86 unique locations. A total of 235 km2 was used to define livestock depredation risk zone during this study. Using Maximum Entropy (MaxEnt) modeling, we found that distance to livestock sheds, distance to paths, aspect, and distance to roads were major contributing factors to the snow leopard’s attacks. We identified 13.64 km2 as risk zone for livestock depredation from snow leopards in the study area. Furthermore, snow leopards preferred to attack livestock near livestock shelters, far from human paths and at moderate distance from motor roads. These identified attack zones should be managed both for snow leopard conservation and livestock protection in order to balance human livelihoods while protecting snow leopards and their habitats.
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Tallian, A., Mattisson, J., Samelius, G., Odden, J., Mishra, C., Linnell, J. D. C., Lkhagvajav, P., Johansson, O. (2023). Wild versus domestic prey: Variation in the kill-site behavior of two large felids. Global Ecology and Conservation, 47(e026750), 1–13.
Abstract: Livestock depredation is an important source of conflict for many terrestrial large carnivore
species. Understanding the foraging behavior of large carnivores on domestic prey is therefore
important for both mitigating conflict and conserving threatened carnivore populations. Handling
time is an important, albeit often overlooked, component of predatory behavior, as it directly
influences access to food biomass, which can affect predator foraging efficiency and subsequent
kill rates. We used long-term data on snow leopards (Panthera uncia) in Mongolia (Asia) and
Eurasian lynx (Lynx lynx) in Norway (Europe) to examine how large carnivore foraging patterns
varied between domestic and wild prey, and how the different landscape characteristics affected
those patterns. Our results suggest handling time was generally shorter for domestic compared to
wild prey. For snow leopards, rugged terrain was linked to increased handling time for larger
prey. For lynx, handling time increased with terrain ruggedness for domestic, but not wild, prey,
and was greater in closed compared to open habitats. There were also other differences in snow
leopard and lynx foraging behavior, e.g., snow leopards also stayed longer at, and remained closer
to, their kill sites than lynx. Shorter handling time suggests that felids may have utilized domestic
prey less effectively than wild prey, i.e., they spent less time consuming their prey. This could a)
result in an energetic or fitness cost related to decreased felid foraging efficiency caused by the
risk of anthropogenic disturbance, or b) exacerbate conflict if reduced handling time associated
with easy prey results in increased livestock depredation.
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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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Yu, C., Ding, N., Li, Y., Liu, Y, Lyu, Z., Munkhtsog, B., Wuliji., Ma, Z., Se, Y., Pei, W., Gao, Y., Zhang, Y., Han, Q., Shi, K. (2022). Preliminary results from applying satellite-tracking on snow leopards for the first time in China. Global Ecology and Conservation, 40(e02346), 1–7.
Abstract: The lack of snow leopards telemetry studies in China has hampered researchers in studying the movement ecology and home range sizes of snow leopards, the knowledge gap of which has affected effective planning and improvement of snow leopard protected areas in China. In 2021, we conducted China’s first snow leopard satellite-tracking project in Qilianshan National Park, China, one of the most representative mountain areas of snow leopard habitat. The outcomes of the research aims to apply gained understanding on snow leopard home range to enhance management and planning of snow leopard protected area. Here we summarize the preliminary home range results on the first three satellite-tracked snow leopards in China. The three snow leopards were followed between 3 and 6 months yielding a total of 7845 GPS locations. Using
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Ahmad, S., Ali, H., Asif, M., Khan, T, Din, N., Rehman, E. U., Hameed, S., Din, J. U., Nawaz, M. A. (2022). Spatial density pattern of Himalayan Ibex (Capra sibirica) in Pakistan. Global Ecology & Conservation, 39(e02288), 1–12.
Abstract: Mountain ungulates perform a key role in maintaining the balance of ecosystems as they are the primary consumers of vegetation and prey for large predators. The mountain ranges of northern Pakistan are home to six species of mountain ungulates, and the Himalayan ibex (Capra sibirica), hereafter ibex, is the most abundant among them. This study was conducted in three administrative regions of northern Pakistan, viz. Gilgit-Baltistan (GB), Azad Jammu and Kashmir (AJK), and Khyber Pakhtunkhwa (KP), to generate a range-wide density pattern map of ibex. A double-observer survey was conducted in 25 study sites during 2018–2021 across the ibex distribution range, covering an area of about 35,307 km2, by walking transects totaling 1647 km. Within the ibex range where the survey was not conducted due to financial and logistical constraints, we obtained species population information from local wildlife departments’ most recent annual survey data. The aim was to generate a density map for the entire ibex range. Using the BBRe-capture package in program R, we estimated an ibex population of 7639 (95 % CI) with a mean density of 0.21/km2 in the surveyed area. Combining with the secondary data from un-surveyed areas, the total population estimate for the country came to 10,242 ibex. The largest population densities were observed in four valleys (Shimshal, Gulkin-Hussaini, Khyber, and Khunjerab) of the Karakoram-Pamir range, followed by the Hindu Kush range (Chitral Wildlife Division [WD]). The central and eastern parts of the Karakoram range had moderate to low densities, while the Himalayan range (e.g., Astore Valley) supported a small population. The mean herd size was 15 individuals (range: 5–41), and the average detection probability of observers A and B was 0.69 and 0.48, respectively. The average male and young ratios per 100 females were estimated to be 75 and 81, respectively. The range-wide density map developed during the study provided an evidence for the impact of trophy hunting programs and an objective tool for range-wide conservation planning of the species.
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Filla, M., Lama, R. P., Ghale, T. R., Filla, T., Heurich, M., Waltert, M., Khorozyan, I. (2022). Blue sheep strongly affect snow leopard relative abundance but not livestock depredation in the Annapurna Conservation Area, Nepal. Global Ecology and Conservation, 37(e02153), 1–15.
Abstract: Large carnivores play key roles in their ecosystems, but their protection is a major challenge in biodiversity conservation due to conflicts with human interests. The snow leopard (Panthera uncia) is the top predator of Asian high-altitude landscapes and faces various threats including wild prey depletion and illegal killings as a consequence of livestock depredation. As the interactions between snow leopards, wild prey, and livestock are still insufficiently understood, we studied the effects of 1) wild prey (blue sheep Pseudois nayaur and Himalayan marmots Marmota himalayana) and domestic prey on snow leopard relative abundance, and of 2) these ecological parameters and intervention applications on livestock depredation by snow leopards. In the Annapurna Conservation Area, Nepal, we monitored wildlife populations and livestock along transects (490.8 km) in 82 grid cells (4 ×4 km) in 2019 and 2021 and conducted questionnaire surveys to determine livestock depredation between 2018 and 2021 (n = 479 households). We applied generalized linear models (GLMs) and sample comparison testing to examine the effects of prey densities and other environmental and anthropogenic predictors on snow leopard relative abundance and livestock depredation. Blue sheep density strongly positively affected snow leopard relative abundance, which also increased with terrain ruggedness and decreased with increasing densities of livestock and the human population. The size of livestock holdings shaped depredation events of large livestock (yak, cattle and horse), whereas depredation events of sheep and goats, which accounted for most (68.6%) depredated animals, decreased with increasing human population density and marmot presence. The strong impact of blue sheep on snow leopard relative abundance supports demands for integrating this ungulate into conservation and management plans, including wild prey recovery and translocation. The rather weak evidence for effects of blue sheep on depredation events suggests that conflicts over livestock depredation by snow leopards would neither be inflicted nor solved by increasing wild prey abundance. This demonstrates the need to improve intervention strategies in the Annapurna region, such as predator-proofing corrals and optimizing daytime herding practices. We suggest further exploring the effects of marmots and other secondary prey on livestock depredation rates, and testing the suitability of additional interventions, e.g., dogs and deterrents, as conflict mitigation tools. Our results will support wildlife managers in setting conservation priorities to promote the long-term co-existence of local people and snow leopards.
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Rode, J., Lambert, C., Marescot, L., Chaix, B., Beesau, J., Bastian, S., Kyrbashev, J., Cabanat, A.L. (2021). Population monitoring of snow leopards using camera trapping in Naryn State Nature Reserve, Kyrgyzstan, between 2016 and 2019. Global Ecology and Conservation, 31(e01850), 1–6.
Abstract: Four field seasons of snow leopard (Panthera uncia) camera trapping inside Naryn State Nature Reserve, Kyrgyzstan, performed thanks to citizen science expeditions, allowed detecting a minimal population of five adults, caught every year with an equilibrated sex ratio (1.5:1) and reproduction: five cubs or subadults have been identified from three litters of two different females. Crossings were observed one to three times a year, in front of most camera traps, and several times a month in front of one of them. Overlap of adults’ minimal territories was observed in front of several camera traps, regardless of their sex. Significant snow leopard presence was detected in the buffer area and at Ulan area which is situated at the reserve border. To avoid poaching on this apex predator and its preys, extending the more stringent protection measures of the core zone to both the Southern buffer area and land adjacent to Ulan is recommended.
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Islam, M., Sahana, M., Areendran, G., Jamir, C., Raj, K., Sajjad, H. (2023). Prediction of potential habitat suitability of snow leopard (Panthera uncia) and blue sheep (Pseudois nayaur) and niche overlap in the parts of western Himalayan region. Geo: Geography and Environment, 10(e00121), 1–15.
Abstract: The snow leopard (Panthera uncia) and blue sheep (Pseudois nayaur) are the inhabitants of remote areas at higher altitudes with extreme geographic and climatic conditions. The habitats of these least-studied species are crucial for sustaining the Himalayan ecosystem. We employed the Maximum Entropy (MaxEnt) species distribution model to predict the potential habitat suitability of snow leopards and blue sheep and extracted common overlapped niches. For this, we utilised presence location, bio-climatic and environmental variables, and correlation analysis was applied to reduce the negative impact of multicollinearity. A total of 134 presence locations of snow leopards and 64 for blue sheep were selected from the Global Biodiversity Information Facility (GBIF). The annual mean temperature (Bio1) was found to be the most useful and highly influential factor to predict the potential habitat suitability of snow leopards. Annual mean temperature, annual precipitation and isothermality were the major influencing factors for blue sheep habitat suitability. Highly influential bio-climatic, topographic and environmental variables were integrated to construct the model for predicting habitat suitability. The area under the curve (AUC) values for snow leopard (0.87) and blue sheep (0.82) showed that the models are under good representation. Of the total area investigated, 47% was suitable for the blue sheep and 38% for the snow leopards. Spatial habitat assessment revealed that nearly 11% area from the predicted suitable habitat class of both species was spatially matched (overlapped), 48.6% area was unsuitable under niche overlap and 40.5% area was spatially mismatched niche. The presence of snow leopards and blue sheep in some highly suitable areas was not observed, yet such areas have the potential to sustain these elusive species. The other geographical regions interested in exploring habitat suitability may find the methodological framework adopted in this study useful for formulating an effective conservation policy and management strategy.
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Ahmad, S., Rehman, E. U., Ali, H., Din, N., Haider, J., Din, J. U., Nawaz, M. A. (2022). Density Pattern of Flare-Horned Markhor (Capra falconeri) in Northern Pakistan. Sustainability, 14(9567), 1–13.
Abstract: Wild ungulates play vital roles in maintaining a balanced ecosystem through herbivory and are also an important determinant of carnivores’ density. The flare-horned markhor (Capra falconeri) is a threatened wild goat distributed across the mountain ranges of Pakistan, India, Afghanistan, Russia, Turkmenistan, Uzbekistan, and Tajikistan. The remote terrain and fragmented population limit our understanding of the population ecology of markhor, though knowledge of the target species population is vital for making informed management decisions. Therefore, the current study was designed to determine the markhor population across their range in Northern Pakistan and to evaluate the efforts made by the government and non-government organizations for the conservation of markhor. Double-observer surveys were conducted during 2019–2021 in nine major watersheds of Khyber Pakhtunkhwa and Gilgit-Baltistan covering an area of 4664 km2. Secondary data were collected for unassessed areas to gain a holistic overview of the markhor population and density in the region. Results revealed a markhor population of 7579, with a density of 0.30 animals per km2 in Northern Pakistan. Our analysis of the double-observer data through the Bayesian behavioral capture–recapture model estimated a population of 5993 individuals (95% CI) of markhor across
nine study sites, with a density of 1.28 animals per km . A review of secondary data revealed that
a population of about 1586 was present in the un-surveyed area (20,033.33 km2), with a density
of 0.08 per km . A total of 146 groups of markhor were counted, with a mean group size of 23
(3–58) individuals. There were 109 males and 108 young per 100 females in the population. Among 1936 recorded males, Class I males accounted for 27.74%, followed by Class II (26.45%), Class IV (trophy-size) (23.40%), and Class III (22.42%). The overall detection probability was recorded as 0.87 and 0.68 for the first observer and second observer, respectively. Compared with the past reports, the population of markhor in Northern Pakistan appears to be increasing, particularly in protected areas (PAs) such as national parks and community-controlled hunting areas (CCHAs). Conservation programs, notably trophy hunting and PA networks, appear to be vital in sustaining markhor populations in parts of the species range. We recommend expansion in such programs in the markhor range in order to maintain a viable population of this majestic wild goat in the region.
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