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Khanyari, M., Oyanedel, R., Khara, A., Sharma, M., Milner-Gulland, E. J., Suryawanshi, K. R., Vineer, H. R., Morgan, E. R. (2024). Predicting and reducing potential parasite infection between migratory livestock and resident Asiatic ibex of Pin valley, India. Journal of Biosciences, 49(50), 1–14.
Abstract: Disease cross-transmission between wild and domestic ungulates can negatively impact livelihoods and wildlife conservation. In Pin valley, migratory sheep and goats share pastures seasonally with the resident Asiatic ibex (Capra sibirica), leading to potential disease cross-transmission. Focussing on gastro-intestinal nematodes (GINs) as determinants of health in ungulates, we hypothesized that infection on pastures would increase over summer from contamination by migrating livestock. Consequently, interventions in livestock that are well-timed should reduce infection pressure for ibex. Using a parasite life-cycle model, that predicts infective larval availability, we investigated GIN transmission dynamics and evaluated potential interventions. Migratory livestock were predicted to contribute most infective larvae onto shared pastures due to higher density and parasite levels, driving infections in both livestock and ibex. The model predicted a c.30-day anti- parasitic intervention towards the end of the livestock’s time in Pin would be most effective at reducing GINs in both hosts. Albeit with the caveats of not being able to provide evidence of interspecific parasite trans- mission due to the inability to identify parasite species, this case demonstrates the usefulness of our predictive model for investigating parasite transmission in landscapes where domestic and wild ungulates share pastures. Additionally, it suggests management options for further investigation.
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Singh, R., Krausman, P. R., Pandey, P., Maheshwari, A., Rawal,
R. S., Sharma, S., Shekhar, S. (2020). Predicting Habitat Suitability of Snow Leopards in the Western
Himalayan Mountains, India. Biology bulletin, 47(6), 655–664.
Abstract: The population of snow leopard (Panthera uncia) is declining
across their range, due to poaching, habitat fragmentation, retaliatory
killing, and a decrease of wild prey species. Obtaining information on
rare and cryptic predators living in remote and rugged terrain is
important for making conservation and management strategies. We used the
Maximum Entropy (MaxEnt) ecological niche modeling framework to predict
the potential habitat of snow leopards across the western Himalayan
region, India. The model was developed using 34 spatial species
occurrence points in the western Himalaya, and 26 parameters including,
prey species distribution, temperature, precipitation, land use and land
cover (LULC), slope, aspect, terrain ruggedness and altitude. Thirteen
variables contributed 98.6% towards predicting the distribution of snow
leopards. The area under the curve (AUC) score was high (0.994) for the
training data from our model, which indicates pre- dictive ability of
the model. The model predicted that there was 42432 km2 of potential
habitat for snow leop- ards in the western Himalaya region. Protected
status was available for 11247 km2 (26.5%), but the other 31185 km2
(73.5%) of potential habitat did not have any protected status. Thus,
our approach is useful for predicting the distribution and suitable
habitats and can focus field surveys in selected areas to save
resources, increase survey success, and improve conservation efforts for
snow leopards.
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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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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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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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Shao, X., Lu, Q., Xiong, M., Bu, H., Shi, X., Wang, D., Zhao, J., Li, S., Yao, M. (2021). Prey partitioning and livestock consumption in the world’s richest large carnivore assemblage. Current Biology, 31, 4887–4897.
Abstract: Large mammalian carnivores have undergone catastrophic declines during the Anthropocene across the world. Despite their pivotal roles as apex predators in food webs and ecosystem dynamics, few detailed di- etary datasets of large carnivores exist, prohibiting deep understanding of their coexistence and persistence in human-dominated landscapes. Here, we present fine-scaled, quantitative trophic interactions among sym- patric carnivores from three assemblages in the Mountains of Southwest China, a global biodiversity hotspot harboring the world’s richest large-carnivore diversity, derived from DNA metabarcoding of 1,097 fecal sam- ples. These assemblages comprise a large-carnivore guild ranging from zero to five species along with two mesocarnivore species. We constructed predator-prey food webs for each assemblage and identified 95 vertebrate prey taxa and 260 feeding interactions in sum. Each carnivore species consumed 6–39 prey taxa, and dietary diversity decreased with increased carnivore body mass across guilds. Dietary partitioning was more evident between large-carnivore and mesocarnivore guilds, yet different large carnivores showed divergent proportional utilization of different-sized prey correlating with their own body masses. Large car- nivores particularly selected livestock in Tibetan-dominated regions, where the indigenous people show high tolerance toward wild predators. Our results suggest that dietary niche partitioning and livestock subsidies facilitate large-carnivore sympatry and persistence and have key implications for sustainable conservation promoting human-carnivore coexistence.
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