|
Maheshwari, A., Niraj, S. K. (2018). Monitoring illegal trade in snow leopards: 2003e2014. Elsevier, , 1–6.
Abstract: Illegal trade in snow leopards (Panthera uncia) has been identified as one of the major
threats to long-term survival of the species in the wild. To quantify severity of the threats
to dwindling snow leopard population, we examined market and questionnaire surveys,
and information from the published and unpublished literature on illegal trade and
poaching of snow leopards.We collected information from 11 of the 12 snow leopard range
counties in central and southern Asia, barring Kazakhstan, and reported 439 snow leopards
(88 records) in illegal trade during 2003e2014, which represents a loss of approximately
8.4%e10.9% snow leopard population (assuming mid-point population of 5240 to
minimum population of 4000 individuals) in a period of 12 years. Our data suggested a 61%
decadal increase in snow leopard trade during 2003e2012 compared with 1993e2002,
while taking the note of significant strengthening of wildlife enforcement and crime
control network in the decades of 2000s and 2010s. We found 50% prosecution rate of
snow leopard crimes resulting in only 20% conviction rate globally. Many limitations e.g.,
secretive nature of illegal trade, ill developed enforcement mechanism, poor and passive
documentation of snow leopards' seizures, restricted us to reflect actual trend of snow
leopards' illegal trade. Even on a conservative scale the present situation is alarming and
may detrimental to snow leopard conservation. We propose an effective networking of
enforcement efforts and coordination among the law enforcement agencies, efficient
collection of data and data management, and sharing of intelligence in snow leopard range
countries, could be useful in curbing illegal trade in snow leopards in central and southern
Asia.
|
|
|
Schutgens, M. G., Hanson, J. H., Baral, N., Ale, S. B. (2018). Visitors’ willingness to pay for snow leopard Panthera uncia conservation in the Annapurna Conservation Area, Nepal. Oryx, , 1–10.
Abstract: The Vulnerable snow leopard Panthera uncia experiences
persecution across its habitat in Central Asia, particularly
from herders because of livestock losses. Given the
popularity of snow leopards worldwide, transferring some
of the value attributed by the international community to
these predators may secure funds and support for their conservation.
We administered contingent valuation surveys to
 international visitors to the Annapurna Conservation
Area, Nepal, between May and June , to determine
their willingness to pay a fee to support the implementation
of a Snow Leopard Conservation Action Plan. Of the %of
visitors who stated they would pay a snow leopard conservation
fee in addition to the existing entry fee, the mean
amount that they were willing to pay was USD  per trip.
The logit regression model showed that the bid amount, the
level of support for implementing the Action Plan, and the
number of days spent in the Conservation Area were significant
predictors of visitors’ willingness to pay. The main reasons
stated by visitors for their willingness to pay were a
desire to protect the environment and an affordable fee. A
major reason for visitors’ unwillingness to pay was that
the proposed conservation fee was too expensive for them.
This study represents the first application of economic valuation
to snow leopards, and is relevant to the conservation of
threatened species in the Annapurna Conservation Area
and elsewhere.
|
|
|
Khanal, G., Poudyal, L. P., Devkota, B. P., Ranabhat, R., Wegge, P. (2018). Status and conservation of the snow leopard Panthera uncia in Api Nampa Conservation Area, Nepal. Fauna & Flora International, , 1–8.
Abstract: The snow leopard Panthera uncia is globally
threatened and reliable information on its abundance,
distribution and prey species is a prerequisite for its conservation.
In October-November 2014 we assessed the distribution
of the snow leopard in the recently established Api
Nampa Conservation Area in the Nepal Himalayas.
Within selected blocks we conducted sign surveys and
counted the number of bharal Pseudois nayaur, its principal
wild prey, along transects totalling 106 km.We recorded 203
putative snow leopard signs at an encounter rate of 1.91
signs/km. Generalized linear models of the number of
signs detected per transect showed that elevation had a positive
influence and human activities a negative influence on
sign encounter rate; prey abundance had only a weak positive
influence on sign encounter rate. Within the effectively
surveyed area of c. 2002 km2, we counted 527 bharal at an estimated
density of 2.28 animals/km2. Recruitment of bharal
was low, estimated at 48 kids/100 adult females, most likely a
result of poor or overgrazed rangeland. We estimate
the total number of bharal in this conservation area to be
.>1,000, a prey base that could sustain 6-9 snow leopards.
Based on our field observations, we identified human disturbance
and habitat degradation associated with extraction
of non-timber forest products, livestock grazing, and poaching
as the main threats to the snow leopard. Standardized
sign surveys, preferably supplemented by sampling with
remote cameras or with genetic analysis of scats would
provide robust baseline information on the abundance of
snow leopards in this conservation area.
|
|
|
Thapa, K., Rayamajhi, S. (2023). Anti-predator strategies of blue sheep (naur) under varied predator compositions: a comparison of snow leopard-inhabited valleys with and without wolves in Nepal. Wildlife Research, , 1–9.
Abstract: In Nepal, naur are usually the staple wild prey for the snow leopard, a solitary stalker hunter, and in some cases, for the wolf who hunts in a pack. We assumed that naur would adapt their anti-predatory responses to the presence of chasing and ambushing predators in the Manang Valley, where there are snow leopards and wolves, and in the Nar Phu valley, an area where there is only the snow leopard.
Aims. The aim of this study was to determine if there were differences in anti-predator strategies (vigilance, habitat selection and escape terrain) of naur in two valleys over two seasons, spring and autumn.
Methods. In spring 2019, we conducted a reconnaissance survey on the status of the naur and its habitat in the Manang and Nar Phu valleys of the Annapurna Conservation Area, Nepal. In spring and autumn 2020 and 2021, we observed 360 focal naur individuals (180 individuals in each valley), using the vigilance behaviour methodology to examine the behaviour of the naur.
Key results. There was little difference in the size of the naur groups between the Manang and Nar Phu valleys. The naur were twice as vigilant in Manang (15%), where there are snow leopards and wolves, as they were in Nar Phu (9%), with only snow leopards. The distance from the naur to escape cover was significantly shorter in Manang than in Nar Phu valley. Naur used significantly more rolling terrain in Nar Phu than in Manang. Conclusions. The return of wolves to the Manang valley may have resulted in an increase in the level of naur vigilance. Most likely, the wolves in Manang have already had an effect on the female-to-young-ratio, and this effect will possibly have important consequences for the naur population, as well as at the ecosystem level in the future. Other key determining factors, such as the climate crisis and changes in local resources, could have a significant impact on the naur population, indicating the need for more research. Implications. The findings of this study would provide valuable baseline information for the design of a science-based conservation strategy for conservation managers and scientists on naur, snow leopards and wolves.
|
|
|
Kichloo, M. A., Sharma, K., Sharma, N. (2023). Climate casualties or human disturbance? Shrinking distribution of the three large carnivores in the Greater Himalaya. Springer – Climatic Change, 176(118), 1–17.
Abstract: Mammalian carnivores are key to our understanding of ecosystem dynamics, but most of them are threatened with extinction all over the world. Conservating large carnivores is often an arduous task considering the complex relationship between humans and carnivores, and the diverse range and reasons of threats they face. Climate change is exacerbating the situation further by interacting with most existing threats and amplifying their impacts. The Mountains of Central and South Asia are warming twice as rapidly as the rest of the northern hemisphere. There has been limited research on the effect of climate change and other variables on large carnivores. We studied the patterns in spatio-temporal distribution of three sympatric carnivores, common leopard, snow leopard, and Asiatic black bear in Kishtwar high altitude National Park, a protected area in the Great Himalayan region of Jammu and Kashmir. We investigated the effects of key habitat characteristics as well as human disturbance and climatic factors to understand the spatio-temporal change in their distributions between the early 1990s and around the year 2016–2017. We found a marked contraction in the distribution of the three carnivores between the two time periods. While snow leopard shifted upwards and further away from human settlements, common leopard and Asiatic black bear suffered higher rates of local extinctions at higher altitudes and shifted to lower areas with more vegetation, even if that brought them closer to settlements. We also found some evidence that snow leopards were less likely to have faced range contraction in areas with permanent glaciers. Our study underscores the importance of climate adaptive conservation practices for long-term management in the Greater Himalaya, including the monitoring of changes in habitat, and space-use patterns by human communities and wildlife.
|
|
|
Zhang, C., Ma, T., Ma, D. (2023). Status of the snow leopard Panthera uncia in the Qilian Mountains, Gansu Province, China. Oryx, , 1–6.
Abstract: Population density estimation is integral to the effective conservation and management of wildlife. The snow leopard Panthera uncia is categorized as Vulnerable on the IUCN Red List, and reliable information on its density is a prerequisite for its conservation and management. Little is known about the status of the snow leopard in the central and eastern Qilian Mountains, China. To address this, we estimated the population density of the snow leopard using a spatially explicit capture–recapture model based on camera trapping in Machang in the central and eastern Qilian Mountains during January–March 2019. We set up
40 camera traps and recorded 84 separate snow leopard captures over 3,024 trap-days. We identified 18 individual snow leopards and estimated their density to be 2.26/100 km. Our study provides baseline information on the snow leopard and the first population estimate for the species in the central and eastern Qilian Mountains.
|
|
|
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.
|
|
|
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.
|
|
|
Atzeni, L., Wang, J., Riordan, P., Shi, K., Cushman, S. A. (2023). Landscape resistance to gene flow in a snow leopard population from Qilianshan National Park, Gansu, China. Landscape Ecology, .
Abstract: Context: The accurate estimation of landscape resistance to movement is important for ecological understanding and conservation applications. Rigorous estimation of resistance requires validation and optimization. One approach uses genetic data for the optimization or validation of resistance models. Objectives We used a genetic dataset of snow leopards from China to evaluate how landscape genetics resistance models varied across genetic distances and spatial scales of analysis. We evaluated whether landscape genetics models were superior to models of resistance derived from habitat suitability or isolation-by-distance.
Methods: We regressed genetically optimized, habitat-based, and isolation-by-distance hypotheses against genetic distances using mixed effect models. We explored all subset combinations of genetically optimized variables to find the most supported resistance scenario for each genetic distance.
Results: Genetically optimized models always out-performed habitat-based and isolation-by-distance hypotheses. The choice of genetic distances influenced the apparent influence of variables, their spatial scales and their functional response shapes, producing divergent resistance scenarios. Gene flow in snow leopards was largely facilitated by areas of intermediate ruggedness at intermediate elevations corresponding to small-to-large valleys within and between the mountain ranges.
Conclusions: This study highlights that landscape genetics models provide superior estimation of functional dispersal than habitat surrogates and suggests that optimization of genetic distance should be included as an optimization routine in landscape genetics, along with variables, scales, effect size and functional response shape. Furthermore, our study provides new insights on the ecological conditions that promote gene flow in snow leopards, which expands ecological knowledge, and we hope will improve conservation planning.
|
|
|
Rashid, W., Shi, J., Rahim, I. U., Dong, S., Ahmad, L. (2020). Research trends and management options in human-snow leopard conflict. Biological Conservation, 242(108413), 1–10.
Abstract: Conservation of the snow leopard (Panthera uncia) is challenging because of its threatened status and increase in human-snow leopard conflict (HSC). The area of occupancy of the snow leopard comprises mountainous regions of Asia that are confronted with various environmental pressures including climate change. HSCs have increased with a burgeoning human population and economic activities that enhance competition between human and snow leopard or its preys. Here we systematically review the peer-reviewed literature from 1994 to 2018 in Web of Science, Google Scholar, Science Direct and PubMed (30 articles), to evaluate the current state of scholarship about HSCs and their management. We determine: 1) the spatio-temporal distribution of relevant researches; 2) the methodologies to assess HSCs; 3) and evaluate existing interventions for conflict management; and 4) the potential options for HSC management. The aim of the current study is thus to identify key research gaps and future research requirements. Of the articles in this review, 60% evaluated the mitigation of HSCs, while only 37% provided actionable and decisive results. Compensation programs and livestock management strategies had high success rates for mitigating HSCs through direct or community-managed interventions. Further research is required to evaluate the efficacy of existing HSC mitigation strategies, many of which, while recommended, lack proper support. In spite of the progress made in HSC studies, research is needed to examine ecological and sociocultural context of HSCs. We suggest future work focus on rangeland management for HSC mitigation, thus ultimately fostering a co-existence between human and snow leopard.
|
|