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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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Brem A.E. (1992). Irbis, or snow leopard (Felis uncia) (Vol. Vol.1. Mammals.).
Abstract: Snow leopard is met in the mountains of Turkistan, Altai, Bukhara, Pamir, Kashmir, and Tibet, and probably in South-East Siberia and along Sungari. In 1871, two animals were living in the Moscow Zoo Garden.
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Chakraborty, R. E., & Chakraborty, S. (1996). Identification of dorsal guard hairs of Indian species of the genus Panthera Oken (Carnivora: Felidae). Mammalia, 60(3), 480.
Abstract: Dorsal guard hairs of four living Indian species of the genus Panthera, viz. P. tigris, P. leo, P. pardus and P. uncia have been studied. It is found that the characters are somewhat overlapping, but identification of the species may be possible from the combination of characters.
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Geptner V.G. (1972). Genus snow leopard or irbis (Vol. Vol. 2, Part 2.).
Abstract: It describes genus and species features of snow leopard such as appearance, skull, sizes, phylogenetic links, distribution, geographic variability, biology including number, habitat, refuges, activity in daylight and night, behavioral patterns, reproduction, enemies and rivals, and practical use of the species.
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Henschel, P., & Ray, J. (2003). Leopards in African Rainforests: Survey and Monitoring Techniques (Wildlife Conservation Society, Ed.).
Abstract: Monitoring Techniques Forest leopards have never been systematically surveyed in African forests, in spite of their potentially vital ecological role as the sole large mammalian predators in these systems. Because leopards are rarely seen in this habitat, and are difficult to survey using the most common techniques for assessing relative abundances of forest mammals, baseline knowledge of leopard ecology and responses to human disturbance in African forests remain largely unknown. This technical handbook sums up the experience gained during a two-year study of leopards by Philipp Henschel in the Lop‚ Reserve in Gabon, Central Africa, in 2001/2002, supplemented by additional experience from carnivore studies conducted by Justina Ray in southwestern Central African Republic and eastern Congo (Zaire) . The main focus of this effort has been to develop a protocol that can be used by fieldworkers across west and central Africa to estimate leopard densities in various forest types. In developing this manual, Henschel tested several indirect methods to assess leopard numbers in both logged and unlogged forests, with the main effort devoted to testing remote photography survey methods developed for tigers by Karanth (e.g., Karanth 1995, Karanth & Nichols 1998; 2000; 2002), and modifying them for the specific conditions characterizing African forest environments. This handbook summarizes the results of the field testing, and provides recommendations for techniques to assess leopard presence/absence, relative abundance, and densities in African forest sites. We briefly review the suitability of various methods for different study objectives and go into particular detail on remote photography survey methodology, adapting previously developed methods and sampling considerations specifically to the African forest environment. Finally, we briefly discuss how camera trapping may be used as a tool to survey other forest mammals. Developing a survey protocol for African leopards is a necessary first step towards a regional assessment and priority setting exercise targeted at forest leopards, similar to those carried out on large carnivores in Asian and South American forests.
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Jackson, R., Roe, J., Wangchuk, R., & Hunter, D. (2006). Estimating Snow Leopard Population Abundance Using Photography and Capture-Recapture Techniques (Vol. 34).
Abstract: Conservation and management of snow leopards (Uncia uncial) has largely relied on anecdotal evidence and presence-absence data due to their cryptic nature and the difficult terrain they inhabit. These methods generally lack the scientific rigor necessary to accurately estimate population size and monitor trends. We evaluated the use of photography in capture-mark-recapture (CMR) techniques for estimating snow leopard population abundance and density within Hemis National Park, Ladakh, India. We placed infrared camera traps along actively used travel paths, scent-sprayed rocks, and scrape sites within 16-30 kmý sampling grids in successive winters during January and March 2003-2004. We used head-on, oblique, and side-view camera configurations to obtain snow leopard photographs at varying body orientations. We calculated snow leopard abundance estimates using the program CAPTURE. We obtained a total of 66 and 49 snow leopard captures resulting in 8.91 and 5.63 individuals per 100 trap nights during 2003 and 2004, respectively. We identified snow leopards based on the distinct pelage patters located primarily on the forelimbs, flanks, and dorsal surface of the tail. Capture probabilities ranged from 0.33 to 0.67. Density estimates ranged from 8.49 (SE+0.22) individuals per 100 kmý in 2003 to 4.45 (SE+0.16) in 2004. We believe the density disparity between years is attributable to different trap density and placement rather than to an actual decline in population size. Our results suggest that photographic capture-mark-recapture sampling may be a useful tool for monitoring demographic patterns. However, we believe a larger sample size would be necessary for generating a statistically robust estimate of population density and abundance based on CMR models.
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Janecka, J. E., Jackson, R., Munkhtsog, B., Murphy, W. J. (2014). Characterization of 9 microsatellites and primers in snow leopards and a species-specific PCR assay for identifying noninvasive samples. Conservation Genetic Resource, 6(2), 369:373.
Abstract: Molecular markers that can effectively identify noninvasively collected samples and provide genetic
information are critical for understanding the distribution, status, and ecology of snow leopards (Panthera uncia). However, the low DNA quantity and quality in many
noninvasive samples such as scats makes PCR amplification and genotyping challenging. We therefore designed primers for 9 microsatellites loci previously isolated in the
domestic cat (Felis catus) specifically for snow leopard studies using noninvasive samples. The loci showed moderate levels of variation in two Mongolian snow leopard
populations. Combined with seven other loci that we previously described, they have sufficient variation (He = 0.504, An = 3.6) for individual identification and
population structure analysis. We designed a species species specific PCR assay using cytochrome b for identification of unknown snow leopard samples. These molecular markers
facilitate in depth studies to assess distribution, abundance, population structure, and landscape connectivity of this endangered species.
endangered species
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Janecka, J. E., Jackson, R., Munkhtsog, B., Murphy, W. J. (2014). Characterization of 9 microsatellites and primers in snow leopards and a species-specific PCR assay for identifying noninvasive samples. Conservation Genetic Resource, 6(2), 369:373.
Abstract: Molecular markers that can effectively identify noninvasively collected samples and provide genetic
information are critical for understanding the distribution, status, and ecology of snow leopards (Panthera uncia). However, the low DNA quantity and quality in many
noninvasive samples such as scats makes PCR amplification and genotyping challenging. We therefore designed primers for 9 microsatellites loci previously isolated in the
domestic cat (Felis catus) specifically for snow leopard studies using noninvasive samples. The loci showed moderate levels of variation in two Mongolian snow leopard
populations. Combined with seven other loci that we previously described, they have sufficient variation (He = 0.504, An = 3.6) for individual identification and
population structure analysis. We designed a species species specific PCR assay using cytochrome b for identification of unknown snow leopard samples. These molecular markers
facilitate in depth studies to assess distribution, abundance, population structure, and landscape connectivity of this endangered species.
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Oli, M. K. (1993). A key for the identification of the hair of mammals of a snow leopard (Panthera uncia) habitat in Nepal. Journal of Zoology London, 231(1), 71–93.
Abstract: Analysis of prey remains in scats, particularly hairs, in widely used to study diet of mammalian predators, but identification of hair is often difficult because hair structures vary considerably both within and between species. Use of photographic reference of diagnostically important hair structures from mammals occurring in a predator's habitat has been found to be convenient for routine identification. A photographic reference key was developed for the identification of hairs of the mammals known to occur in a snow leopard (Panthera uncia) habitat in the Annapurna Conservation Area, Nepal. The key included a photographic reference of the diagnostic hair structures of nine species of wild and five species of domestic mammals. The cross-sectional appearance, shape and arrangement of medulla, the ratio of cortex to medulla, and the form and distribution of pigment in medulla and cortex were important diagnostic aids in the identification of hairs.
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Shrestha, B. (2008). Prey Abundance and Prey Selection by Snow Leopard (uncia uncia) in the Sagarmatha (Mt. Everest) National Park, Nepal.
Abstract: Predators have significant ecological impacts on the region's prey-predator dynamic and community structure through their numbers and prey selection. During April-December 2007, I conducted a research in Sagarmatha (Mt. Everest) National Park (SNP) to: i) explore population status and density of wild prey species; Himalayan tahr, musk deer and game birds, ii) investigate diet of the snow leopard and to estimate prey selection by snow leopard, iii) identify the pattern of livestock depredation by snow leopard, its mitigation, and raise awareness through outreach program, and identify the challenge and opportunities on conservation snow leopard and its co-existence with wild ungulates and the human using the areas of the SNP. Methodology of my research included vantage points and regular monitoring from trails for Himalayan tahr, fixed line transect with belt drive method for musk deer and game birds, and microscopic hair identification in snow leopard's scat to investigate diet of snow leopard and to estimate prey selection. Based on available evidence and witness accounts of snow leopard attack on livestock, the patterns of livestock depredation were assessed. I obtained 201 sighting of Himalayan tahr (1760 individuals) and estimated 293 populations in post-parturient period (April-June), 394 in birth period (July -October) and 195 November- December) in rutting period. In average, ratio of male to females was ranged from 0.34 to 0.79 and ratio of kid to female was 0.21-0.35, and yearling to kid was 0.21- 0.47. The encounter rate for musk deer was 1.06 and density was 17.28/km2. For Himalayan monal, the encounter rate was 2.14 and density was 35.66/km2. I obtained 12 sighting of snow cock comprising 69 individual in Gokyo. The ratio of male to female was 1.18 and young to female was 2.18. Twelve species (8 species of wild and 4 species of domestic livestock) were identified in the 120 snow leopard scats examined. In average, snow leopard predated most frequently on Himalayan tahr and it was detected in 26.5% relative frequency of occurrence while occurred in 36.66% of all scats, then it was followed by musk deer (19.87%), yak (12.65%), cow (12.04%), dog (10.24%), unidentified mammal (3.61%), woolly hare (3.01%), rat sp. (2.4%), unidentified bird sp. (1.8%), pika (1.2%), and shrew (0.6%) (Table 5.8 ). Wild species were present in 58.99% of scats whereas domestic livestock with dog were present in 40.95% of scats. Snow leopard predated most frequently on wildlife species in three seasons; spring (61.62%), autumn (61.11%) and winter (65.51%), and most frequently on domestic species including dog in summer season (54.54%). In term of relative biomass consumed, in average, Himalayan tahr was the most important prey species contributed 26.27% of the biomass consumed. This was followed by yak (22.13%), cow (21.06%), musk deer (11.32%), horse (10.53%), wooly hare (1.09%), rat (0.29%), pika (0.14%) and shrew (0.07%). In average, domestic livestock including dog were contributed more biomass in the diet of snow leopard comprising 60.8% of the biomass consumed whilst the wild life species comprising 39.19%. The annual prey consumption by a snow leopard (based on 2 kg/day) was estimated to be three Himalayan tahr, seven musk deer, five wooly hare, four rat sp., two pika, one shrew and four livestock. In the present study, the highest frequency of attack was found during April to June and lowest to July to November. The day of rainy and cloudy was the more vulnerable to livestock depredation. Snow leopard attacks occurred were the highest at near escape cover such as shrub land and cliff. Both predation pressure on tahr and that on livestock suggest that the development of effective conservation strategies for two threatened species (predator and prey) depends on resolving conflicts between people and predators. Recently, direct control of free – ranging livestock, good husbandry and compensation to shepherds may reduce snow leopard – human conflict. In long term solution, the reintroduction of blue sheep at the higher altitudes could also “buffer” predation on livestock.
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