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Islam, M., Sahana, M., Areendran, G., Jamir, C., Raj, K., Sajjad, H. |
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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 |
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2023 |
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Geo: Geography and Environment |
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10 |
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e00121 |
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1-15 |
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bioclimatic variables, habitat suitability, MaxEnt model, niche overlap, western Himalayan region |
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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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SLN @ rakhee @ |
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1719 |
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Singh, R., Krausman, P. R., Pandey, P., Maheshwari, A., Rawal,
R. S., Sharma, S., Shekhar, S. |
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Title |
Predicting Habitat Suitability of Snow Leopards in the Western
Himalayan Mountains, India |
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Journal Article |
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Year |
2020 |
Publication |
Biology bulletin |
Abbreviated Journal |
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47 |
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6 |
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655-664 |
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biogeographic distribution, climate, endangered cat, MaxEnt, snow leopard |
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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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1629 |
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Thapa, K., Schmitt, N., Pradhan, N. M. B., Acharya, H. R., Rayamajhi, S. |
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No silver bullet? Snow leopard prey selection in Mt. Kangchenjunga, Nepal |
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2021 |
Publication |
Ecology and Evolution |
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1-13 |
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blue sheep, common leopard, fecal, genetic analysis, snow leopard, wolf, yak |
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In this study, we investigated the impact of domestic and wild prey availability on snow leopard prey preference in the Kangchenjunga Conservation Area of eastern Nepal-a region where small domestic livestock are absent and small wild ungulate prey are present. We took a comprehensive approach that combined fecal genetic sampling, macro- and microscopic analyses of snow leopard diets, and direct observation of blue sheep and livestock in the KCA. Out of the collected 88 putative snow leopard scat samples from 140 transects (290km) in 27 (4x4km2) sampling grid cells, 73 (83%) were confirmed to be from snow leopard. The genetic analysis accounted for 19 individual snow leopards (10 males and 9 females), with a mean population size estimate of 24 (95% CI: 19-29) and an average density of 3.9 snow leopards/100km2 within 609km2. The total available prey biomass of blue sheep and yak was estimated at 355,236 kg (505 kg yak/km2 and 78kg blue sheep/km2). From the available prey biomass, we estimated snow leopards consumed 7% annually, which comprised wild prey (49%), domestic livestock (45%). and 6% unidentified items. the estimated 47,736 kg blue sheep biomass gives a snow leopard-to-blue sheep ratio of 1:59 on a weight basis. The high preference of snow leopard to domestic livestock appears to be influenced by a much smaller available biomass of wild prey then in other regions of Nepal (e.g., 78kg/km2 in the KCA compared with a range of 200-300 kg/km2 in other regions of Nepal?. Along with livestock insurance scheme improvement, there needs to be a focus on improved livestock guarding, predator-proof corrals as well as engaging and educating local people to be citizen scientists on the importance of snow leopard conservation, involving them in long-term monitoring programs and promotion of ecotourism. |
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1665 |
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Thapa, K., Jackson, R., Gurung, L, Acharya, H. B., Gurung, R. K., |
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Applying the double observer methodology for assessing blue sheep population size in Nar Phu valley, Annapurna Conservation Area, Nepal |
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2021 |
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Wildlife Biology |
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1-11 |
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blue sheep, density estimation, double observer counts, Nepal, Panthera uncia, prey abundance, Pseudois nayaur, snow leopard, viewshed mapping |
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This study was undertaken in spring, 2019 to assess the applicability of the double-observer survey method for estimating blue sheep Pseudois nayaur abundance in Nar-Phu valley of Manang District located in Annapurna Conservation Area of northern Nepal. Since counting large mammals in rugged mountain habitat poses a special challenge, we tested the efficacy of the double observer method for generating robust population estimates for this important protected area. The overall detection probability for observers (O1 and O2) was 0.94 and 0.91 for a total of 106 groups comprised of 2059 individual blue sheep. We estimated the area’s blue sheep population at 2070 (SE ± 168.77; 95% CI 2059–2405) for the 246.2 km2 of sampled habitat. We determined blue sheep to be widely distributed within the study area with a mean density of 8.4 individuals per km2 based on a total study area of 246.2 km2. We discuss demographic population structure and identify limitations when applying the double observer approach, along with recommending viewshed mapping for ensuring more robust density estimates of mountain-dwelling ungulates like blue sheep or ibex that inhabit extremely heterogeneous terrain which strongly influences sighting distances and overall animal detection rates. |
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1666 |
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Johansson, O., Agvaantseren, B., Jackson, R., Kachel, S., Kubanychbekov, Z., McCarthy, T., Mishra, C., Ostrowski, S., Kulenbekov, R., Rajabi, A. M., Subba, S. |
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Body measurements of free-ranging snow leopards across their range |
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2022 |
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Snow Leopard Reports |
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1 |
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1-6 |
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Body mass, body size, carnivore, morphology, Panthera uncia |
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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. |
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1711 |
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Feng, X., Peng, Q., Chen, Y., Li, W. |
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A Case Study of the Snow Leopard in Sanjiangyuan National Park Boundaries regarding Park Boundary Divergence |
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2022 |
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Land |
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11 |
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813 |
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1-15 |
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boundary divergence; national park; global warming; snow leopard; Sanjiangyuan National Park |
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This paper uses remote sensing data from the Sanjiangyuan National Park (SNP) to explore the divergence between the boundaries of national parks and the distribution of natural habitats. Results are used to argue that these discrepancies evolve along with the potential impact of global warming. Using the example of the habitat change of snow leopards and the conflicts between local people and snow leopards, we reflect on the consequences of this divergence. Results show that divergence between the political boundaries and natural habitats as well as the consequent influence on the living conditions of local people are strikingly visible, and the effects of global warming on such conflicts are apparent. The authors conclude that both notions of ‘political boundaries’ and ‘natural habitats’ are expected to come together as the SNP region is spatially configured, while ‘global warming’ seems to be relevant as an essential reference when delimiting the region in the future. Finally, the proposal for the establishment of cooperative conservation areas is presented,
emphasizing the role of cooperative governance in/around national parks. |
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1687 |
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Sharma, K., Fiechter, M., George, T., Young, J., Alexander, J.
S., Bijoor, Suryawanshi, K., Mishra, C. |
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Conservation and people: Towards an ethical code of conduct for
the use of camera traps in wildlife research |
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2020 |
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Ecological Solutions and Evidence |
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camera trap, code of conduct, ethics, human rights, law, PARTNERS principles for community- based conservation, privacy, snow leopard |
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1. Camera trapping is a widely employed tool in wildlife
research, used to estimate animal abundances, understand animal
movement, assess species richness and under- stand animal behaviour. In
addition to images of wild animals, research cameras often record human
images, inadvertently capturing behaviours ranging from innocuous
actions to potentially serious crimes.
2. With the increasing use of camera traps, there is an urgent need to
reflect on how researchers should deal with human images caught on
cameras. On the one hand, it is important to respect the privacy of
individuals caught on cameras, while, on the other hand, there is a
larger public duty to report illegal activity. This creates ethical
dilemmas for researchers.
3. Here, based on our camera-trap research on snow leopards Panthera
uncia, we outline a general code of conduct to help improve the practice
of camera trap based research and help researchers better navigate the
ethical-legal tightrope of this important research tool. |
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1626 |
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Koju. N. P, , Bashyal, B., Pandey, B. P., Shah, S. N., Thami, S. ,Bleisch, W. V. |
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Title |
First camera-trap record of the snow leopard Panthera uncia in Gaurishankar Conservation Area, Nepal |
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2020 |
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Oryx |
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1-4 |
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Camera trap, corridor, Gaurishankar Conser- vation Area, Nepal, Panthera uncia, prey abundance, transboundary, snow leopard |
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The snow leopard Panthera uncia is the flagship species of the high mountains of the Himalayas. There is po- tentially continuous habitat for the snow leopard along the northern border of Nepal, but there is a gap in information about the snow leopard in Gaurishankar Conservation Area. Previous spatial analysis has suggested that the Lamabagar area in this Conservation Area could serve as a transbound- ary corridor for snow leopards, and that the area may con- nect local populations, creating a metapopulation. However, there has been no visual confirmation of the species in Lamabagar. We set !! infrared camera traps for " months in Lapchi Village of Gaurishankar Conservation Area, where blue sheep Pseudois nayaur, musk deer Moschus leucogaster and Himalayan tahr Hemitragus jemlahicus, all snow leopard prey species, had been observed. In November #$!% at &,!$$ m, ' km south-west of Lapchi Village, one camera recorded three images of a snow leopard, the first photographic evidence of the species in the Conservation Area. Sixteen other species of mammals were also recorded. Camera-trap records and sightings indicated a high abun- dance of Himalayan tahr, blue sheep and musk deer. Lapchi Village may be a potentially important corridor for snow leopard movement between the east and west of Nepal and northwards to Quomolongma National Park in China. However, plans for development in the region present in- creasing threats to this corridor. We recommend develop- ment of a transboundary conservation strategy for snow leopard conservation in this region, with participation of Nepal, China and international agencies. |
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1622 |
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Durbach, I., Borchers, D., Sutherland, C., Sharma, K. |
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Fast, flexible alternatives to regular grid designs for spatial
capture–recapture. |
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2020 |
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Methods in Ecology and Evolution |
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1-13 |
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camera trap, population ecology,sampling, spatial capture-recapture, surveys |
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Spatial capture–recapture (SCR) methods use the location of
detectors (camera traps, hair snares and live-capture traps) and the
locations at which animals were detected (their spatial capture
histories) to estimate animal density. Despite the often large expense
and effort involved in placing detectors in a landscape, there has been
relatively little work on how detectors should be located. A natural
criterion is to place traps so as to maximize the precision of density
estimators, but the lack of a closed-form expression for precision has
made optimizing this criterion computationally demanding. 2. Recent
results by Efford and Boulanger (2019) show that precision can be well
approximated by a function of the expected number of detected
individuals and expected number of recapture events, both of which can
be evaluated at low computational cost. We use these results to develop
a method for obtaining survey designs that optimize this approximate
precision for SCR studies using count or binary proximity detectors, or
multi-catch traps. 3. We show how the basic design protocol can be
extended to incorporate spatially varying distributions of activity
centres and animal detectability. We illustrate our approach by
simulating from a camera trap study of snow leopards in Mongolia and
comparing estimates from our designs to those generated by regular or
optimized grid designs. Optimizing detector placement increased the
number of detected individuals and recaptures, but this did not always
lead to more precise density estimators due to less precise estimation
of the effective sampling area. In most cases, the precision of density
estimators was comparable to that obtained with grid designs, with
improvement in some scenarios where approximate CV(¬D) < 20% and density
varied spatially. 4. Designs generated using our approach are
transparent and statistically grounded. They can be produced for survey
regions of any shape, adapt to known information about animal density
and detectability, and are potentially easier and less costly to
implement. We recommend their use as good, flexible candidate designs
for SCR surveys when reasonable knowledge of model parameters exists. We
provide software for researchers to construct their own designs, in the
form of updates to design functions in the r package oSCR. |
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1618 |
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Oberosler, V., Tenan, S., Groff, C., Krofel, M., Augugliaro, C., Munkhtsog, B., Rovero, F. |
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First spatially‐explicit density estimate for a snow leopard population in the Altai Mountains |
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2021 |
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Biodiversity and Conservation |
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15 |
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Camera trapping · Conservation · Abundance · Felids · Activity range · Mongolia · Panthera uncia · Spatial capture-recapture |
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The snow leopard Panthera uncia is an elusive and globally-threatened apex predator occurring in the mountain ranges of central Asia. As with other large carnivores, gaps in data on its distribution and abundance still persist. Moreover, available density estimates are often based on inadequate sampling designs or analytical approaches. Here, we used camera trapping across a vast mountainous area (area of the sampling frame 850 km2; analysed habitat extent 2600 km2) and spatially-explicit capture-recapture (SECR) models to provide, to our knowledge, the first robust snow leopard population density estimate for the Altai Mountains. This region is considered one of the most important conservation areas for snow leopards, representing a vast portion of suitable habitat and a key ecological corridor. We also provide estimates of the scale parameter (σ) that reflects ranging behaviour (activity range) and baseline encounter probability, and investigated potential drivers of density and related parameters by assessing their associations with anthropogenic and environmental factors. Sampling yielded 9729 images of snow leopards corresponding to 224 independent detections that belonged to a minimum of 23 identified adult individuals. SECR analysis resulted in an overall density of 1.31 individuals/100 km2 (1.15%–1.50 95% CI), which was positively correlated with terrain slope. This estimate falls within the mid-values of the range of density estimates for the species globally. We estimated significantly different activity range size for females and males (79 and 329 km2, respectively). Base- line encounter probability was negatively associated with anthropogenic activity. Our study contributes to on-going efforts to produce robust global estimates of population abundance for this top carnivore. |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
SLN @ rakhee @ |
Serial |
1662 |
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