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Atzeni, L., Cushman, S. A., Bai, D., Wang, J., Chen, P., Shi,
K., Riordan, P. |
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Title  |
Meta-replication, sampling bias, and multi-scale model selection:
A case study on snow leopard (Panthera uncia) in western China. |
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Journal Article |
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2020 |
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Ecology and Evolution |
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1-27 |
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MaxEnt, meta-replication, multi-scale, Panthera uncia, sampling bias, scale selection, snow leopard, species distribution model |
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Replicated multiple scale species distribution models (SDMs)
have become increasingly important to identify the correct variables
determining species distribution and their influences on ecological
responses. This study explores multi-scale habitat relationships of the
snow leopard (Panthera uncia) in two study areas on the Qinghai–Tibetan
Plateau of western China. Our primary objectives were to evaluate the
degree to which snow leopard habitat relationships, expressed by
predictors, scales of response, and magnitude of effects, were
consistent across study areas or locally landcape-specific. We coupled
univariate scale optimization and the maximum entropy algorithm to
produce multivariate SDMs, inferring the relative suitability for the
species by ensembling top performing models. We optimized the SDMs based
on average omission rate across the top models and ensembles’ overlap
with a simulated reference model. Comparison of SDMs in the two study
areas highlighted landscape-specific responses to limiting factors.
These were dependent on the effects of the hydrological network,
anthropogenic features, topographic complexity, and the heterogeneity of
the landcover patch mosaic. Overall, even accounting for specific local
differences, we found general landscape attributes associated with snow
leopard ecological requirements, consisting of a positive association
with uplands and ridges, aggregated low-contrast landscapes, and large
extents of grassy and herbaceous vegetation. As a means to evaluate the
performance of two bias correction methods, we explored their effects on
three datasets showing a range of bias intensities. The performance of
corrections depends on the bias intensity; however, density kernels
offered a reliable correction strategy under all circumstances. This
study reveals the multi-scale response of snow leopards to environmental
attributes and confirms the role of meta-replicated study designs for
the identification of spatially varying limiting factors. Furthermore,
this study makes important contributions to the ongoing discussion about
the best approaches for sampling bias correction. |
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1616 |
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Alexander, J. S., Shi, K., Tallents, L. A., Riordan, P. |
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Title |
On the high trail: examining determinants of site use by the Endangered snow leopard Panthera uncia in Qilianshan, China |
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Journal Article |
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Year |
2015 |
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Oryx |
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Fauna & Flora International |
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1-8 |
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Camera Trap, China, Detection Probability, Occupancy Modelling, Panthera Uncia, Site use, Snow Leopard |
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Abstract There is a need for simple and robust techniques for assessment and monitoring of populations of the Endangered snow leopard Panthera uncia to inform the de- velopment of action plans for snow leopard conservation. We explored the use of occupancy modelling to evaluate the influence of environmental and anthropogenic features on snow leopard site-use patterns. We conducted a camera trap survey across  km in Gansu Province, China, and used data from  camera traps to estimate probabilities of site use and detection using the single season occupancy model. We assessed the influence of three covariates on site use by snow leopards: elevation, the presence of blue sheep Pseudois nayaur and the presence of human disturb- ance (distance to roads). We recorded  captures of snow leopards over , trap-days, representing a mean capture success of . captures per  trap-days. Elevation had the strongest influence on site use, with the probability of site use increasing with altitude, whereas the influence of presence of prey and distance to roads was relatively weak. Our findings indicate the need for practical and robust tech- niques to appraise determinants of site use by snow leo- pards, especially in the context of the limited resources available for such work. |
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SLN @ rakhee @ |
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1433 |
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Alexander, J., S., Gopalaswamy, A., M., Shi, K., Hughes, J., Riordan, P. |
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Title |
Patterns of Snow Leopard Site Use in an Increasingly Human-Dominated Landscape |
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2016 |
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PLoS ONE |
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1-15 |
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Human population growth and concomitant increases in demand for natural resources pose threats to many wildlife populations. The landscapes used by the endangered snow leopard (Panthera uncia) and their prey is increasingly subject to major changes in land use. We aimed to assess the influence of 1) key human activities, as indicated by the presence of mining and livestock herding, and 2) the presence of a key prey species, the blue sheep (Pseudois nayaur), on probability of snow leopard site use across the landscape. In Gansu Province, China, we conducted sign surveys in 49 grid cells, each of 16 km2 in size, within a larger area of 3392 km2. We analysed the data using likelihood-based habitat occupancy models that explicitly account for imperfect detection and spatial auto-correlation between survey transect segments. The model-averaged estimate of snow leopard occupancy was high [0.75 (SE 0.10)], but only marginally higher than the naïve estimate (0.67). Snow leop- ard segment-level probability of detection, given occupancy on a 500 m spatial replicate, was also high [0.68 (SE 0.08)]. Prey presence was the main determinant of snow leopard site use, while human disturbances, in the form of mining and herding, had low predictive power. These findings suggest that snow leopards continue to use areas very close to such disturbances, as long as there is sufficient prey. Improved knowledge about the effect of human activity on large carnivores, which require large areas and intact prey populations, is urgently needed for conservation planning at the local and global levels. We highlight a number of methodological considerations that should guide the design of such research. |
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1440 |
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Shi, K.; Jun, Z.F.S.; Zhigang, D.; Riordan, P.; MacDonald, D. |
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Reconfirmation of snow leopards in Taxkurgan Nature Reserve, Xinjiang, China |
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2009 |
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Oryx |
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43 |
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2 |
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169-170 |
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administration; Beijing; China; conservation; global; habitat; management; nature; presence; province; range; research; reserve; snow-leopard; snow-leopards; snow leopard; snow leopards; species; uncia; wildlife; Xinjiang |
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China may hold a greater proportion of the global snow leopard Panthera uncia population than any other country, with the area of good quality suitable habitat, estimated at nearly 300,000 km2, comprising .50% of that available across the species' entire range. We can now reconfirm the presence of snow leopard in the Taxkurgan area of Xinjiang Province in north-west China after a period of 20 years. |
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Fauna & Flora International |
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United Kingdom |
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Notes |
SHI KUN Institute of Wildlife Conservation and Management, Beijing Forestry University, China ZHU FUDE SHI JUN and DAI ZHIGANG Xinjiang Forestry Administration, China PHILIP RIORDAN and DAVID MACDONALD Wildlife Conservation Research Unit, Department of Zoology, University of Oxford, Tubney House, Abingdon Road, Tubney, Abingdon, OX13 5QL, UK. E-mail philip.riordan@zoo.ox.ac.uk |
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SLN @ rana @ 1056 |
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884 |
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Riordan, P. |
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Title |
Unsupervised recognition of individual tigers and snow leopards from their footprints |
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Miscellaneous |
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1998 |
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Animal Conservation |
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1 |
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253-262 |
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captive; panthera tigris; panthera uncia; snow leopard; techniques; tiger |
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This study presents the testing of two unsupervised classification methods for their ability to accurately identify unknown individual tigers, Panthera tigris, and snow leopards, Panthera uncia, from their footprints. A neural-network based method, the Kohonen self-organizing map (SOM), and a Bayesian method, AutoClass, were assessed using hind footprints taken from captive animals under standardized conditions. AutoClass successfully discriminated individuals of both species from their footprints. Classification accuracy was greatest for tigers, with more misclassification of individuals occurring for snow leopards. Examination of variable influence on class formations failed to identify consistently influential measurements for either species. The self-organizing map did not provide accurate classification of individuals for either species. Results were not substantially improved by altering map dimensions nor by using principal components derived from the original data. The interpretation of resulting classifications and the importance of using such techniques in the study of wild animal populations are discussed. The need for further testing in the field is highlighted. |
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SLN @ rana @ 896 |
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823 |
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