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Author (up) Atzeni, L., Cushman, S. A., Bai, D., Wang, J., Chen, P., Shi, K., Riordan, P. url  openurl
  Title Meta-replication, sampling bias, and multi-scale model selection: A case study on snow leopard (Panthera uncia) in western China. Type Journal Article
  Year 2020 Publication Ecology and Evolution Abbreviated Journal  
  Volume Issue Pages 1-27  
  Keywords MaxEnt, meta-replication, multi-scale, Panthera uncia, sampling bias, scale selection, snow leopard, species distribution model  
  Abstract 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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  Area Expedition Conference  
  Notes Approved no  
  Call Number Serial 1616  
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