SCIENTIFIC REPORTS - Interactive spatial scale effects on species distribution modeling: The case of the giant panda

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October 10, 2019 - Author: Thomas Connor, Andrés Viña, Julie A. Winkler, , Ying Tang, Ashton Shortridge, , , , , Zejun Zhang, Caiquan Zhou, Wenke Bai & Jianguo Liu

Scientific Reports

DOI: 10.1038/s41598-019-50953-z

Research has shown that varying spatial scale through the selection of the total extent of investigation and the grain size of environmental predictor variables has effects on species distribution model (SDM) results and accuracy, but there has been minimal investigation into the interactive effects of extent and grain. To do this, we used a consistently sampled range-wide dataset of giant panda occurrence across southwest China and modeled their habitat and distribution at 4 extents and 7 grain sizes. We found that increasing grain size reduced model accuracy at the smallest extent, but that increasing extent negated this effect. Increasing extent also generally increased model accuracy, but the models built at the second-largest (mountain range) extent were more accurate than those built at the largest, geographic range-wide extent. When predicting habitat suitability in the smallest nested extents(50 km2), we found that the models built at the next-largest extent (500 km2) were more accurate than the smallest-extent models but that further increases in extent resulted in large decreases in accuracy. Overall, this study highlights the impacts of the selection of spatial scale when evaluating species’ habitat and distributions, and we suggest more explicit investigations of scale effects in future modeling efforts.

 

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Authors

Andres Vina

Andres Vina
vina@msu.edu

Vanessa Hull

Vanessa Hull
hullvane@gmail.com

Hongbo Yang

Hongbo Yang
517-775-0215
yanghongbo01@gmail.com

Jindong Zhang

Jindong Zhang

Zhiqiang Zhao

Zhiqiang Zhao
zhaozq@msu.edu

Fang Wang

Fang Wang
wangfa15@msu.edu

Jianguo

Jianguo "Jack" Liu
517-432-5025
liuji@msu.edu


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