Potential effects of climate change on geographic distribution of the [PDF]

Mar 8, 2017 - This study, using species distribution modeling (involving a new approach that allows for uncertainty), pr

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Article | OPEN

Cindy Q. Tang

, Yi-Fei Dong, Sonia Herrando-Moraira, Tetsuya Matsui, Haruka Ohashi, Long-Yuan He, Katsuhiro Nakao, Nobuyuki Tanaka, Mizuki

Tomita, Xiao-Shuang Li, Hai-Zhong Yan, Ming-Chun Peng

, Jun Hu, Ruo-Han Yang, Wang-Jun Li, Kai Yan, Xiuli Hou, Zhi-Ying Zhang & Jordi López-

Pujol Scientific Reports 7, Article number: 43822 (2017)

Received: 22

doi:10.1038/srep43822

August 2016

Download Citation

Accepted: 01

Climate-change ecology Plant sciences

February 2017 Published online: 08 March 2017

(A) An inflorescence with two showy white bracts of D. involucrata (Photograph by Shi-Liu Wang). (B) Fresh fruits with autumn foliage D. involucrata (Photograph by Cindy Q. Tang). (C) A forest of D. involucrata at ca. 1480 m in Longcanggou, Sichuan (Photograph by Jun Hu).

(A) Provinces of China. Ch = Chongqing. (B) The spatial distribution pattern of forests containing D. involucrata as one of the dominants. Purple lines: national boundaries between China and India (at issue). Maps were generated using the software ArcGIS v. 9.3.

(A) A “standard” model for the present time period is obtained by averaging the multiple runs (20 in our case) from the cross-validation (or from another sampling technique, e.g. subsample); (B) a map showing the variability in the predicted suitable areas among all generated models (20) from the cross-validation (“uncertainty” map); (C) A “refined” map is obtained by removing the pixels that are forecast by

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