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[Prediction of potential suitable distribution area of Flaveria bidentis in China based on niche models].

Authors: Xiang-feng, Cao; Guo-liang, Qian; Bai-shi, Hu; Feng-quan, Liu;

[Prediction of potential suitable distribution area of Flaveria bidentis in China based on niche models].

Abstract

Based on the distribution records of Flaveria bidentis in China, and by using five ecological niche models (GARP, Maxent, ENFA, Bioclim, and Domain), 32 eco-geographical variables were chosen to simulate the potential suitable distribution area of F. bidentis in the country, and the simulation precision of the models was assessed by the method of Receiver Operating Characteristic (ROC) curve analysis. Among the models adopted, Maxent model had the best simulation precision. Its prediction showed that the potential suitable distribution area of F. bidenti in this country accounted for 7. 5% of the total, with the central and southern Hebei, Beijing, Tianjin, Henan, Shandong, Anhui, and Jiangsu having high potential invasion risk.

Related Organizations
Keywords

China, Flaveria, Geography, Biodiversity, Models, Biological, Ecosystem, Forecasting

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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