Literature DB >> 30488535

Potential distribution of an invasive pest, Euplatypus parallelus, in China as predicted by Maxent.

Jihong Tang1, Jinhua Li2, Hui Lu1, Fuping Lu1, Baoqian Lu1.   

Abstract

BACKGROUND: Euplatypus parallelus is a highly polyphagous invasive pest native to Central and South America. In recent years it has invaded many countries in Africa and Asia and resulted in considerable economic loss. In China it has been reported to have invaded Taiwan, and been also recorded in Hainan Province. Until now there has been no invasion into the mainland. In order to better manage this invasive pest, here we predicted the suitable area of E. parallelus in China by the Maxent model.
RESULTS: The Maxent model predicted the potential distribution of E. parallelus with a test AUC value of 0.962 and a training AUC value of 0.978. Temperature seasonality (Bio_04), annual temperature range (Bio_07), annual precipitation (Bio_12) and mean temperature of the coldest quarter (Bio_11) were the strongest predictors of E. parallelus distribution with 32.1%, 19.8%, 15% and 10.4% contributions, respectively. The potential suitable area for E. parallelus was mainly distributed in the southeastern coast, the southwestern border, and Taiwan and Hainan provinces in China, and the highly suitable areas were located in the northern coast of Hainan Province and the southwestern coast of Taiwan Province. This pest prefers a stable, warm and rainy climate, which indicates that tropics and subtropics would be its ideal area.
CONCLUSION: Euplatypus parallelus has invaded Hainan and Taiwan in China. Measures should be taken to prevent it from spreading on these two islands. Moreover, strict quarantine, biological study and control measures are necessary to block its spread, invasion and damage, especially in these climate-suitable areas.
© 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Entities:  

Keywords:  Euplatypus parallelus; invasive pest; maximum entropy; potential distribution area

Mesh:

Year:  2019        PMID: 30488535     DOI: 10.1002/ps.5280

Source DB:  PubMed          Journal:  Pest Manag Sci        ISSN: 1526-498X            Impact factor:   4.845


  5 in total

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  5 in total

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