Bark beetles have been recognized as the main insects that threaten forests worldwide. Several years of research related to evaluating the potential establishment of beetles have yielded widespread recognition of the usefulness of cluster analysis or species distribution models (SDMs) in predicting which species present a high risk of invasion. It is necessary to integrate current practices to quantitatively estimate the risk of establishment.This article analyzes global occurrence data of bark beetles using ‘SOM (self-organizing mapping) + MaxEnt’ to generate the list of high-risk species based on an SOM index and ranges of suitable distribution. All selected countries were clustered into nine clusters to discover which countries have similar bark beetles assemblages. A list of species considering potential threats that were absent from some countries was generated, and Hylurgus ligniperda and Scolytus multistriatus have a relatively high risk of establishment in China. Moreover, MaxEnt were used to analyze the potential geographic areas that species may be invaded. The results indicated that suitable regions of H. ligniperda are distributed in North America, Europe, the Middle East, Central Asia, and the southwest part of China. In addition, S. multistriatus has limited distribution on the Chinese mainland.The integration of SOM and MaxEnt provides a valuable reference for identifying potentially threatening invaders, and assessing the establishment risk for biological invasion, which provide the basis for forest management measures.
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1 July 2019
Assessing the invasive risk of bark beetles (Curculionidae: Scolytinae and Platypodinae)
Yanxue Yu,
Zhihao Chi,
Junhua Zhang,
Peishan Sun,
Cong Wang,
Xubin Pan
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bark beetle
biological invasion
self-organizing mapping
species distribution model