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利用最大熵模型预测三种潜在入侵性金龟在中国的潜在分布。

Using MaxEnt Model to Predict the Potential Distribution of Three Potentially Invasive Scarab Beetles in China.

作者信息

Wang Shuangyi, Lu Yuanyuan, Han Mengyang, Li Lulu, He Ping, Shi Aimin, Bai Ming

机构信息

College of Life Science, China West Normal University, Nanchong 637002, China.

Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.

出版信息

Insects. 2023 Feb 27;14(3):239. doi: 10.3390/insects14030239.

DOI:10.3390/insects14030239
PMID:36975924
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10054099/
Abstract

A hot topic in recent years is the prediction of the potential distribution of possible invasive insects. China is facing a great challenge due to invasive insects. Scarab beetles are a highly diverse group, and many of them are well-known invasive insects. Here, in order to prevent the invasion of scarab beetles in China, we screened the invasive insects globally and obtained a preliminary database of quarantine or invasive scarab beetles. From the obtained database, we selected the top five species (, , , and ) to discuss and analyzed the potential distribution of three species that have not invaded China by using the MaxEnt model. The prediction results show that every continent has potential distribution areas for these species. Specifically within China, and were mainly concentrated in east central regions and and were mainly distributed in the southwest areas, while has no suitable area. Notably, Yunnan, Hunan, Jiangxi and Zhejiang province had a high risk of invasion. In general, local agriculture, forestry and customs departments in China should pay more attention to monitoring for the prevention of infestation by invasive insects.

摘要

近年来的一个热门话题是对可能入侵昆虫潜在分布的预测。由于入侵昆虫,中国正面临巨大挑战。金龟子是一个高度多样化的类群,其中许多是著名的入侵昆虫。在此,为防止金龟子入侵中国,我们在全球范围内筛选入侵昆虫,获得了一份检疫或入侵金龟子的初步数据库。从所获数据库中,我们挑选出排名前五的物种(、、、和),利用最大熵模型对三种尚未入侵中国的物种的潜在分布进行讨论和分析。预测结果表明,各大洲均有这些物种的潜在分布区域。具体在中国境内,和主要集中在中东部地区,和主要分布在西南地区,而没有适宜区域。值得注意的是,云南、湖南、江西和浙江省入侵风险较高。总体而言,中国当地农业、林业和海关部门应更加重视监测,以防入侵昆虫侵扰。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c970/10054099/f2d0ae3ba00b/insects-14-00239-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c970/10054099/6890fff72ea9/insects-14-00239-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c970/10054099/e54cb8c2b286/insects-14-00239-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c970/10054099/f2d0ae3ba00b/insects-14-00239-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c970/10054099/6890fff72ea9/insects-14-00239-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c970/10054099/e54cb8c2b286/insects-14-00239-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c970/10054099/f2d0ae3ba00b/insects-14-00239-g003.jpg

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