Modelling potential distribution of Tuta absoluta in China under climate change using CLIMEX and MaxEnt
The Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) originated in South America and is a major pest of the economically critical solanaceous crops. It is devastating to tomatoes, attacking mainly the leaves, stems, flowers and fruits of tomato plants, and can cause up to 100% damage. T. absoluta...
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Published in: | Journal of applied entomology (1986) Vol. 147; no. 10; pp. 895 - 907 |
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Main Authors: | , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Berlin
Wiley Subscription Services, Inc
01-12-2023
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Subjects: | |
Online Access: | Get full text |
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Summary: | The Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) originated in South America and is a major pest of the economically critical solanaceous crops. It is devastating to tomatoes, attacking mainly the leaves, stems, flowers and fruits of tomato plants, and can cause up to 100% damage. T. absoluta invaded China in 2017 and expanded rapidly, severely impacting the tomato industry. To illustrate the detailed potential distribution of T. absoluta in China, we used CLIMEX and MaxEnt models to predict the potential distribution of this pest using historical and future climate data. CLIMEX predicts a wider potential distribution area for T. absoluta in China than MaxEnt, which suggests that most of China is suitable for its distribution, except for the Tarim Basin in southern Xinjiang, western Inner Mongolia and northwestern Gansu. Both models accurately predicted the known distribution of T. absoluta in the provinces of Yunnan and Guangxi, and the predictions by both models suggest the total distribution range of T. absoluta in China is to increase slightly with future changes in climate temperature. These predictions will help understand the influence of climate change on the potential distribution of T. absoluta in China and thus provide a theoretical foundation for developing early monitoring, quarantine and control strategies. |
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ISSN: | 0931-2048 1439-0418 |
DOI: | 10.1111/jen.13181 |