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Mapping the Spatio-Temporal Distribution of Fall Armyworm in China by Coupling Multi-Factors.

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Title: Mapping the Spatio-Temporal Distribution of Fall Armyworm in China by Coupling Multi-Factors.
Authors: Huang, Yanru1,2,3 (AUTHOR), Lv, Hua4 (AUTHOR), Dong, Yingying1,2,3 (AUTHOR), Huang, Wenjiang1,2,3 (AUTHOR) huangwj@aircas.ac.cn, Hu, Gao4 (AUTHOR), Liu, Yang5 (AUTHOR), Chen, Hui4 (AUTHOR), Geng, Yun1,2,3 (AUTHOR), Bai, Jie3,6 (AUTHOR), Guo, Peng7 (AUTHOR), Cui, Yifeng3,8 (AUTHOR)
Source: Remote Sensing. Sep2022, Vol. 14 Issue 17, p4415. 19p.
Subjects: Fall armyworm, Integrated pest control, Plant phenology, Pest control, Host plants, Remote sensing
Geographic Terms: China
Abstract: The fall armyworm (FAW) (Spodoptera frugiperda) (J. E. Smith) is a migratory pest that lacks diapause and has raised widespread concern in recent years due to its global dispersal and infestation. Seasonal environmental changes lead to its large-scale seasonal activities, and quantitative simulations of its dispersal patterns and spatiotemporal distribution facilitate integrated pest management. Based on remote sensing data and meteorological assimilation products, we constructed a mechanistic model of the dynamic distribution of FAW (FAW-DDM) by integrating weather-driven flight of FAW with host plant phenology and environmental suitability. The potential distribution of FAW in China from February to August 2020 was simulated. The results showed a significant linear relationship between the dates of the first simulated invasion and the first observed invasion of FAW in 125 cities (R2 = 0.623; p < 0.001). From February to April, FAW was distributed in the Southwestern and Southern Mountain maize regions mainly due to environmental influences. From May to June, FAW spread rapidly, and reached the Huanghuaihai and North China maize regions between June to August. Our results can help in developing pest prevention and control strategies with data on specific times and locations, reducing the impact of FAW on food security. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Mapping the Spatio-Temporal Distribution of Fall Armyworm in China by Coupling Multi-Factors.
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  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22Remote+Sensing%22&quot;&gt;Remote Sensing&lt;/searchLink&gt;. Sep2022, Vol. 14 Issue 17, p4415. 19p.
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  Data: The fall armyworm (FAW) (Spodoptera frugiperda) (J. E. Smith) is a migratory pest that lacks diapause and has raised widespread concern in recent years due to its global dispersal and infestation. Seasonal environmental changes lead to its large-scale seasonal activities, and quantitative simulations of its dispersal patterns and spatiotemporal distribution facilitate integrated pest management. Based on remote sensing data and meteorological assimilation products, we constructed a mechanistic model of the dynamic distribution of FAW (FAW-DDM) by integrating weather-driven flight of FAW with host plant phenology and environmental suitability. The potential distribution of FAW in China from February to August 2020 was simulated. The results showed a significant linear relationship between the dates of the first simulated invasion and the first observed invasion of FAW in 125 cities (R2 = 0.623; p &lt; 0.001). From February to April, FAW was distributed in the Southwestern and Southern Mountain maize regions mainly due to environmental influences. From May to June, FAW spread rapidly, and reached the Huanghuaihai and North China maize regions between June to August. Our results can help in developing pest prevention and control strategies with data on specific times and locations, reducing the impact of FAW on food security. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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        Value: 10.3390/rs14174415
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      – Code: eng
        Text: English
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        PageCount: 19
        StartPage: 4415
    Subjects:
      – SubjectFull: Fall armyworm
        Type: general
      – SubjectFull: Integrated pest control
        Type: general
      – SubjectFull: Plant phenology
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      – SubjectFull: Pest control
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      – SubjectFull: Host plants
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      – SubjectFull: Remote sensing
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      – SubjectFull: China
        Type: general
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      – TitleFull: Mapping the Spatio-Temporal Distribution of Fall Armyworm in China by Coupling Multi-Factors.
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              Text: Sep2022
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