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

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 (R-2 = 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.

Automated summary

This study constructed a mechanistic model of the dynamic distribution of fall armyworm (FAW) and simulated its potential distribution in China from February to August 2020. The results showed a significant linear relationship between the dates of the first simulated invasion and the first observed invasion of FAW. From February to April, FAW was mainly distributed in the Southwestern and Southern Mountain maize regions, while it rapidly spread and reached the Huanghuaihai and North China maize regions from May to June.