Temporal analyses of global suitability distribution for fall armyworm based on Multiple factors

Le résumé fourni par la source

• Monthly models reveal seasonal shifts in global Fall Armyworm suitability. • Remote sensing data enhances real-time monitoring of pest distribution. • Differentiating records improves the precision of suitable area identification. • Integrating static and dynamic factors is vital for accurate distribution modeling. • Findings support proactive pest control strategies aligned with seasonal changes. The fall armyworm (FAW; Spodoptera frugiperda) has been a persistent threat to global food security due to its strong migratory ability and wide range of host plants. However, most current studies on the suitability distribution of FAW focus on extracting suitable areas in specific regions on an annual basis. Consequently, research on the suitability distribution of FAW at a larger scale and with higher temporal resolution is urgently needed to provide data support for early prevention and control. This study differentiated the historical occurrence records of FAW into annual distribution points and seasonal distribution points. By integrating multi-factor environmental data, including climate, soil, topography, and vegetation, we used MaxEnt to establish annual and monthly models. The annual model extracted the annual suitability distribution of FAW worldwide. Among the nine selected environmental factors, temperature seasonality had the greatest impact on the suitability distribution of FAW, with a single-factor contribution rate of 39.87%. The monthly models analyzed the inter-monthly variations in the global suitability distribution of FAW from January to December. The results indicated that FAW’s suitability was highest in July and lowest in March. Under the dominant influence of dynamic environmental factors such as temperature, precipitation, and vegetation index, the expansion and contraction of FAW’s suitability distribution corresponded with seasonal changes, exhibiting significant seasonal fluctuations. Our results can provide FAW control personnel with more practical references for formulating preventive strategies in advance, helping to prevent the potentially incalculable damage FAW could cause to crops in invaded areas.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.