
Abstract Invasive alien species can significantly impact the environment, public health, and food production. Identifying high-risk areas is essential for implementing preventive measures, especially for species with several traits linked to invasive behavior, such as Spodoptera litura (F.). This study aimed to predict the potential global distribution of S. litura and assess its implications for five major crops in Brazil. Climatic suitability was estimated using the MaxEnt correlative algorithm, with fifty models generated by varying feature classes and regularization multiplier values. The best model selected based on the corrected Akaike Information Criterion demonstrated strong predictive performance, with high Area Under the Curve (AUC train = 0.92, AUC test = 0.86) and Continuous Boyce Index (CBI train = 0.95, CBI test = 0.75) values. Predictions identified highly and moderately suitable areas for S. litura across all continents, including regions where the species has not yet been recorded, such as the Neotropics. In Brazil, highly suitable areas include the mid-west, northeastern coast, and the southeastern and southern regions. Among the assessed crops, citrus (97.2%) had the greatest overlap with the suitable range for S. litura , followed by rice (94.2%), coffee (90.3%), and soybean (72.8%). These findings suggest that S. litura could cause significant economic damage if introduced and spread in Brazil. The results of this study can inform the development of preventive measures against the introduction and spread of this important agricultural pest, especially on high-risk areas near airports and seaports with intense international trade and in proximity to host crops.
Crops, Agricultural, Ecology, Behavior and Bionomics, Animals, Agriculture, Spodoptera, Introduced Species, Brazil, Ecosystem
Crops, Agricultural, Ecology, Behavior and Bionomics, Animals, Agriculture, Spodoptera, Introduced Species, Brazil, Ecosystem
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