Cotton production areas are at high risk of invasion by Amrasca biguttula (Ishida) (Cicadellidae: Hemiptera): potential distribution under climate change.

Background: The cotton jassid, Amrasca biguttula, a dangerous and polyphagous pest, has recently invaded the Middle East, Africa and South America, raising concerns about the future of cotton and other food crops including okra, eggplant and potato. However, its potential distribution remains largely unknown, posing a challenge in developing effective phytosanitary strategies. We used an ensemble model of six machine-learning algorithms including random forest, maxent, support vector machines, classification and regression tree, generalized linear model and boosted regression trees to forecast the potential distribution of A. biguttula in the present and future using presence records of the pest and bioclimatic predictors. The accuracy of these algorithms was assessed based on the area under the curve (AUC), correlation (COR), deviance and true skill statistic (TSS).

Results: All algorithms showed good performance in forecasting the distribution of A. biguttula (AUC ≥ 0.91, COR ≥ 0.72, TSS ≥ 0.77 and deviance ≤ 0.65). Mean temperature of wettest quarter, mean temperature of driest quarter and precipitation of the wettest month were the key variables that contributed to predicting A. biguttula occurrence. Projection of the model showed that cotton production areas in Asia, sub-Saharan Africa, and South America are at threat of invasion by A. biguttula under the current climatic scenario. Additionally, range expansion for A. biguttula is projected in the future in sub-Saharan Africa, South America and China, indicating a suitable ecological niche for A. biguttula to thrive.

Conclusion: Our results provide early warning and decision-making information that can guide efforts to prevent this pest's further spread and invasion into new areas. © 2025 Society of Chemical Industry.