The fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith), is a highly destructive insect pest of several crop plants and threatening global food security. The current Coupled Model Intercomparison Project phase 6 (CMIP6) data set was analysed to predict the potential worldwide distribution of FAW under present and future climate change scenarios in 2050 and 2070 under Shared Socioeconomic Pathway (SSP) 1-2.6 and SSP5-8.5 emission scenario with 19 bioclimatic variables through maximum entropy (MaxEnt) niche modelling. The MaxEnt model predicted the potential distribution of S. frugiperda with area under the receiver operator curve (AUC) values of 0.915 and 0.910 during training and testing, respectively. Annual precipitation, annual mean temperature and isothermality were the strongest predictors of S. frugiperda distribution with 42.6%, 22.4% and 10% contributions, respectively. The recent CMIP6 models predicted higher suitability of FAW in North America, Africa and Asia under future climatic conditions. Global suitability of FAW is predicted to increase by 4.49% and 8.33% under SSP1-2.6 and SSP5-8.5 scenarios, respectively, compared to that of current climate conditions. Multimodel ensemble predicted the highest risk of invasion and spread of FAW by 2050 and 2070 under SSP5-8.5 scenario. The predictions could be used to forecast the potential spread of FAW and combating outbreaks well in advance. Our results will be an important guide for researchers, policymakers and governments to devise suitable management strategies against this highly invasive pest.

秋季粘虫 (FAW)草地夜蛾(JE Smith) 是一种对多种农作物具有高度破坏性的害虫，威胁着全球粮食安全。对当前耦合模型比对项目第 6 阶段 (CMIP6) 数据集进行分析，以预测在共享社会经济路径 (SSP) 1-2.6 和 SSP5-8.5 排放情景下，2050 年和 2070 年当前和未来气候变化情景下秋粘虫在全球的潜在分布通过最大熵 (MaxEnt) 生态位建模获得 19 个生物气候变量。MaxEnt 模型预测了草地早熟禾的潜在分布在训练和测试期间，接受者操作曲线下面积 (AUC) 值分别为 0.915 和 0.910。年降水量、年平均温度和等温度是草地贪夜蛾的最强预测因子分布，贡献分别为 42.6%、22.4% 和 10%。最近的 CMIP6 模型预测，在未来的气候条件下，秋粘虫在北美、非洲和亚洲的适用性更高。与当前气候条件相比，预计在 SSP1-2.6 和 SSP5-8.5 情景下，秋粘虫的全球适宜性分别提高 4.49% 和 8.33%。多模式集合预测了 SSP5-8.5 情景下 2050 年和 2070 年秋粘虫入侵和传播的最高风险。这些预测可用于提前预测秋粘虫的潜在传播和抗击疫情。我们的研究结果将成为研究人员、政策制定者和政府制定针对这种高度入侵性害虫的合适管理策略的重要指南。