Bioclimatic variables used for the study.

Rice yellow stem borer, Scirpophaga incertulas (Walker) (Lepidoptera: Crambidae) is a serious pest, that causes significant yield loss (10-40%) to rice crop in India and other parts of the world. This study emphasizes the prediction of the potential invasion risk, distribution, and further spread of S. incertulas during current and future climate change scenarios in India and the world. The pest identity was confirmed with morphological taxonomy, and the possible habitat distribution and further spread in future climate scenarios were modelled using the MaxEnt algorithm. The climate niche for S. incertulas was also established by analyzing the correlation between the pest occurrence data of 143 locations in India and seven bioclimatic variables viz., bio01, bio02, bio03, bio05, bio12, bio13, and bio15, were chosen for predicting the distribution of S. incertulas. The model performance was good as it exhibited a strong Receiver Operating Characteristic Curve value of 0.949. Based on the Jackknife test, the Bio 13 (precipitation of the wettest month), exhibited the highest gain value and emerged as the primary abiotic factor exerting influence on the potential habitat distribution of this borer. The study demonstrated that bioclimatic variables annual mean temperature (30 °C), and annual precipitation (10-700 mm) favour its multiplication, infestation, and further spread to new areas. As the anticipated habitat range of S. incertulas is of considerable importance for researchers and other stakeholders involved in plant protection, the data generated here may be useful for researchers, policymakers, and farmers for designing better management strategies to mitigate this pest and curtail its spread to new rice growing areas in a rapidly changing global environment.

稻黄茎螟（Scirpophaga incertulas (Walker)，鳞翅目（Lepidoptera）草螟科（Crambidae））是一种重大农业害虫，在印度及全球其他地区可造成水稻10%~40%的产量损失。本研究聚焦印度及全球范围内当前与未来气候变化情景下稻黄茎螟的潜在入侵风险、分布格局及扩张趋势预测。本研究通过形态分类学方法确认了该害虫的物种身份，并采用最大熵模型（MaxEnt）对未来气候变化情景下的潜在适生分布及扩张趋势进行了模拟。通过分析印度境内143个采样点的害虫发生数据与7个生物气候变量（即bio01、bio02、bio03、bio05、bio12、bio13、bio15）之间的相关性，本研究构建了稻黄茎螟的气候生态位，上述变量被用于该虫的分布预测。模型表现优异，受试者工作特征曲线（Receiver Operating Characteristic Curve，ROC）值高达0.949。通过刀切法（Jackknife）检验可知，Bio13（最湿月降水量）的增益值最高，是影响该螟虫潜在适生分布的首要非生物因子。研究表明，年平均温度（30℃）与年降水量（10~700mm）这两个生物气候变量有利于该虫的繁殖、为害及向新区域的扩张。鉴于稻黄茎螟的潜在适生范围对植物保护领域的研究者及其他利益相关方具有重要参考价值，本研究生成的数据可为研究者、政策制定者与农户提供支撑，助力其在快速变化的全球环境中制定更科学的害虫治理策略，减轻该虫为害并遏制其向新稻区的扩散。