Suitable region prediction of <italic>Malacosoma disstria</italic> based on MaxEnt model

To predict the distribution pattern of Malacosoma disstria suitable region and evaluate the impact of future climate change on its suitable region range in China, global distribution data combined with current and future environmental factors under different climate scenarios were utilized. The parameters of the MaxEnt model were optimized using the Kuenm package in R software, followed by analysis of the optimized model outputs. The results indicated that the optimal model parameters were determined as regularization multiplier (Rm) of 0.5, with feature combinations (Fc) including linear (L), quadratic (Q), threshold (T), and hinge (H) features. Model evaluation metrics revealed that the area under the curve (AUC) of receiver operating characteristic curve (ROC) was 0.947 and the true skill statistic (TSS) was 0.834, indicating that the model predictions were highly reliable. The primary environmental factors influencing the suitable habitat were identified as precipitation in the driest month (bio14), precipitation in the wettest quarter (bio16), and maximum temperature in the warmest month (bio5). Under current climatic conditions, the pest’s suitable regions in China were concentrated in the northeastern, central, eastern, southern, and southwestern regions. Moderately suitable region and high suitability region in provinces including Jilin, Liaoning, Henan, Shandong, Anhui, Jiangxi, Fujian, and Yunnan accounted for 35.06% of Chinese total forest coverage. Under future climate scenarios, the distribution range of M. disstria suitable region in China is expected to remain relatively stable.