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In recent decades, ecological niche models (ENMs) have been widely used to predict suitable habitats for species. However, for invasive organisms, the prediction accuracy is unclear. In this study, we employed the most widely used maximum entropy (MaxEnt) model and ensemble model (EM) Biomod2 and verified the practical effectiveness of the ENM in predicting the distribution areas of invasive insects based on the true occurrence of Hyphantria cunea in China. The results showed that when only limited data of invasive areas were used, the two ENMs could not effectively predict the distribution of suitable habitats of H. cunea, although the use of global data can greatly improve the prediction accuracy of ENMs. When analyzing the same data, Biomod2's prediction accuracy was significantly better than that of MaxEnt. For long‐term predictions, the area of suitable habitat predicted by the ENMs was much greater than the occurrence area; for short‐term predictions, the accuracy of the predicted area was significantly improved. Under the current conditions, the area of suitable habitat for H. cunea in China is 118 × 104 km2, of which 59.32% is moderately or highly suitable habitat. Future climate change could significantly increase the suitable habitat area of H. cunea in China, and the predicted area of suitable habitats in all climate scenarios exceeded 355 × 104 km2, accounting for 36.98% of the total land area in China. This study demonstrates the use of ENMs to study invasive insects and provides a reference for the management of H. cunea in China. [ABSTRACT FROM AUTHOR]

Bemisia tabaci is an important pest affecting agricultural and horticultural crops worldwide and comprises a complex of cryptic species. In China, the introduction of the two invasive cryptic species, Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED), has considerably affected the ecological niche of the native cryptic species. Based on occurrence records obtained through field surveys and high-resolution environmental data, using maximum entropy modelling, we established ecological niche models to predict the distribution of invasive and native cryptic species of B. tabaci in China and identified the differences in ecological niches. The results showed that the distribution range and niche breadth of the invasive cryptic species exceed that of the native cryptic species in the order of MED > MEAM1 > China1 > Asia1. There are different degrees of niche overlap and range overlap between cryptic species. Moreover, the important environmental variables affecting their distribution were different, as well as their response and adaptation to most environmental variables. Our results suggest that the B. tabaci species complex occupies a complex ecological niche in China. The findings improve our understanding of the ecological characteristics of B. tabaci species complex, which will be useful in the development of prevention and control strategies for this pest in China. [ABSTRACT FROM AUTHOR]