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Rhododendron delavayi Franch. predominantly thrives in broad-leaved evergreen forests and bushes at altitudes of 1,200–3,200 meters. It favors a cool, moist climate and thrives in acidic soils. Due to its high ornamental, medicinal, and scientific values, understanding its ecological needs and optimal cultivation ranges is crucial. This study analyzing the key environmental factors and their thresholds affecting its distribution and predicts the future potential habitats of R. delavayi using existing distribution data alongside current and projected climate data. The results indicate that the primary environmental influencers are soil pH (4.9–5.4), precipitation in the driest month (10–20 mm), and altitude, contributing 41.8, 24.1, and 18.3%, respectively. It also shows a declining trend in suitable habitats: from 27.75 × 104 km² under current conditions, to 3.69 × 104 km² by the 2050s, and further to 2.65 × 104 km² by the 2070s. [ABSTRACT FROM AUTHOR]

Simple Summary: Bactrocera tsuneonis (Miyake) is a significant pest of commercial citrus crops. It is a univoltine and oligophagous species widely distributed in Japan and China. In this study, the potential distribution of the B. tsuneonis population under current and different future climate change scenarios was modeled using MaxEnt software (v. 3.4.1) and optimized using R software (v. 4.3.2). Under current climate conditions, the potentially suitable areas were mainly concentrated in Central, South, and East China. The total area of habitats suitable for this pest was predicted to increase in the future climate scenarios. The centroid of the total suitable habitat for this pest gradually shifted westward and northward. Our findings provide new insights that could aid the monitoring of B. tsuneonis in China. The invasive pest, Bactrocera tsuneonis (Miyake), has become a significant threat to China's citrus industry. Predicting the area of potentially suitable habitats for B. tsuneonis is essential for optimizing pest control strategies that mitigate its impact on the citrus industry. Here, existing distribution data for B. tsuneonis, as well as current climate data and projections for four future periods (2021–2040, 2041–2060, 2061–2080, and 2081–2100) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) were obtained. The distribution of B. tsuneonis under current and different climate change scenarios in China was predicted using the optimized MaxEnt model, ArcGIS, and the ENMeval data package. Model accuracy was assessed using ROC curves, and the primary environmental factors influencing the distribution of the pest were identified based on the percent contribution. When the regularization multiplier (RM) was set to 1.5 and the feature combination (FC) was set to LQH, a model with lower complexity was obtained. Under these parameter settings, the mean training AUC was 0.9916, and the mean testing AUC was 0.9854, indicating high predictive performance. The most influential environmental variables limiting the distribution of B. tsuneonis were the Precipitation of Warmest Quarter (Bio18) and Temperature Seasonality (standard deviation ×100) (Bio4). Under current climatic conditions, potentially suitable habitat for B. tsuneonis in China covered an area of 215.9 × 104 km2, accounting for 22.49% of the country's land area. Potentially suitable habitat was primarily concentrated in Central China, South China, and East China. However, under future climatic projections, the area of suitable habitat for B. tsuneonis exhibited varying degrees of expansion. Furthermore, the centroid of the total suitable habitat for this pest gradually shifted westward and northward. These findings suggest that B. tsuneonis will spread to northern and western regions of China under future climate changes. The results of our study indicate that climate change will have a major effect on the invasion of B. tsuneonis and have implications for the development of strategies to control the spread of B. tsuneonis in China. [ABSTRACT FROM AUTHOR]

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]