Prediction of the Potential Geographical Distribution of Obolodiplosis robiniae (Diptera: Cecidomyiidae) in China Based on A Novel Maximum Entropy Model

Objective: Based on the national investigation of Obolodiplosis robiniae, the current and future (2050) sustainable habitats of O. robiniae in China were predicted by using the complementary log-log (Cloglog) of maximum entropy model. This study would provide an important reference for forestry and quarantine authorities to control and quarantine of O. robiniae at present and in the future. Method: MaxEnt, ArcGIS, and R software were used to scientifically optimize the three aspects of the O. robiniae distribution points, bio-climatic variables and model parameter setting, to ensure the scientificity and validity of the model. The current bio-climatic variables for the suitable area were predicted by using WorldClim Website Global Weather Database Version 1.4, with5 min of spatial resolution. The future data were derived from three representative concentration pathways RCP26, RCP45 and RCP85 under CCSM4. Result: A total of 52 distribution points and 7 bio-climatic variables were finally determined. The complementary log-log output format was used to predict the potential geographical distribution. The test omission rate of simulation results is basically consistent with the theoretical omission rate. The ROC (receiver operating characteristic curve), which has an AUC (area under the ROC curve) of 0.919 and a standard deviation of 0.023, indicating that the test and training data have no spatial autocorrelation and the constructed model meets the "excellent" standard. Through Jackknife test analysis, the three bio-climatic variables that have the greatest influence on O. robiniae distribution are Bio1 (Annual mean temperature), Bio12 (Annual precipitation) and Bio5 (Max temperature of warmest month). For the current classification of the potential geographical distribution for O. robiniae, the suitable range is in the range of 22.08°-48.42°N, 39.39°-135.06°E, accounting for 31.90% of the national area. With the exception of Tibet, Qinghai, Hainan, and Taiwan province, the other provinces have their own potential geographical distribution, and the highly potential geographical distribution regions are mainly in the southwest (Sichuan, Chongqing) and Northern China (Beijing, Tianjin, Hebei, Shandong, and Shaanxi). For the prediction of the future (2050), the total susceptibility zones of the three representative concentration pathways RCP26, RCP45, and RCP85 are larger than the total habitats in the current climate, especially for high and moderate suitable habitats. The areas in Xinjiang and northern China will expand significantly. The risk area under the RCP85 scenario is the largest, reaching to 39.71% of the national area, 750 000 km2 more than the current prediction. Conclusion: Combined with the actual investigation, the novel MaxEnt model has high reliability to clarify the dominant climatic factors affecting the distribution of O. robiniae, and predict the distribution and fitness of O. robiniae current and future (2050), which is of important value for the prevention and control of O. robiniae. © 2019, Editorial Department of Scientia Silvae Sinicae. All right reserved.