Abstract: [Obiective] The Chinese pine caterpillar, Dendrolimus tabulaeformis, is a serious native pine defoliator with frequent outbreaks in northern China. The MaxEnt model is one of the most effective software packages available for modeling species' distributions. The main objective of the current study was to test and determine the possibility of using MaxEnt to simulate and predict future large-scale outbreaks of D. tabulaeformis based on county-level historical outbreak records (2002-2011), and daily meteorological data from 19 weather stations in Shanxi province. [Method] Using Principal Component Analysis and Step-wise Regression methods with actual pest outbreak data, the 8 most relevant factors were chosen from 80 outbreak-related bio-climate factors potentially affecting development of the insect. The key factors were X₂₉ (days with mean temperature<5℃ in October), X₄₃ (days with humidity >75% in July), X₅₄ (mean monthly wind speed in March), X₅₅ (mean monthly wind speed in April, May and June), X₅₆ (mean monthly wind speed in July and August), X₆₂ (days with wind speed >10 m·s^-1 in October), X₆₃ (maximum daily wind speed in September), X₆₇ (precipitations in April, May and June). [Result] With the 8 screened phenological factors, the MaxEnt model was used to make the training simulation with the actual disaster data. The Jackknife test showed that X₄₃, X₅₄ and X₅₅ were the three principle climatic factors that best simulated historical outbreaks using the MaxEnt model, and ROC (recevier operating characteristic curve) test showed an AUC (area uner the ROC curve) value of 0.82 with a STD(standard deviation) of 0.019. Based on data from the WorldClim database for future climate scenarios, pine caterpillar outbreak distribution maps for 2050 were generated via the MaxEnt model under RCP(representative concentration pathway)4.5 and RCP6.0. According to these maps, in the 2050s, Beijing and Hebei province, plus the southern border area of Inner Mongolia Autonomous Region with Hebei, will have a high risk of outbreaks under RCP4.5, while more serious outbreak area will be the south central region of Shanxi province under RCP6.0. [Conclusion] MaxEnt model is potentially useful for forecasting future pine caterpillar outbreaks under climate change.

Key words: Dendrolimus tabulaeformis, MaxEnt, bio-climatic variables, climate change, outbreak