Modeling Natural Forest Fire Regimes Based on Drought Characteristics at Various Spatial and Temporal Scales in P. R. China

Climate change causes extreme weather events to occur frequently, such as drought, which may exacerbate forest fire regimes; as such, forest fire regimes may be closely related to drought characteristics. The spatial non-stationarity of factors affecting forest fires has not been fully clarified and needs further exploration. This study intends to address how drought characteristics affect forest fire regimes in China and whether spatial non-stationarity can improve the model prediction based on methods such as the run theory and GWR. Our results show that geographically weighted regression models perform better (AICc, AUC, R2, RMSE, and MAE) than global regression models in modeling forest fire regimes. Although GWR improves accuracy, small sample sizes (vegetation zones, climatic zones) may affect its accuracy. Drought characteristics significantly affect (p < 0.05) the forest fire regimes, and the correlation is spatially non-static. At the grid scale, a positive correlation between the forest fire occurrence probability and drought characteristics is mostly distributed in the southwest and northwest regions. Our study is conducive to an in-depth understanding of the relationship between forest fire regimes and drought, aiming to provide a scientific basis for the development of forest fire management measures to mitigate drought stress according to local conditions.