Lightning-induced forest fires represent a dominant natural ignition source in boreal and temperate ecosystems, yet their climatic and biophysical controls remain poorly understood. This study investigates the spatiotemporal patterns and environmental drivers of 646 lightning-induced forest fires across the Da Hinggan Ling region, Northeast China, during 2001–2024. Multi-source datasets from ERA5-Land, MODIS, and ETCCDI were integrated to quantify short-term meteorological variability, vegetation water status, and long-term climatic extremes. Using Random Forest and XGBoost models combined with SHAP interpretability analysis, we identified key predictors and nonlinear responses of burned area to environmental forcing. Results reveal pronounced interannual fluctuations in fire activity, with 2010, 2016, and 2022 emerging as compound extreme years characterized by co-occurring drought and heatwaves. Vegetation moisture index (NDMI), diurnal temperature range (DTR), and heatwave duration (HWDI) were the most influential variables controlling burned area variability. The total burned area and fire duration showed significant declining trends, while high burned-area fires exhibited spatial clustering in dry, low-LAI regions. These findings demonstrate that compound dry–hot conditions coupled with vegetation desiccation are the primary drivers of large lightning fires. The study provides a process-based understanding of climate–fuel–fire linkages and supports improved fire risk forecasting under a warming climate.
Lou et al. (Sat,) studied this question.