Abstract
Tobacco black shank, caused by Phytophthora nicotianae, is characterized by rapid outbreak onset and high control difficulty, posing a persistent threat to tobacco production in China. To assess its potential geographic distribution and management risks under climate change, this study employed 410 verified occurrence records and 32 environmental variables to construct a Maximum Entropy (MaxEnt) model, with key variable interpretation supported by an XGBoost-SHAP framework. The model simulated a suitable habitat under current conditions and four CMIP6 climate scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) from 2021 to 2100. The optimized model (AUC = 0.959) identified eight key environmental predictors, including the minimum temperature of the coldest month (bio6), annual precipitation (bio12), temperature seasonality (bio4), precipitation of the wettest month (bio13), precipitation of the driest month (bio14), elevation, slope, and land use type. Response curves and SHAP dependence plots revealed clear ecological thresholds, such as a notable increase in suitability when bio6 exceeds 0°C, elevation ranges from 800 to 1500 m, and both bio13 and bio14 fall within specific precipitation intervals. Future projections showed an overall expansion of suitable areas, with the largest extent (165.54 × 10(4) km(2)) under the SSP2-4.5 scenario and a northeastward shift in habitat centroid. Overlaying predicted suitability with tobacco cultivation data revealed 28.35% spatial overlap, primarily in major growing regions such as Yunnan and Guizhou. These results clarify the critical role of temperature and moisture in shaping the pathogen's ecological niche and offer a quantitative foundation for risk-based surveillance and region-specific management of tobacco black shank.