Analysis of the drivers of tropical soil acidification in Hainan Island based on explainable machine learning

Soil acidification poses a severe threat to tropical agriculture. This study establishes an explainable machine learning framework to quantify drivers of soil acidification in Hainan Island, China. Total runoff and nitrogen fertilizer application emerged as the dominant natural and anthropogenic drivers. Hydrological factors exert contrasting effects: total runoff intensifies acidification, whereas subsurface runoff buffers it. A critical interaction was identified, with nitrogen fertilizer exerting its strongest acidifying effect under medium runoff conditions but weakening under extreme conditions. Spatial SHAP mapping revealed acidification hotspots concentrated in the central-western region. The findings highlight that effective mitigation requires integrating hydrothermal conditions with human inputs and tailoring fertilization strategies to local hydrological regimes, providing a scientific basis for precision soil management.