Causality-guided explainable machine learning shows groundwater accounts for 48% to 101% of aridity's effect on forest photosynthesis across the contiguous United States
Using satellite observations of solar-induced fluorescence together with model estimates of water table depth and aridity, and applying causality-guided explainable machine learning, this study quantified the relative roles of groundwater and climatic aridity in shaping the spatial pattern of photosynthesis across the contiguous United States, finding that groundwater's relative importance equals 48% to 101% of aridity's effect on forest photosynthesis, 30% to 58% in savannahs and shrublands, 22% to 42% in grasslands, and 15% to 32% in croplands.