Causal Drivers of Land-Atmosphere Carbon Fluxes from Machine Learning Models and Data

• Information theory measures describe individual and joint causal relationships in observed versus modeled vertical carbon dioxide fluxes. • Three machine learning models overestimate unique information from sources at the expense of synergistic, or joint information. • Regionally trained models have improved functional but not predictive performances, indicating a trade-off.