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. CO2 production in soils responds strongly to changes in temperatureand moisture, but the magnitude of such responses at different timescalesremains difficult to predict. Knowledge of the mechanisms leading to theoften observed interactions in the effects of these drivers on soil CO2 emissions is especially limited. Here we test the ability ofdifferent soil carbon models to simulate responses measured in soilsincubated at a range of moisture levels and cycled through 5, 20, and35  ∘ C. We applied parameter optimization methods while modifying twostructural components of models: (1) the reaction kinetics of decompositionand uptake and (2) the functions relating fluxes to soil moisture. We foundthat the observed interactive patterns were best simulated by a model usingMichaelis–Menten decomposition kinetics combined with diffusion of dissolvedcarbon (C) and enzymes. In contrast, conventional empirical functions that scaledecomposition rates directly were unable to properly simulate the mainobserved interactions. Our best model was able to explain 87 % of thevariation in the data. Model simulations revealed a central role ofMichaelis–Menten kinetics as a driver of temperature sensitivity variationsas well as a decoupling of decomposition and respiration C fluxes in theshort and mid-term, with general sensitivities to temperature and moisturebeing more pronounced for respiration. Sensitivity to different modelparameters was highest for those affecting diffusion limitations, followed byactivation energies, the Michaelis–Menten constant, and carbon useefficiency. Testing against independent data strongly validated the model( R2=0.99 ) and highlighted the importance of initial soil C poolconditions. Our results demonstrate the importance of model structure and thecentral role of diffusion and reaction kinetics for simulating andunderstanding complex dynamics in soil C.

Diffusion limitations and Michaelis–Menten kinetics as drivers of combined temperature and moisture effects on carbon fluxes of mineral soils