Challenges of using microbial explicit models for evaluating organic matter decomposition in predominantly organic soils

Models of soil organic matter (SOM) decomposition are critical for predicting the fate of soil carbon (and nutrient) under changing climate. Traditionally, models have used a simple set-up where the substrate is divided into conceptual pools to represent their resistance to microbial degradation, and decomposition rates are often proportional to the amount of substrate in each pool. Emerging models now consider explicit microbial dynamics and show that SOM loss under warming may be fundamentally different from the classical models. Microbial explicit models use reaction kinetics, represented on a concentration basis. However, when the substrate makes up most of the volume of soils (e.g., the organic horizon in forest soils or peat), an increase or decrease in SOM does not, or only very little, affect concentrations of microbes and substrate. Consequently, reduction in SOM does not reduce the amount of substrate the microbial biomass encounters. This problem does not occur in classical models like CENTURY. We incorporated the effect of organic matter on soil volume in several microbial models. If microbes are solely limited by enzymes, organic soils or peats are decomposed very quickly as there is no mechanism that stops the positive feedback between microbial growth and SOM concentration until the substrate is gone. Alternative formulations that account for carbon limitation or microbial ‘cannibalism’ display a sweet spot of soil carbon concentration. Interestingly, a response to warming will depend on the amount of organic vs. mineral materials. Apparent Q₁₀ was higher in fully organic soil than in mineral soils, which was pronounced when small to moderate amounts of the mineral matter was present that diluted the substrate for microbes. We suggest that model formulations need to be clear about the assumption in key processes, as each of the steps in the cascade of biogeochemical reaction can produce surprising results.