Models of organic matter decomposition are critical to predict of soil carbon and nitrogen in soils and sediments in response to global change stressors. Many of these models have traditionally a very simple set-up in which the substrate is divided up in conceptual pools that are represent their resistance to microbial degradation. In these, rates of decomposition are often proportional to the amount of substrate in each pool. Newer models have now emerged that consider explicit microbial dynamics. These models show that soil organic matter loss in response to warming may be fundamentally different from the classical decomposition models.
An important feature of the explicit microbial models is that the reaction kinetics are formulated on a concentration basis. However, when the substrate makes up most of the volume of a soil, such as the organic horizon in forest soils or peat, an increase or decrease in soil organic matter does not, or only very little, affect concentrations of microbes and substrate. As a consequence, reduction in soil organic matter does not reduce the amount of substrate the microbial biomass encounters. This problem does not occur in traditional linear decomposition models, such as CENTURY.
Results/Conclusions
We incorporated the effect organic matter on soil volume in several microbial models. If microbes are solely limited by enzymes, peat and organic soil are decomposed very quickly as there is no mechanism that stops the positive feedback between microbial growth and soil organic matter concentration until the substrate is gone. Alternative formulations that account for carbon limitation or microbial ‘cannibalism’ display a sweet spot of soil carbon concentration. Perhaps most interestingly and most consequential, a response to warming will depend on amount or organic vs. mineral materials. Apparent Q10 was higher in fully organic soil than in mineral soils but was even more pronounced when small to moderate amounts of mineral matter was present that diluted the substrate for microbes.
Thus, new 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.