Microbial decomposition of plant litter is a crucial process for the land carbon (C) cycle, as it directly controls the partitioning of litter C between CO2 released to the atmosphere versus the formation of new soil organic matter (SOM). Land surface models used to study the C cycle rarely considered flexibility in the decomposer C use efficiency (CUEd) defined by the fraction of decomposed litter C that is retained as SOM (as opposed to be respired). In this study, we adapted a conceptual formulation of CUEd based on assumption that litter decomposers optimally adjust their CUEd as a function of litter substrate C to nitrogen (N) stoichiometry to maximize their growth rates. This formulation was incorporated into the widely used CENTURY soil biogeochemical model and evaluated based on data from laboratory litter incubation experiments. Results indicated that the CENTURY model with new CUEd formulation was able to reproduce differences in respiration rate of litter with contrasting C:N ratios and under different levels of mineral N availability, whereas the default model with fixed CUEd could not. Using the model with flexible CUEd, we also illustrated that litter quality affected the long-term SOM formation. Litter with a small C:N ratio tended to form a larger SOM pool than litter with larger C:N ratios, as it could be more efficiently incorporated into SOM by microorganisms. This study provided a simple but effective formulation to quantify the effect of varying litter quality (N content) on SOM formation across temporal scales. Optimality theory appears to be suitable to predict complex processes of litter decomposition into soil C and to quantify how plant residues and manure can be harnessed to improve soil C sequestration for climate mitigation.
CITATION STYLE
Zhang, H., Goll, D. S., Manzoni, S., Ciais, P., Guenet, B., & Huang, Y. (2018). Modeling the effects of litter stoichiometry and soil mineral N availability on soil organic matter formation using CENTURY-CUE (v1.0). Geoscientific Model Development, 11(12), 4779–4796. https://doi.org/10.5194/gmd-11-4779-2018
Mendeley helps you to discover research relevant for your work.