All in? Soil organic carbon and nitrogen turnover modeling including structure dynamics

The adequate quantification of soil organic carbon (SOC) turnover is a pressing need for improving soil health and understanding climate dynamics. It is controlled by the complex interplay of microbial activity, availability of carbon (C) and nitrogen (N) sources, and the dynamic restructuring of the soil's architecture. Accurate modeling of SOC dynamics requires the representation of these processes at small spatial scales to help understanding the mechanisms that drive these processes.

Among them are the enzymatic degradation of particulate organic matter, the cycling of microbial necromass, but also short-term influences as root exudation. As such, microbial growth and turnover, C respiration and N cycling depend on the C/N ratios of the different organic carbon sources.

We show the feasibility to include such a variety of processes in a microscale model, along with the possibility to simulate soil structure dynamics including the stabilization of soil particles, POM or microbial necromass via organo‐mineral associations. The computational framework is a cellular automaton model that allows to create virtual soils on the basis of µCT or video analysis data of aggregates. Parameters are chosen consistently from rhizosphere experiments without parameter fitting to explore the influence of soil structural heterogeneity and connectivity, N limitation, or necromass formation on SOC storage.

Our results highlight that evolving soil architecture and pore connectivity control substrate accessibility, creating micro‐scale hot and cold spots for microbes. N availability consistently co-limits microbial growth, while a favorable C/N ratio of root exudates substantially reduces respiration and increases CUE over extended periods. Necromass emerges as long‐term SOC pool, as N from short‐term root exudation pulses promotes biomass growth and is converted into slowly degradable necromass, which can be physically protected through occlusion. The findings align with lab experiments and additionally allow us to elucidate the spatial and temporal dynamics of the drivers of carbon turnover. We also present an option to couple such microscale simulations to macroscale transport  model for, e.g., CO2 across soil profiles.