Soil organic matter (SOM) is a major ecosystem component, central to soil fertility, carbon balance and other soil functions. To advance SOM modelling, we devised a steady‐state model of topsoil SOM, with explicit descriptions of physical states and properties, and used it to simulate SOM concentration, carbon:nitrogen:phosphorus (C:N:P) stoichiometry, bulk density and radiocarbon content. The model classifies SOM by element stoichiometry (αSOM is poor in N and P, βSOM is rich), mean residence times (1–2000 years) and physical state (free, occluded, adsorbed, hypoxic). The most stable SOM is either βSOM preferentially adsorbed by mineral matter, or αSOM in strongly hypoxic zones. Soil properties were simulated for random combinations of plant litter input (amount and C:N:P stoichiometry), mineral sorption capacity, propensity for hypoxia, and bulk density of non‐adsorbed αSOM. To optimize model parameters, outputs from 5000 simulations were used to construct bivariate relations among soil variables, which were compared with those found in data for 835 survey sites, covering all common land uses. The bivariate relations, and patterns of data scatter, were reproduced, and also variations in soil radiocarbon with soil type, suggesting that apparent scatter in measured data might reflect SOM diversity. The temporal acquisition by soil of ‘bomb 14C’ could also be simulated. The steady‐state model is the basis for a dynamic version, suitable for simulating changes in SOM through time. It provides insight into the possible manipulation of soil organic carbon (SOC) sequestration; for example, increasing litter inputs might only increase moderately‐stable SOC pools, whereas encouraging the creation of βSOM by adsorption to mineral matter from deeper soil could lead to long‐term stabilization.
Highlights
Models of SOM should include explicit descriptions of physical states and properties.
Our new topsoil SOM model is constrained by C:N:P stoichiometry, SO14C, and physical fractionation data.
Simulated soil properties, randomly generated, account for measured trends and patterns of scatter in SOM data.
SOM properties depend upon litter input, interactions with mineral matter, hypoxia, and bulk density.