OOS 33-1
What does data tell us about model structure of microbial decomposition of soil organic carbon
Traditionally, soil carbon decomposition has been modeled by first-order, donor pool-dominated carbon transfers (i.e., linear model). Recently many other types of models have been developed to describe soil carbon cycling. Most of these models are based on kinetic and stoichiometric principles to constrain elemental cycling within the soil and carbon exchange with vegetation and the atmosphere. In particular, various models have been developed to account for different assumptions of microbial roles in soil biogeochemistry. One type of models, which describes microbial roles in soil carbon decomposition with Michaelis-Menton kinetics (i.e., nonlinear model), can simulate priming effects and respiratory acclimation more flexibly than the traditional decomposition model. Not many of those models, however, have been rigorously examined against data.
We have used the data assimilation approach to rigorously test various types of soil carbon models against hundreds and thousands of data sets from litter decommission studies, soil incubation, field measurement of soil carbon dynamics during forest succession, and regional and global soil carbon databases. For example, we used data assimilation approach to separate soil carbon (C) efflux from long-term incubation experiments into different source pools. We used first-order linear kinetic models with one, two or three pools in data assimilation and used probability density functions as a criterion to judge the best model to fit the datasets.
Results/Conclusions
Our results indicated that soil C release trajectories over the period of the incubation studies were best modeled with two- or three-pool, linear C decomposition models. That means soil organic matter (SOM) is heterogeneous in structure and consist of various pools with different intrinsic turnover rates. We have applied this approach to hundreds of soil incubation data. All analyses indicate that two- or three-pool, linear kinetic models can adequately represent each of the soil incubation data. None of data sets from those studies and thousands of other data sets from studies on litter decomposition and soil carbon dynamics during forest succession exhibits oscillatory behavior of the nonlinear microbial models. Even so, estimated coefficients of carbon transfers and mineralization rates in each of the pools nonlinearly vary with soil type, vegetation type, experimental treatment, and environmental conditions, likely due to microbial mediation. It is still a challenge to develop a model that can realistically represent soil carbon dynamics in the real world.