Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
2026098 | Soil Biology and Biochemistry | 2010 | 9 Pages |
The most frequently used models simulating soil organic matter (SOM) dynamics are based on first-order kinetics. These models fail to describe and predict such interactions as priming effects (PEs), which are short-term changes in SOM decomposition induced by easily available C or N sources. We hypothesized that if decomposition rate depends not only on size of the SOM pool, but also on microbial biomass and its activity, then PE can be simulated. A simple model that included these interactions and that consisted of three C pools – SOM, microbial biomass, and easily available C – was developed. The model was parameterized and evaluated using results of 12C–CO2 and 14C–CO2 efflux after adding 14C-labeled glucose to a loamy Haplic Luvisol. Experimentally measured PE, i.e., changes in SOM decomposition induced by glucose, was compared with simulated PE. The best agreement between measured and simulated CO2 efflux was achieved by considering both the total amount of microbial biomass and its activity. Because it separately described microbial turnover and SOM decomposition, the model successfully simulated apparent and real PE.The proposed PE model was compared with three alternative approaches with similar complexity but lacking interactions between the pools and neglecting the activity of microbial biomass. The comparison showed that proposed new model best described typical PE dynamics in which the first peak of apparent PE lasted for 1 day and the subsequent real PE gradually increased during 60 days. This sequential decomposition scheme of the new model, with immediate microbial consumption only of soluble substrate, was superior to the parallel decomposition scheme with simultaneous microbial consumption of two substrates with different decomposability. Incorporating microbial activity function in the model improved the fit of simulation results with experimental data, by providing the flexibility necessary to properly describe PE dynamics. We conclude that microbial biomass should be considered in models of C and N dynamics in soil not only as a pool but also as an active driver of C and N turnover.