Quantifying the short-term dynamics of soil organic carbon decomposition using a power function model

Abstract

Introduction: Soil heterotrophic respiration (Rh, an indicator of soil organic carbon decomposition) is an important carbon efflux of terrestrial ecosystems. However, the dynamics of soil Rh and its empirical relations with climatic factors have not been well understood. Methods: We incubated soils of three subtropical forests at five temperatures (10, 17, 24, 31, and 38 °C) and five moistures (20, 40, 60, 80, and 100% water holding capacity (WHC)) over 90 days. Rh was measured throughout the course of the incubation. Three types of models (log-linear, exponential, and power model) were fitted to the measurements and evaluated based on the coefficient of determination (r2) and Akaike Information Criterion (AIC) of the model. Further regression analysis was used to derive the empirical relations between model parameters and the two climatic factors. Results: Among the three models, the power function model (Rh = R1t−k) performed the best in fitting the descending trend of soil Rh with incubation time (r2 > 0.69 for 26 of 30 models). Both R1 and k generally increased linearly with soil temperature but varied quadratically with soil moisture in the three forest soils. Conclusions: This study demonstrated that the power function model was much more accurate than the exponential decay model in describing the decomposition dynamics of soil organic carbon (SOC) in mineral soils of subtropical forests. The empirical relations and parameter values derived from this incubation study may be incorporated into process-based ecosystem models to simulate Rh responses to climate changes.