Publication

Simulation models have played an important role in the development of terrestrial biogeochemistry. One contemporary application of biogeochemical models is simulating interactions between global climate change and terrestrial carbon balance. The largest global pool of terrestrial carbon is detrital (nonliving) soil organic matter, and one ongoing debate is whether warmer temperatures will increase the amount of soil C released to the atmosphere via microbial decomposition (oxidation to CO2) While much of the literature suggests that decomposition rates increase with temperature, several recent papers cast doubt on this general conclusion. Given the difficulty of directly estimating field rates of total organic matter decomposition, models are playing an important role in assessing how ecosystem carbon balance will respond to global change. We evaluated a suite of models to ask three main questions: (1) What are the nature and origin of the equations used to simulate organic matter decomposition? (2) Is there a consensus understanding of the role of temperature in controlling decomposition? and (3) How well do these models serve as resources for the scientific community? Our review resulted in several important conclusions. First, current models of decomposition are based on very few empirical studies of the process. Instead, soil organic matter decomposition is simulated using data from soil respiration, short-term laboratory studies, or decomposition of recently senesced foliage. Second, while most models represent decomposition as a process that increases with temperature, the shape of the temperature decomposition curve, and their interactions with soil moisture varied among the models. Ultimately, the development of realistic, mechanistically based models of organic matter decomposition is limited by field data. There is a strong need for long-term experiments with estimates of detrital inputs and detrital pools to test the understanding of decomposition currently incorporated into simulation models. Finally, our evaluation of the models was limited by incomplete documentation of the source of the relationships used in the model and by the evolution of the models through time.