ESD welcomes Eric A. Davidson, Ph.D. (Woods Hole Research Center, MA).
Soils carbon stocks are 2-4 times greater than atmospheric CO2-C and 3-6 times larger than aboveground plant biomass-C. Potential exists for C sequestration in soils, but there is also a large potential positive feedback to climate change as permafrost thaws and enzymatic decomposition of soil organic matter increases with warming. Enzymatic reaction rates are temperature sensitive when substrate is not limiting. However, substrate supply often, perhaps usually, limits enzymatic reaction rates in soils. Soil microbial community composition varies temporally and spatially, and the reactive properties of extracellular enzymes also can probably be changed by microorganisms in response to environmental cues. The C, N, and P assimilation enabled by extracellular enzyme activity affects the growth of microbial populations, their metabolism, and their enzyme synthesis. Do models need to represent all of these processes in 3-D space and in time? Ideally, the answer would be “yes,” but only if there is a viable approach to testing and validating model structures and parameterizations representing each process. When that is not possible, some aggregation is needed. A modular design enables progress on model components without losing sight of the way that components fit together. Admittedly, the Dual Arrhenius and Michaelis–Menten (DAMM) model does not yet attain all of these lofty goals, but it offers promise to build upon an integrated, modular approach to represent as parsimoniously as possible numerous key interacting processes in a heterogeneous matrix, and to keep making improvements until we get the DAMM thing right.