OOS 41-2
Tradeoffs in incorporating microbial function into soil organic carbon decomposition models

Wednesday, August 12, 2015: 8:20 AM
327, Baltimore Convention Center
Melanie A. Mayes, Environmental Sciences Division & Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Jiang Jiang, Department of Ecology and Evolutionary Biology, University of Tennessee
Gangsheng Wang, Environmental Sciences Division & Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Aimee Classen, University of Copenhagen
Chris W. Schadt, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN
Christine V. Hawkes, Integrative Biology, University of Texas, Austin, TX
Tim Keitt, Section of Integrative Biology, The University of Texas at Austin, Austin, TX
Background/Question/Methods

There is tremendous interest in improving the representation of below-ground functions of Earth System Models (ESM), which typically rely on first-order decomposition rates, conceptual soil pools, and empirical responses to changes in temperature and moisture.  The ecological community has responded with a number of new models that incorporate microbial and enzyme dynamics.  In this talk we focus on two major issues that inhibit full application of microbial dynamics into ESMs.  We will review existing models and demonstrate potential solutions. 

Results/Conclusions

First, a major justification of including microbes is their physiological ability to acclimate to new temperature and moisture conditions, such as by changing their carbon use efficiency. Acclimation could result from physiological changes, community shifts or evolutionary adaptation. We believe we understand physiological acclimation, but we lack a consistent understanding of the extent to which community shifts might negate or enhance physiological acclimation.  Multiple microbial functional groups would be necessary to consider community shifts, but how those groups should be defined is uncertain, and any representation adds considerable complexity to a model.  Second, a more mechanistic representation of decomposition implies a large range of residence times of soil carbon pools, which imparts oscillation behaviors from non-linear microbial and enzyme kinetics in future predictions of pool sizes.  An optimal balance between short temporal and small spatial dynamics, and long-term and large spatial scales is needed to include more mechanistic details into ESMs. We will present model simulations and testing to balance short- and long-term dynamics and multiple microbial functional groups.