OOS 72-8
Modeling carbon use efficiency at multiple levels of system complexity

Thursday, August 13, 2015: 4:00 PM
315, Baltimore Convention Center
Emily Kyker-Snowman, Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH
Kevin M. Geyer, Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH
Will R. Wieder, TSS / CGD, National Center for Atmospheric Research, Boulder, CO
A. Stuart Grandy, Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH
Serita D. Frey, Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH
Background/Question/Methods

The concept of carbon use efficiency (defined as the proportion of a metabolized substrate that becomes microbial biomass rather than respired as CO2) has been applied and measured in biological systems ranging in scale from metabolic pathways to whole ecosystems. Different systems often display different patterns in the way efficiency responds to environmental conditions like substrate availability or temperature. These diverging patterns are generally attributed to differences in measurement methods, and no unifying framework has yet been established that can reconcile contradictions between systems. However, many of the systems in which efficiency is evaluated are hierarchically nested (e.g., metabolic pathways within the cell or cells within a microbial community), with each hierarchical level integrating the processes of the levels below it. These nested systems may not be easy to disentangle experimentally, but a model that integrates processes across multiple levels could serve to unify efficiency theory and explain divergent patterns. This study used the MIcrobial-MIneral Carbon Stabilization model (MIMICS) to calculate efficiency within the same simulation for a single cell, a mixed microbial community, and a community interacting with the soil mineral matrix. The response of each modeled efficiency measure to gradients in environmental conditions was compared against published trends.

Results/Conclusions

In addition to the three hierarchical levels described above, several other definitions of efficiency were included to simulate different measurement techniques, including methods relying on microbial respiration, substrate uptake, and/or isotopic tracer measurements. MIMICS predicted shifts in each efficiency measure across a range of environmental factors, including time (ranging from several hours to several years), temperature, substrate quantity and quality, and soil texture. Depending on the simulated system and method, different efficiency measures converged or diverged along each environmental gradient. The model replicated trends in microbial efficiency found in the published literature, including the convergence over time of uptake-based methods in soils and underlying thermodynamic limits. MIMICS also provided several mechanistic hypotheses for diverging efficiency trends. Evaluating efficiency in a modeling framework may help reconcile differences and unify efficiency theory across systems.