Scaling Microbial Functions from Molecule to the Globe: Integrated Experiment-Model Approaches
Wednesday, August 12, 2015: 8:00 AM-11:30 AM
327, Baltimore Convention Center
Steven D. Allison
Soil carbon (C) is the largest organic C pool in terrestrial biosphere and soil responses to climate change represent a major portion of uncertainty in global carbon cycle. Microbial communities are the primary drivers of soil organic matter (SOM) decomposition and thus accounting for the response of soil microbial communities to environmental parameters in Earth system models hold promise for improving predictions of climate effects on soil decomposition, yet the regulatory mechanisms governing microbial processes remain a major gap in understanding soil responses to climate change. Field and laboratory experiments have been deployed across a wide range of ecosystems and advanced our mechanistic understanding of microbial regulation of soil decay. Extracellular enzymes produced by microbes are responsible for the degradation of complex organic C that is ultimately taken up by microbial biomass and released to the atmosphere as CO2. In contrast to the assumptions of conventional first-order decomposition models, SOM decomposition rates depend on not only the size of the soil C pool but also on the size and composition of the decomposer microbe pool. As climate changes, soil carbon stocks will likely depend on sequestration and loss pathways regulated by microbial physiology, and first-order models may have difficulty simulating climate responses over short time scales. Yet even with recent integration of microbial components in global models, nearly 50% of the spatial variation in global soil C stocks is still unexplained. Therefore, identifying accurate and simple models at microbial to large spatial scales is essential for improving global soil models. A data-model integration approach could help facilitate both experimental investigation and modeling representation of microbial processes to simulate soil-climate interactions and feedbacks. Our session invites papers that address this topic by employing field and laboratory experiments, modeling analysis, data synthesis and assimilation approaches at the molecular, community, ecosystem, regional to global scales.