OOS 33
Modeling Microbial Processes: From the Earth Down or the Microbe up?

Thursday, August 14, 2014: 8:00 AM-11:30 AM
202, Sacramento Convention Center
Xiaofeng Xu, Auburn University, AL
Joshua P. Schimel, University of California, Santa Barbara
Wyatt Hartman, Lawrence Berkeley National Laboratory
Parallel advances in developing ecosystem biogeochemical process models and characterizing soil microbial community structure suggest the potential to incorporate microbial population dynamics and physiological processes into large-scale Earth system models. However, this emerging effort faces the challenge: which processes to represent and how? From a top down modeling perspective, identifying the critical processes and then developing approaches to model them, we may lack understanding of the driving mechanisms and the data to develop parameterizations. An alternative approach is more bottom-up, working from the community data to develop relationships and develop models that explain them—but these data sets may be more complex than current ecosystem models can accommodate. For ecosystem modelers to explicitly incorporate microbial mechanisms into Earth system models, and so better simulate and predict biogeochemistry-climate feedbacks, we need to bridge the gaps between these top-down and bottom-up, model- vs. data-driven approaches to microbial dynamics and element cycling. This organized special session will invite experts to discuss current issues in the field of modeling microbial processes to predict global climate change dynamics and feedbacks. The objectives of this session are 1) to enhance communication between microbial data scientists and ecosystem modelers; 2) to review the status of microbial data for improving ecosystem models; 3) to promote designing laboratory and field experiments to test and parameterize models of microbial processes, and 4) to identify opportunities for data-model integration to better simulate and predict biogeochemical feedbacks in the earth-climate system. Speakers will identify critical knowledge gaps and present case studies illustrating both data-guided model development, and model-driven experiments to determine appropriate mechanisms and improve data synthesis. Case study presentations will be contextualized by opening and closing talks emphasizing the overall progress and gaps in the field, and opportunities for future collaboration to improve synthesis of modeling and data-driven process studies. The significance of data-model integration as a mechanism to advance understanding of microbial processes, including carbon and nutrient cycling, and trace gas fluxes will be emphasized. Progress in these areas and the data-model integration process will be of interest to many members of ESA including microbiologists, ecosystem ecologists, ecosystem modelers, and data scientists.
8:20 AM
 Exoenzymes: Are they the secret to capturing non-equilibrium in microbe-SOM system?
Joshua P. Schimel, University of California, Santa Barbara
8:40 AM
 Theoretical modeling C- and N- acquiring exoenzyme activities to balance microbial demands during decomposition
Daryl L. Moorhead, University of Toledo; Gwenaëlle Lashermes, Institut National de la Recherche Agronomique; Robert L. Sinsabaugh, University of New Mexico; Michael N. Weintraub, University of Toledo
9:20 AM
 Integrating microbial eco-physiological responses to drought and nutrient limitation into ecosystem models
Stefano Manzoni, Swedish University of Agricultural Sciences; Sean M. Schaeffer, University of Tennessee, Knoxville; Joshua P. Schimel, University of California, Santa Barbara; Gabriel G. Katul, Duke University; Thomas Kätterer, Swedish University of Agricultural Sciences; Göran Ågren, Swedish University of Agricultural Sciences; Amilcare Porporato, Duke University
9:40 AM
9:50 AM
 Merging microbial traits and soil physiochemical interactions with the MIMICS (MIcrobial-MIneral Carbon Stabilization) model
Will R. Wieder, University of Colorado; A. Stuart Grandy, University of New Hampshire; Cynthia Kallenbach, University of New Hampshire; Eve-Lyn S. Hinckley, National Ecological Observatory Network (NEON, Inc.); Gordon Bonan, NCAR
10:10 AM
 A Bayesian hierarchical approach for estimating microbial community compositions assessed using two sets of primers via polymerase chain reaction
Nels G. Johnson, Colorado State University; Akihiro Koyama, Algoma University; Joe C. von Fischer, Colorado State University; Colleen T. Webb, Colorado State University
10:30 AM
 Observational and experimental constraints on global scale microbial models to improve climate prediction
Peter E. Thornton, Oak Ridge National Laboratory; Melanie A. Mayes, Oak Ridge National Laboratory; Guoping Tang, Oak Ridge National Laboratory; Xiaofeng Xu, Auburn University, AL; Gangsheng Wang, Oak Ridge National Laboratory; Xiaojuan Yang, Oak Ridge National Laboratory
10:50 AM
 Genome informed trait-based models for improved prediction of microbial dynamics and biogeochemical rates
Eoin Brodie, Lawrence Berkeley National Laboratory; Eric King, Lawrence Berkeley National Laboratory; Jinyun Tang, Lawrence Berkeley National Laboratory; Yiwei Cheng, Lawrence Berkeley National Laboratory; Ulas Karaoz, Lawrence Berkeley National Laboratory; Sergi Molins, Lawrence Berkeley National Laboratory; William Riley, Lawrence Berkeley National Laboratory; Nicholas J. Bouskill, Lawrence Berkeley National Laboratory
11:10 AM
 Developing next-generation trace gas models: challenges and direction
Xiaofeng Xu, Auburn University, AL; Peter E. Thornton, Oak Ridge National Laboratory; Hanqin Tian, Auburn University; Stan D. Wullschleger, Oak Ridge National Laboratory