, Volume 109, Issue 1, pp 7–18

Integrating microbial ecology into ecosystem models: challenges and priorities


    • Department of Ecology and Evolutionary BiologyUniversity of California
  • Teri C. Balser
    • Department of Soil ScienceUniversity of Wisconsin—Madison
  • Mark A. Bradford
    • School of Forestry and Environmental StudiesYale University
  • Eoin L. Brodie
    • Center for Environmental BiotechnologyLawrence Berkeley National Laboratory
  • Eric A. Dubinsky
    • Center for Environmental BiotechnologyLawrence Berkeley National Laboratory
  • Valerie T. Eviner
    • Department of Plant SciencesUniversity of California Davis
  • Kirsten S. Hofmockel
    • Department of Ecology, Evolution, & Organismal BiologyIowa State University
  • Jay T. Lennon
    • W. K. Kellogg Biological Station and the Department of Microbiology & Molecular GeneticsMichigan State University
  • Uri Y. Levine
    • Department of Microbiology and Molecular GeneticsMichigan State University
  • Barbara J. MacGregor
    • Department of Marine SciencesUniversity of North Carolina
  • Jennifer Pett-Ridge
    • NanoSIMS Group, Chemical Sciences DivisionLawrence Livermore National Lab
  • Mark P. Waldrop
    • U.S. Geological Survey

DOI: 10.1007/s10533-011-9636-5

Cite this article as:
Treseder, K.K., Balser, T.C., Bradford, M.A. et al. Biogeochemistry (2012) 109: 7. doi:10.1007/s10533-011-9636-5


Microbial communities can potentially mediate feedbacks between global change and ecosystem function, owing to their sensitivity to environmental change and their control over critical biogeochemical processes. Numerous ecosystem models have been developed to predict global change effects, but most do not consider microbial mechanisms in detail. In this idea paper, we examine the extent to which incorporation of microbial ecology into ecosystem models improves predictions of carbon (C) dynamics under warming, changes in precipitation regime, and anthropogenic nitrogen (N) enrichment. We focus on three cases in which this approach might be especially valuable: temporal dynamics in microbial responses to environmental change, variation in ecological function within microbial communities, and N effects on microbial activity. Four microbially-based models have addressed these scenarios. In each case, predictions of the microbial-based models differ—sometimes substantially—from comparable conventional models. However, validation and parameterization of model performance is challenging. We recommend that the development of microbial-based models must occur in conjunction with the development of theoretical frameworks that predict the temporal responses of microbial communities, the phylogenetic distribution of microbial functions, and the response of microbes to N enrichment.


Community compositionFunctional groupsGlobal changeNitrogenPrecipitationTemporal dynamicsWarming

Copyright information

© Springer Science+Business Media B.V. 2011