Integrating microbial ecology into ecosystem models: challenges and priorities |
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Authors: | Kathleen K. Treseder Teri C. Balser Mark A. Bradford Eoin L. Brodie Eric A. Dubinsky Valerie T. Eviner Kirsten S. Hofmockel Jay T. Lennon Uri Y. Levine Barbara J. MacGregor Jennifer Pett-Ridge Mark P. Waldrop |
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Affiliation: | 1. Department of Ecology and Evolutionary Biology, University of California, Irvine, CA, 92697, USA 2. Department of Soil Science, University of Wisconsin—Madison, Madison, WI, 53706, USA 3. School of Forestry and Environmental Studies, Yale University, New Haven, CT, 06511, USA 4. Center for Environmental Biotechnology, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA 5. Department of Plant Sciences, University of California Davis, Davis, CA, 95616, USA 6. Department of Ecology, Evolution, & Organismal Biology, Iowa State University, Ames, IA, 50011, USA 7. W. K. Kellogg Biological Station and the Department of Microbiology & Molecular Genetics, Michigan State University, Hickory Corners, MI, 49060, USA 8. Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, 48824, USA 9. Department of Marine Sciences, University of North Carolina, Chapel Hill, NC, 27599, USA 10. NanoSIMS Group, Chemical Sciences Division, Lawrence Livermore National Lab, Livermore, CA, 94551-9900, USA 11. U.S. Geological Survey, 345 Middlefield Road, M.S. 962, Menlo Park, CA, 94025, USA
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Abstract: | 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. |
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