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dc.contributor.authorDeng, Jia
dc.contributor.authorMcCalley, Carmody K
dc.contributor.authorFrolking, Steve
dc.contributor.authorChanton, Jeff
dc.contributor.authorCrill, Patrick
dc.contributor.authorVarner, Ruth
dc.contributor.authorTyson, Gene
dc.contributor.authorRich, Virginia
dc.contributor.authorHines, Mark
dc.contributor.authorSaleska, Scott R.
dc.contributor.authorLi, Changsheng
dc.date.accessioned2017-08-09T22:59:45Z
dc.date.available2017-08-09T22:59:45Z
dc.date.issued2017-06
dc.identifier.citationAdding stable carbon isotopes improves model representation of the role of microbial communities in peatland methane cycling 2017, 9 (2):1412 Journal of Advances in Modeling Earth Systemsen
dc.identifier.issn19422466
dc.identifier.doi10.1002/2016MS000817
dc.identifier.urihttp://hdl.handle.net/10150/625198
dc.description.abstractClimate change is expected to have significant and uncertain impacts on methane (CH4) emissions from northern peatlands. Biogeochemical models can extrapolate site-specificCH(4) measurements to larger scales and predict responses of CH4 emissions to environmental changes. However, these models include considerable uncertainties and limitations in representing CH4 production, consumption, and transport processes. To improve predictions of CH4 transformations, we incorporated acetate and stable carbon (C) isotopic dynamics associated with CH4 cycling into a biogeochemistry model, DNDC. By including these new features, DNDC explicitly simulates acetate dynamics and the relative contribution of acetotrophic and hydro-genotrophic methanogenesis (AM and HM) to CH4 production, and predicts the C isotopic signature (delta C-13) in soil C pools and emitted gases. When tested against biogeochemical and microbial community observations at two sites in a zone of thawing permafrost in a subarctic peatland in Sweden, the new formulation substantially improved agreement with CH4 production pathways and delta C-13 in emitted CH4 (delta C-13-CH4), a measure of the integrated effects of microbial production and consumption, and of physical transport. We also investigated the sensitivity of simulated delta C-13-CH4 to C isotopic composition of substrates and, to fractionation factors for CH4 production (alpha(AM) and alpha(HM)), CH4 oxidation (alpha(MO)), and plant-mediated CH4 transport (alpha(TP)). The sensitivity analysis indicated that the delta C-13-CH4 is highly sensitive to the factors associated with microbial metabolism (alpha(AM), alpha(HM), and alpha(MO)). The model framework simulating stable C isotopic dynamics provides a robust basis for better constraining and testing microbial mechanisms in predicting CH4 cycling in peatlands.
dc.description.sponsorshipU.S. Department of Energy [DE-SC0004632, DE-SC0010580]; U.S. National Science Foundation (MacroSystems Biology) [1241937]; Northern Ecosystems Research for undergraduates REU Site (NSF EAR) [1063037]; Vetenskapradet (DR) [2007-4547, 2013-5562]en
dc.language.isoenen
dc.publisherAMER GEOPHYSICAL UNIONen
dc.relation.urlhttp://doi.wiley.com/10.1002/2016MS000817en
dc.rights© 2017. The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License.en
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectmethaneen
dc.subjectstable carbon isotopeen
dc.subjectbiogeochemistryen
dc.subjectpeatlandsen
dc.subjectDNDCen
dc.titleAdding stable carbon isotopes improves model representation of the role of microbial communities in peatland methane cyclingen
dc.typeArticleen
dc.contributor.departmentUniv Arizona, Dept Ecol & Evolutionary Biolen
dc.identifier.journalJournal of Advances in Modeling Earth Systemsen
dc.description.noteOpen access journal.en
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
dc.contributor.institutionEarth Systems Research Center, Institute for the Study of Earth, Oceans and Space, University of New Hampshire; Durham New Hampshire USA
dc.contributor.institutionThomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, One Lomb Memorial Drive; Rochester New York USA
dc.contributor.institutionEarth Systems Research Center, Institute for the Study of Earth, Oceans and Space, University of New Hampshire; Durham New Hampshire USA
dc.contributor.institutionDepartment of Earth, Ocean and Atmospheric Science; Florida State University; Tallahassee Florida USA
dc.contributor.institutionDepartment of Geological Sciences; Stockholm University; Stockholm Sweden
dc.contributor.institutionEarth Systems Research Center, Institute for the Study of Earth, Oceans and Space, University of New Hampshire; Durham New Hampshire USA
dc.contributor.institutionAustralian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences; University of Queensland; Brisbane Queensland Australia
dc.contributor.institutionDepartment of Microbiology; The Ohio State University; Columbus Ohio USA
dc.contributor.institutionDepartment of Biological Sciences; University of Massachusetts Lowell; Lowell Massachusetts USA
dc.contributor.institutionDepartment of Ecology and Evolutionary Biology; University of Arizona; Tucson Arizona USA
dc.contributor.institutionEarth Systems Research Center, Institute for the Study of Earth, Oceans and Space, University of New Hampshire; Durham New Hampshire USA
refterms.dateFOA2018-06-29T20:25:39Z
html.description.abstractClimate change is expected to have significant and uncertain impacts on methane (CH4) emissions from northern peatlands. Biogeochemical models can extrapolate site-specificCH(4) measurements to larger scales and predict responses of CH4 emissions to environmental changes. However, these models include considerable uncertainties and limitations in representing CH4 production, consumption, and transport processes. To improve predictions of CH4 transformations, we incorporated acetate and stable carbon (C) isotopic dynamics associated with CH4 cycling into a biogeochemistry model, DNDC. By including these new features, DNDC explicitly simulates acetate dynamics and the relative contribution of acetotrophic and hydro-genotrophic methanogenesis (AM and HM) to CH4 production, and predicts the C isotopic signature (delta C-13) in soil C pools and emitted gases. When tested against biogeochemical and microbial community observations at two sites in a zone of thawing permafrost in a subarctic peatland in Sweden, the new formulation substantially improved agreement with CH4 production pathways and delta C-13 in emitted CH4 (delta C-13-CH4), a measure of the integrated effects of microbial production and consumption, and of physical transport. We also investigated the sensitivity of simulated delta C-13-CH4 to C isotopic composition of substrates and, to fractionation factors for CH4 production (alpha(AM) and alpha(HM)), CH4 oxidation (alpha(MO)), and plant-mediated CH4 transport (alpha(TP)). The sensitivity analysis indicated that the delta C-13-CH4 is highly sensitive to the factors associated with microbial metabolism (alpha(AM), alpha(HM), and alpha(MO)). The model framework simulating stable C isotopic dynamics provides a robust basis for better constraining and testing microbial mechanisms in predicting CH4 cycling in peatlands.


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© 2017. The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License.
Except where otherwise noted, this item's license is described as © 2017. The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License.