Microbial Community Analyses Inform Geochemical Reaction Network Models for Predicting Pathways of Greenhouse Gas Production
AuthorWilson, Rachel M.
Neumann, Rebecca B.
Crossen, Kelsey B.
Raab, Nicole M.
Hodgkins, Suzanne B.
Saleska, Scott R.
Woodcroft, Ben J.
Tyson, Gene W.
Chanton, Jeffrey P.
Rich, Virginia I.
AffiliationUniv Arizona, Dept Soil Water & Environm Sci
MetadataShow full item record
PublisherFRONTIERS MEDIA SA
CitationWilson RM, Neumann RB, Crossen KB, Raab NM, Hodgkins SB, Saleska SR, Bolduc B, Woodcroft BJ, Tyson GW, Chanton JP and Rich VI (2019) Microbial Community Analyses Inform Geochemical Reaction Network Models for Predicting Pathways of Greenhouse Gas Production. Front. Earth Sci. 7:59. doi: 10.3389/feart.2019.00059
JournalFRONTIERS IN EARTH SCIENCE
RightsCopyright © 2019 Wilson, Neumann, Crossen, Raab, Hodgkins, Saleska, Bolduc, Woodcroft, Tyson, Chanton and Rich. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Collection InformationThis 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 email@example.com.
AbstractThe mechanisms, pathways, and rates of CO2 and CH4 production are central to understanding carbon cycling and greenhouse gas flux in wetlands. Thawing permafrost regions are of particular interest because they are disproportionally affected by climate warming and store large reservoirs of organic C that may be readily converted to CO2 and CH4 upon thaw. This conversion is accomplished by a community of microorganisms interacting in complex ways to transform large organic compounds into fatty acids and ultimately CO2 and CH4. While the central role of microbes in this process is well-known, geochemical rate models rarely integrate microbiological information. Herein, we expanded the geochemical rate model of Neumann et al., (2016, Biogeochemistry 127: 57-87) to incorporate a Bayesian probability analysis and applied the result to quantifying rates of CO2, CH4, and acetate production in closed-system incubations of peat collected from three habitats along a permafrost thaw gradient. The goals of this analysis were twofold. First, we integrated microbial community analyses with geochemical rate modeling by using microbial data to inform the best model choice among equally mathematically feasible model variants. Second, based on model results, we described changes in organic carbon transformation among habitats to understand the changing pathways of greenhouse gas production along the permafrost thaw gradient. We found that acetoclasty, hydrogenotrophy, CO2 production, and homoacetogenesis were the important reactions in this system, with little evidence for anaerobic CH4 oxidation. There was a distinct transition in the reactions across the thaw gradient. The collapsed palsa stage presents an initial disequilibrium where the abrupt (physically and temporally) change in elevation introduces freshly fixed carbon into anoxic conditions then fermentation products build up over time as the system transitions through the acid phase and electron acceptors are depleted. In the bog, fermentation slows, while methanogenesis increases. In the fully thawed fen, most of the terminal electron acceptors are depleted and the system becomes increasingly methanogenic. This suggests that as permafrost regions thaw and dry palsas transition into wet fens, CH4 emissions will rise, increasing the warming potential of these systems and accelerating climate warming feedbacks.
NoteOpen access journal
VersionFinal published version
SponsorsGenomic Science Program of the United States Department of Energy, Office of Science, Office of Biological and Environmental Research [DE-SC0010580, DE-SC0016440, DE-SC0010338]; Genomic Science Program of the United States DOE Office of Biological and Environmental Research [DE-SC0010580, DE-SC0016440]; Office of Biological and environmental Research; [DE-AC02-05CH11231]; [DE-AC05-76RL01830]