https://dx.doi.org/10.1002/2016MS000817">
 

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Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

Abstract

Climate change is expected to have significant and uncertain impacts on methane (CH4) emissions from northern peatlands. Biogeochemical models can extrapolate site-specificCH4 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 hydrogenotrophic methanogenesis (AM and HM) to CH4 production, and predicts the C isotopic signature (δ13C) 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 δ13C in emitted CH4 (δ13C-CH4), a measure of the integrated effects of microbial production and consumption, and of physical transport. We also investigated the sensitivity of simulated δ13C-CH4 to C isotopic composition of substrates and, to fractionation factors for CH4 production (αAM and αHM), CH4 oxidation (αMO), and plant-mediated CH4 transport (αTP). The sensitivity analysis indicated that the δ13C-CH4 is highly sensitive to the factors associated with microbial metabolism (αAM, αHM, and αMO). 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.

Publication Date

6-13-2017

Journal Title

Journal of Advances in Modeling Earth Systems

Publisher

American Geophysical Union (AGU)

Digital Object Identifier (DOI)

https://dx.doi.org/10.1002/2016MS000817

Document Type

Article

Rights

© 2017. The Authors.

Comments

This is an article published by AGU in Journal of Advances in Modeling Earth Systems in 2017, available online: https://dx.doi.org/10.1002/2016MS000817

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