Environmental drivers of methane fluxes from an urban temperate wetland park

Morin, T. H.; Bohrer, G.; Frasson, R. P. d. M.; Naor‐Azreli, L.; Mesi, S.; Stefanik, K. C.; Schäfer, K. V. R.

doi:10.1002/2014JG002750

Title: Environmental drivers of methane fluxes from an urban temperate wetland park

Journal Article · Fri Nov 28 00:00:00 EST 2014 · Journal of Geophysical Research. Biogeosciences

DOI:https://doi.org/10.1002/2014JG002750· OSTI ID:1402256

Morin, T. H. ^[1]; Bohrer, G. ^[1]; Frasson, R. P. d. M. ^[1]; Naor‐Azreli, L. ^[1]; Mesi, S. ^[1]; Stefanik, K. C. ^[1]; Schäfer, K. V. R. ^[2]

Department of Civil and Environmental Engineering and Geodetic Science Ohio State University Columbus Ohio USA
Department of Biological Sciences Rutgers University Newark New Jersey USA

Abstract Methane (CH ₄ ) emissions were measured at the Wilma H. Schiermeier Olentangy River Wetland Research Park (ORWRP) over three summers and two winters using an eddy covariance system. We used an empirical model to determine the main environmental drivers of methane emissions. Methane emissions covary strongly with water vapor fluxes, CO ₂ fluxes, and soil temperature. We adjust our models to account for the heterogeneous environment of the wetland by including the flux footprint distribution among different microsites as a predictive variable in the methane model. We used a forward linear stepwise model in combination with an Akaike information criteria‐based model selection process and neural network modeling to determine which environmental variables are most effective in modeling methane emissions in our site. Different models and environmental variables best represented methane fluxes in the winter and summer and also during the day or night within each season. We parameterized an optimal empirical model for methane emissions from the ORWRP that is used for gap filling of site‐level methane fluxes over 2 years. Some of the most effective variables for modeling methane were carbon, water vapor, and heat fluxes, all of which typically have the same data gaps as the time series of methane flux. In order to determine if these variables were useful for modeling methane despite the additional gap‐filling error, we determined through an error propagation experiment that eddy covariance gap‐filling models for methane may be best developed by including other gap‐filled fluxes as predictors, despite the high level of shared gaps and subsequent gap‐fill error propagation.

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Sponsoring Organization:: USDOE

OSTI ID:: 1402256

Journal Information:: Journal of Geophysical Research. Biogeosciences, Journal Name: Journal of Geophysical Research. Biogeosciences Vol. 119 Journal Issue: 11; ISSN 2169-8953

Publisher:: American Geophysical Union (AGU)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 52 works

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