Poster 247 – Click on poster below to view presentation from author.
Theresia Yazbeck
Ohio State University
Co-Authors: Gil Bohrer, Qing Zhu, William Riley
Accurately predicting terrestrial net methane (CH4) fluxes from wetlands depends on multiple physical, biological, and chemical mechanisms that are poorly understood, oversimplified, or missing in regional and global biogeochemical models. The large uncertainty of CH4 fluxes and the challenging aspects of modeling them are driven, to a large degree, by the small-scale spatial and temporal heterogeneity of CH4 fluxes, the complex coupling between aboveground and belowground processes, and the complexity of meteorological, hydrological, ecological, and microbial processes that affect these fluxes. The aim of this research is to improve understanding and quantitative representation of the multiple processes that affect methane emissions at a high (patch level, vertically detailed) spatial resolution, and translate this understanding to improved modeling capability of coastal wetland fluxes using the E3SM Land Model (ELM v1) wetland CH4 biogeochemistry module. Field work will take place in Old Women Creek (OWC) wetland site in Ohio and in 3 sites in coastal wetlands in Louisiana. Flux measurements using Eddy Covariance are taken all year long. In the coming growing season, chamber and peepers’ measurements will take place, in addition to analyzing the microbiology involved in methanogenesis and methanotrophy in each site. ELM was run at the site level for OWC using site level forcing, and results matched original run with default forcing. However, observations were much higher than modelled fluxes, which could be due to the specific ecological and biological characteristic of OWC site. Future work will focus on incorporating field results in ELM, by dividing the vertical column into several columns based on patch type, and improve vertical and process resolutions of the model.
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Virtual Poster Symposium 
Interesting work. I look forward to learning more after you complete the field data collection.
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Thank you for your presentation. At this point in your project, which one of your two competing hypotheses for explaining sources of methane flux variability do you think will be best supported by your future field data collection, and why?
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