2024 Abstracts

Simulating Greenhouse Gas Fluxes from a Terrestrial-Aquatic Interface using Microsite Probability Density Functions and Redox-Reaction Networks


Debjani Sihi1* ([email protected]), Jianqiu Zheng2, Eric Davidson3, Michael Weintraub4, Roberta Bittencourt-Peixoto4, Patrick Megonigal5


1Emory University, Atlanta, GA; 2Pacific Northwest National Laboratory, Richland, WA; 3Center for Environmental Science, Appalachian Laboratory, University of Maryland–Frostburg, MD; 4University of Toledo, Toledo, OH; 5Smithsonian Environmental Research Center, Edgewater, MD



Terrestrial-aquatic interfaces (TAIs) represent biogeochemically active and diverse systems. Soil microsites regulate oxidation-reduction (redox)-driven biogeochemical transformations and greenhouse gas (GHG) fluxes in TAIs by creating spatial heterogeneity and variations in reaction kinetics. Researchers demonstrate how microsite-scale processes manifest into ecosystem-scale functions and ultimately control GHG fluxes in these dynamic interfaces. The team quantified redox heterogeneity using intact soil cores collected from a TAI near Old Woman Creek, OH and O2 optodes. Flooding and draining events significantly shifted O2 distribution, which allowed the team to develop O2 probability distribution functions (PDFs). By constraining microsite O2 PDFs in the Dual Arrhenius and Michaelis-Menten-Greenhouse Gas (DAMM-GHG) model, researchers are quantifying spatial (across sites) and temporal (hydrology treatment) heterogeneity of GHG production and consumption processes, and evaluating model performance against observed GHG fluxes in the laboratory. Using microsite O2 PDFs, the team will explain hot spots and hot moments of GHG fluxes under fluctuating hydrology. Further, researchers are constraining redox reaction network in AquaMEND using soil structural (or pore network) heterogeneity (via X-ray Computed Tomography), and information on alternative terminal electron acceptors (via porewater measurements), and redox potential (via Eh probes). The team will further validate model performance against field measurements of GHG fluxes across the hydrology gradient in Old Woman Creek. The Model-Experiment (ModEx) framework evaluates whether explicitly representing soil microsite PDFs and redox reaction networks improve predictions of GHG fluxes from TAIs.