Wetland in situ zero resistance ammetry measurements demonstrate hourly microbial activity and can be used to evaluate process-based model microbial respiration estimates

Ecosys Processed-based Modeling of Microbial Activity in a Freshwater Marsh Overview This repository contains code and analysis used to simulate microbial activity in the freshwater, temperate marsh Old Woman Creek National Estuarine Research Reserve (OWC NERR) in Huron, Ohio using the ecosys process-based model (Grant 1997). Ecosys model outputs of microbial activity (g soil C consumed/hourly) are evaluated against high-frequency electrochemical measurements from a zero-resistance ammetry (ZRA) sensor. This novel sensor produces near-real-time measurements of electron transfer processes (current) in wetland sediments at decreasing depths, which we use as a proxy for microbial activity. ZRA field measurements used in this project were collected between September and December 2023. We first ensured that the model was adequately simulating carbon flux dynamics, evaluated with eddy covariance and chamber measurements, prior to modeling the microbes: See: https://github.com/erhasset/ecosys_carbon Hassett, Erin, Gil Bohrer, Lauren Kinsman-Costello, Yvette Onyango, Talia Pope, Chelsea Smith, Justine Missik et al. "Changes in inundation drive carbon dioxide and methane fluxes in a temperate wetland." Science of the Total Environment 915 (2024): 170089. What This Project Does This project integrates process-based modeling and electrochemical microbial activity data to evaluate microbial processes in wetland sediments. Specifically, this repository includes and/or references workflows to: Simulate carbon cycling and microbial processes in a freshwater marsh using the ecosys processed-based model. Integrate zero-resistance ammetry (ZRA) sensor data to assess microbial electron transfer dynamics in wetland sediments. Optimize key model parameters using Bayesian optimization. Compare modeled microbial activity (g soil C consumed/hourly) with high-frequency (hourly) electrochemical measurements of microbial activity (current, a proxy for microbial activity). Why This Project Is Useful Wetlands are globally important sources and sinks of greenhouse gases, but microbial processes controlling these fluxes are difficult to observe directly and are often poorly represented in ecosystem models. This project advances wetland modeling by: Improving greenhouse gas modeling in wetlands using a process-based ecosystem model Providing one of the first evaluations of microbial processes in a process-based ecosystem model using real, high-frequency microbial activity measurements Integrating electrochemical sensor data with ecosystem modeling to better constrain microbial dynamics By combining ecosystem modeling, Bayesian optimization, and electrochemical microbial measurements, this work provides a new framework for evaluating how microbial activity influences greenhouse gas emissions from wetlands. Data Used for Model Evaluation Chamber Flux Measurements Hassett E ; Villa J ; Onyango Y ; Eberhard E ; Bohrer G ; Kinsman-Costello L ; Morin T (2023)Carbon flux measurements from chambers collected between July to October 2022 at Old Woman Creek, Huron, Ohio.Rewriting the Redox Paradigm: Dynamic hydrology shapes nutrient and element transformations in a Great Lakes Coastal Estuary.ESS-DIVE Dataset.https://doi.org/10.15485/2229438 Hassett E ; Villa J ; Bohrer G ; Kinsman-Costello L ; Eberhard E ; Carnevali J ; Brown M ; Martin S ; Morin T (2025)Carbon flux measurements from chambers collected between April to October 2023 at Old Woman Creek, Huron, Ohio.ESS-DIVE Dataset.https://doi.org/10.15485/3003419 Eddy Covariance Data Bohrer, G., & Kerns, J. (2024)AmeriFlux BASE US-OWC Old Woman Creek, Ver. 5-5.AmeriFlux AMP Dataset.https://doi.org/10.17190/AMF/1418679 Supporting Publication The modeling framework builds on previous work: Hassett E, Bohrer G, Kinsman-Costello L, et al. Changes in inundation drive carbon dioxide and methane fluxes in a temperate wetland. Science of The Total Environment. 2024; 915, 170089. https://doi.org/10.1016/j.scitotenv.2024.170089 Morin, Timothy H., William J. Riley, Robert F. Grant, Zelalem Mekonnen, Kay C. Stefanik, A. Camilo Rey Sanchez, Molly A. Mulhare, Jorge Villa, Kelly Wrighton, and Gil Bohrer. "Water level changes in Lake Erie drive 21st century CO2 and CH4 fluxes from a coastal temperate wetland." Science of the Total Environment 821 (2022): 153087. Model Parameter Optimization Model parameters were optimized using Bayesian Optimization for Anything (BOA), an open-source framework designed to make Bayesian optimization accessible for environmental modeling. Scyphers, M., Missik, J., Kujawa, H., Paulson, J., & Bohrer, G. (2024)Bayesian Optimization for Anything (BOA): An open-source framework for accessible, user-friendly Bayesian optimization.Environmental Modelling & Softwarehttps://doi.org/10.1016/j.envsoft.2024.106191 Scyphers, M., Missik, J., Paulson, J., & Bohrer, G. (2024)Bayesian Optimization for Anything (BOA) [Computer software]https://doi.org/10.5281/zenodo.12797033 Additional Dataset Related to the Microbial Activity Heard T ; Eberhard E ; Weerasinghe S ; Kinsman-Costello L ; Monty C ; Morin T ; Senko J (2025)Old Woman Creek Wetland Sediment and Electrochemical Sensor Microbial Community, 2023ESS-DIVE Datasethttps://doi.org/10.15485/2568076