Wetland in situ zero resistance ammetry measurements demonstrate hourly microbial activity and can be used to evaluate process-based model microbial respiration estimates
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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
淡水沼泽微生物活性的ecosys过程模型模拟 ## 研究概况 本研究仓库包含利用ecosys过程模型（ecosys process-based model，Grant 1997）模拟美国俄亥俄州休伦市老妇人溪国家河口研究保护区（Old Woman Creek National Estuarine Research Reserve，OWC NERR）内温带淡水沼泽的微生物活性的代码与分析脚本。 本研究以零电阻安培计（zero-resistance ammetry，ZRA）传感器采集的高频电化学测量数据为参照，对ecosys模型输出的微生物活性（单位：克土壤碳/每小时消耗量）进行评估。该新型传感器可对不同深度的湿地沉积物中的电子传递过程（电流）进行近实时测量，我们将其作为微生物活性的替代指标。本项目使用的ZRA野外测量数据采集于2023年9月至12月期间。 在开展微生物模拟研究之前，我们首先通过涡度协方差和箱式测量数据验证了模型对碳通量动态的模拟能力： 详见：https://github.com/erhasset/ecosys_carbon Hassett, Erin, Gil Bohrer, Lauren Kinsman-Costello, Yvette Onyango, Talia Pope, Chelsea Smith, Justine Missik 等. 淹水变化驱动温带湿地的二氧化碳与甲烷通量[J]. 总环境科学, 2024, 915: 170089. ## 本项目研究内容 本项目将过程基建模与电化学微生物活性数据相结合，以评估湿地沉积物中的微生物过程。具体而言，本仓库包含并/或引用以下工作流程： 1. 利用ecosys过程模型模拟淡水沼泽的碳循环与微生物过程； 2. 整合零电阻安培计（ZRA）传感器数据，评估湿地沉积物中的微生物电子传递动态； 3. 采用贝叶斯优化方法对模型关键参数进行率定； 4. 将模拟得到的微生物活性（单位：克土壤碳/每小时消耗量）与高频（每小时级）电化学微生物活性测量数据（电流，即微生物活性的替代指标）进行对比。 ## 本项目的研究价值 湿地是全球重要的温室气体源与汇，但调控温室气体通量的微生物过程难以直接观测，且现有生态系统模型对该过程的表征往往不足。本项目通过以下方式推动湿地建模研究： - 基于过程基生态系统模型优化湿地的温室气体模拟； - 利用真实的高频微生物活性测量数据，实现过程基生态系统模型中微生物过程的首批评估之一； - 将电化学传感器数据与生态系统建模相结合，以更好地约束微生物动态。 本研究将生态系统建模、贝叶斯优化与电化学微生物测量相结合，为评估微生物活性如何影响湿地温室气体排放提供了全新的分析框架。 ## 模型评估所用数据集 ### 箱式通量测量数据 1. Hassett E, Villa J, Onyango Y, Eberhard E, Bohrer G, Kinsman-Costello L, Morin T (2023). 2022年7月至10月于俄亥俄州休伦市老妇人溪采集的箱式碳通量测量数据[数据集]. 《改写氧化还原范式：动态水文塑造大湖沿岸河口的营养与元素转化》. ESS-DIVE数据集. https://doi.org/10.15485/2229438 2. Hassett E, Villa J, Bohrer G, Kinsman-Costello L, Eberhard E, Carnevali J, Brown M, Martin S, Morin T (2025). 2023年4月至10月于俄亥俄州休伦市老妇人溪采集的箱式碳通量测量数据[数据集]. ESS-DIVE数据集. https://doi.org/10.15485/3003419 ### 涡度协方差数据 Bohrer G, Kerns J (2024). AmeriFlux BASE US-OWC 老妇人溪，版本5-5[数据集]. AmeriFlux AMP数据集. https://doi.org/10.17190/AMF/1418679 ## 支撑性发表文献 本建模框架基于此前的研究成果： 1. Hassett E, Bohrer G, Kinsman-Costello L, 等. 淹水变化驱动温带湿地的二氧化碳与甲烷通量[J]. 总环境科学, 2024, 915: 170089. https://doi.org/10.1016/j.scitotenv.2024.170089 2. Morin TH, Riley WJ, Grant RF, 等. 伊利湖水位变化驱动沿岸温带湿地21世纪的CO2与CH4通量[J]. 总环境科学, 2022, 821: 153087. ## 模型参数率定 本研究采用贝叶斯优化工具包（Bayesian Optimization for Anything，BOA）对模型参数进行率定，该开源框架旨在为环境建模提供易用的贝叶斯优化方案。 1. Scyphers M, Missik J, Kujawa H, Paulson J, Bohrer G (2024). 贝叶斯优化工具包（BOA）：面向环境建模的开源易用贝叶斯优化框架[J]. 环境建模与软件, https://doi.org/10.1016/j.envsoft.2024.106191 2. Scyphers M, Missik J, Paulson J, Bohrer G (2024). 贝叶斯优化工具包（BOA）[计算机软件]. https://doi.org/10.5281/zenodo.12797033 ## 微生物活性相关补充数据集 Heard T, Eberhard E, Weerasinghe S, Kinsman-Costello L, Monty C, Morin T, Senko J (2025). 2023年老妇人溪湿地沉积物与电化学传感器微生物群落[数据集]. ESS-DIVE数据集. https://doi.org/10.15485/2568076
