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DOE OSTI2026

Informing Robust Functional Relationship Benchmarks: An Evaluation of the Temperature Sensitivity of Ecosystem Respiration Across the Arctic-Boreal Region

During land model development, simulated carbon dynamics are often benchmarked against observational data sets to evaluate model performance. Functional relationship benchmarks are the relationship between a driving variable (e.g., temperature) and a response variable (e.g., ecosystem respiration) and are a promising tool for assessing model performance by evaluating modeled sensitivities to changing environmental conditions. However, observed functional relationships can be influenced by choices made during data collection and throughout the benchmarking process, impacting the inferred skill of land models. To avoid misrepresenting a model's true performance, it is necessary to systematically evaluate best practices when constructing functional relationship benchmarks. We developed a set of guidelines for constructing functional relationship benchmarks, considering the choice of data set, number of daily observations, temporal extent, and temporal resolution across Alaska and Canada over a 20-year period from 2001 to 2020. The temperature sensitivity of ecosystem respiration from observations, evaluated through an apparent Q 10 , is highly variable both spatially and as a result of the data processing approach applied in the benchmark formation. When benchmarking 13 models from the Warming Permafrost Model Intercomparison Project (WrPMIP), the range in inferred model skill is substantially impacted by the choices applied in constructing functional relationship benchmarks. The inferred performance of a given model is most sensitive to the number of daily observations and temporal extent, followed by choice of benchmark data set and temporal averaging. Results from this analysis can guide the development of consistent and robust functional relationships for future model evaluation studies.

Poe, Jeralyn [Northern Arizona University, Flagsta↗

DOE OSTI2025

Widespread underestimation of rain-induced soil carbon emissions from global drylands

Dryland carbon fluxes, particularly those driven by ecosystem respiration, are highly sensitive to water availability and rain pulses. However, the magnitude of rain-induced carbon emissions remains unclear globally. Here we quantify the impact of rain-pulse events on the carbon balance of global drylands and characterize their spatiotemporal controls. Using eddy-covariance observations of carbon, water and energy fluxes from 34 dryland sites worldwide, we produce an inventory of over 1,800 manually identified rain-induced CO2 pulse events. Based on this inventory, a machine learning algorithm is developed to automatically detect rain-induced CO2 pulse events. Our findings show that existing partitioning methods underestimate ecosystem respiration and photosynthesis by up to 30% during rain-pulse events, which annually contribute 16.9 ± 2.8% of ecosystem respiration and 9.6 ± 2.2% of net ecosystem productivity. We show that the carbon loss intensity correlates most strongly with annual productivity, aridity and soil pH. Finally, we identify a universal decay rate of rain-induced CO2 pulses and use it to bias-correct respiration estimates. Our research highlights the importance of rain-induced carbon emissions for the carbon balance of global drylands and suggests that ecosystem models may largely underrepresent the influence of rain pulses on the carbon cycle of drylands.

Nguyen, Ngoc B↗

DOE OSTI2025

Walker Branch Watershed: Daily Stream Metabolism and Organic Carbon Spiraling Metrics in the West Fork of Walker Branch, Tennessee, USA, 2004-2010

This dataset contains daily metabolism estimates of gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP), in addition to organic carbon spiraling length (SOC) and mineralization velocity (VfOC) estimates at the West Fork of Walker Branch, a small headwater stream, in the Walker Branch Watershed, Tennessee, USA. Observations were made from 2004-2010 (2004-01-01 to 2010-12-31). These data were generated to assess seasonal and interannual variability in metabolism and organic carbon spiraling and to explore potential driver variables, as analyses of intra- and interannual variability in metabolism and organic carbon spiraling are currently limited, leaving knowledge gaps in the driving mechanisms of and future changes to stream metabolism and carbon processing under climate change. Additionally, measurements of discharge (Q), stream width, stream- and canopy-level photosynthetically active radiation (PAR), water temperature, and precipitation from this time frame are included. This dataset contains one data file in comma separated (*.csv) format.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Earlier snowmelt increases the strength of the carbon sink in montane meadows unequally across the growing season

1. Warming temperatures are changing winters, leading to earlier snowmelt. This shift can lead to an earlier and potentially longer growing season, which in turn may affect various plant-mediated ecosystem functions. Despite its relevance in the carbon cycle, we still know little about how earlier snowmelt impacts the carbon balance in ecosystems over the growing season, for example, does it only shift phenology, or does it affect the overall carbon uptake? Most studies rely on interannual variability in snowmelt timing, making it difficult to isolate snowmelt effects from other confounding variables, for example, temperature and moisture anomalies. To address this uncertainty, we investigated how experimentally advancing snowmelt affects the carbon cycling of montane meadows across the growing season. 2. We experimentally advanced the snowmelt date in a montane meadow by approximately 12 days and collected data every 2 weeks throughout the growing season, including net ecosystem exchange (NEE), gross primary productivity (GPP), ecosystem respiration (ER), plant composition, and shrub, graminoid, and forb biomass. 3. Early in the growing season, GPP was higher in the early snowmelt plots, though this effect decreased as the growing season progressed. Our modelling of cumulative NEE showed a possible 22% increase in the carbon sink strength with earlier snowmelt. The effect was strongest in the early spring and diminished as the growing season progressed, with control plots being a greater carbon sink in the later season. Graminoid biomass was 47% higher in plots with earlier snowmelt, but there was no change in total biomass. 4. Synthesis. As winters warm and snowmelt occurs earlier, plant productivity will shift earlier in the growing season, and montane meadows may become a stronger carbon sink. However, this effect will differ seasonally, altering the carbon balance in montane meadows.

carbon cycle↗

DOE OSTI2025

Water Column Respiration in the Yakima River Basin is Explained by Temperature, Nutrients and Suspended Solids

Understanding aquatic ecosystem metabolism involves the study of two key processes: carbon fixation via primary production and organic C mineralization as total ecosystem respiration (ERtot). In streams and rivers, ERtot includes respiration in the water column (ERwc) and in the sediments (ERsed). While literature surveys suggest that ERsed is often a dominant contributor to ERtot, recent studies indicate that the relative influence of sediment-associated processes versus water column processes can fluctuate along the river continuum. Still, a comprehensive understanding of the factors contributing to these shifts within basins and across stream orders is needed. Here we contribute to this need by measuring ERwc and collecting water samples across 47 sites in the Yakima River basin, Washington, USA. We found that ERwc rates varied throughout the basin during baseflow conditions, ranging from –7.38 to 0.36 g O2 m?3 d?1, and encompassed the range of ERwc literature values. Additionally, by comparing to ERtot estimates for rivers across the contiguous United States, we suggest that the contribution of ERwc rates to reach-scale ERtot rates across the Yakima River was likely highly variable, but we did not test this directly. We observed that temperature, nutrient concentrations (dissolved organic carbon, total dissolved nitrogen), and total suspended solids explained 41% of ERwc variability across the basin. Our findings highlight the potential relevance of water column processes in aquatic ecosystem metabolism, with the Yakima River basin serving as an environmentally diverse river network representative of the larger Columbia River basin that spans much of the Pacific Northwest region of the United States. Our results are generally congruent with previous work, suggesting that the observed variability and suite of associated environmental factors influencing ERwc are potentially transferable across basins.

Laan, Maggi M.↗

DOE OSTI2025

Pyrogenic Organic Matter Laboratory Experiment: Aerobic Respiration and Geochemistry from Variably Inundated Stream Sediments (v3)

This dataset supports a broader study examining the effects of variable inundation and pyrogenic organic matter on ecosystem respiration. The dataset provides data generated from a laboratory batch experiment investigating the interaction between variable inundation conditions (wet and dry sediment) and pyrogenic organic matter (burned and unburned treatments). The contents include time series dissolved oxygen, sediment geochemistry data, and field metadata (including qualitative information on instream and river corridor characteristics). This data package was originally published in November 2025. It was updated in April 2026 (v2; new and modified files) and May 2026 (v3; modified files). See the change history section in the readme for more details For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) international generic sample number (IGSN) mapping file; (5) readme; (6) field protocol; (7) sample name metadata; (8) an environmental context picture for the dry and inundated sampling locations; and (9) a subfolder with sample data from the sediment incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) gravimetric moisture; (4) partial pressure and production rates of carbon dioxide, methane, and nitrous oxide; (5) field wet sediment mass, dry sediment mass, water mass, and field wet sediment volume in incubation and sediment NPOC/TN vials; (6) methods codes; (7) respiration rates, pH, and temperature from after the incubation, raw time series dissolved oxygen and temperature, and a subfolder containing associated plots and scripts; (8) ions; (9) FTICR-MS methods; and (10) a subfolder of 12 Tesla (12T) FTICR-MS data. This folder contains the CoreMS processed data and three subfolders, one containing the .xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .html, .Rmd, .py, .cal, .json, or .jpg.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Contrasting carbon dynamics in grazed and flood-prone grasslands on mineral and degraded peat soils

Ecosystem-scale methane (CH₄) flux measurements from grazed grasslands remain scarce, despite their importance for understanding grassland contributions to the global carbon budget. In this study, we present full annual budgets of both carbon dioxide (CO₂) and CH₄ derived from eddy covariance measurements at two contrasting grazed grasslands: a floodplain grassland at Marchegg, Austria, and an intensively grazed pasture at Sherman Barn, California. By combining continuous, year-round observations of CO₂ and CH₄, this study provides a rare, comparative assessment of greenhouse gas dynamics across distinct climatic, hydrological, and management regimes. Our results highlight how environmental conditions, grazing intensity, and hydrology jointly regulate CO₂ exchange and CH₄ emissions, underscoring the importance of including methane alongside net ecosystem exchange when evaluating grassland carbon balances. At Marchegg, characterized by seasonal flooding and moderate horse grazing on mineral soils, the ecosystem acted as a weak carbon sink in 2024, with a GWP 100 of 42.2 ± 113.4 g CO₂ eq m⁻². Net CO₂ uptake (–27.3 ± 30.2 g C m⁻² yr⁻¹) was partly offset by CH₄ emissions (1.6 ± 0.04 g C m⁻² yr⁻¹), which were strongly linked to soil moisture and inundation events. In contrast, Sherman Barn, a cattle pasture on degraded peat soils, was a consistent carbon source in 2019, with a GWP 100 of 567.6 ± 120.5 g CO₂ eq m⁻², associated with high ecosystem respiration during summer. The site released 125.3 ± 32.2 g C m⁻² yr⁻¹ of CO₂ and 3 ± 0.06 g C m⁻² yr⁻¹ of CH₄. Across both sites, net ecosystem exchange was primarily linked to photosynthetically active radiation and vegetation greenness, while CH₄ fluxes were related to soil moisture rather than grazing intensity. Flooding at Marchegg reduced CO₂ uptake but enhanced CH₄ emissions, highlighting the critical role of flood timing within the growing season. Moreover, inundation appeared to suppress the spread of invasive plant species, emphasizing the ecological value of dynamic hydrological regimes. Together, these findings reveal the complexity of grassland carbon budgets and the need for site-specific, year-round CO₂ and CH₄ monitoring to inform climate-adaptive management strategies.

Carbon sequestration↗

DOE OSTI2025

Observations and modeling reveal that heatwaves reduce photosynthesis, plant carbon reserves, and net carbon uptake

Heatwaves threaten ecosystem carbon balances, yet the mechanisms driving short-term carbon flux responses remain poorly understood. Here, integrating high-frequency eddy covariance (EC) data from 140 global flux tower sites (872 site-years) with detailed process-based modeling, we examine ecosystem responses during and immediately after heatwaves. We show that heatwaves caused a −40% (range [−29%, −128%]) reduction in net ecosystem productivity (NEP) compared to pre-heatwave values, with this reduction persisting over the following two weeks (−38% range [+3%, −154%]). We attributed NEP decreases to photosynthesis decreases more than to ecosystem respiration (RE) increases. Forest sites had greater NEP decreases during heatwaves than non-forest sites, but remained carbon sinks afterwards, indicating resilience. Our modeling analysis of extreme heatwaves at selected EC sites shows that decreased photosynthesis, increased maintenance respiration, and decreased plant non-structural carbon reserves during heatwaves drive carbon cycle changes that persist for weeks. Consistent with phenocam observations, we modeled a reduction in leaf area index caused by reduced non-structural carbon reserves, leading to early leaf senescence and longer-term impacts. Ongoing increases in heatwaves are therefore likely to reduce NEP across a range of ecosystems, exacerbating carbon cycle feedback.

carbon cycle↗

DOE OSTI2025

Gap-filled methane and carbon dioxide fluxes across two ecosystem states at the US-OWC AmeriFlux site (2015−2016, 2020−2022)

This dataset contains gap-filled measurements of methane flux (FCH4), net ecosystem CO2 exchange (NEE) partitioned into gross primary productivity (GPP) and ecosystem respiration (RE), as well as latent heat flux (LE) from a Great Lakes coastal freshwater wetland at the US-OWC AmeriFlux site. The dataset covers the peak growing seasons (June−September) of 2015−2016, dominated by Typha spp., and 2020−2022, characterized by floating-leaved species (lotus and water lily). These data were generated to investigate how rising water levels and vegetation shifts influence CH4 and CO2 fluxes across two distinct ecosystem states in this wetland. The dataset, provided in CSV format, includes half-hourly gap-filled flux data from June to September for 2015, 2016, 2020, 2021, and 2022. The gap-filled data refers to measurements where missing values due to instrument issues or quality control were filled using artificial neural networks (ANNs).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Hyporheic‐Zone Processes and Stream Oxygen Dynamics: Insights From a Multiscale Reactive Transport Model

Aquatic ecosystem metabolism encapsulates the daily fixation (gross primary production, GPP d ) and mineralization (ecosystem respiration, ER d ) of organic carbon. In fluvial systems, these are commonly estimated by inverse solutions to field observations using a model that describes oxygen concentrations varying in the water column in response to metabolic fluxes and air‐water gas exchange controlled by a rate coefficient (K 600 ). The most common conceptual model is the single‐station metabolism (SSM) model. The simplicity and flexibility of this conceptualization make it attractive; however, it implicitly assumes that all the processes that consume oxygen in fluvial systems can be lumped into a bulk estimate of respiration with poorly understood consequences for estimates of GPP d , ER d , and K 600 . Here, we focus on the implications of using SSM conceptualization when estimating metabolic fluxes from oxygen dynamics in channels where hyporheic exchange occurs. We use a new multiscale numerical model for reactive transport in streams that represents hyporheic exchange and streambed heterotrophic respiration. Nondimensionalization of this model reveals dimensionless groups that collectively control oxygen dynamics. Numerical experiments offer a mechanistic understanding of the impacts of hyporheic exchange on diel oxygen dynamics revealing that potential biases arise from neglecting mass transfer limitations. Specifically, we found that hyporheic exchange significantly affects diel oxygen dynamics, even for nonreactive streambed sediments. Moreover, while the SSM performs well in many situations, we find conditions where significant bias is produced by hyporheic exchange, even when oxygen data are well‐fitted. These situations pose a major challenge in the interpretation of metabolism assessment estimates.

Gomez‐Velez, Jesus D. [Oak Ridge National Laborato↗

DOE OSTI2025

Large emissions of CO 2 and CH 4 due to active-layer warming in Arctic tundra

Climate warming may accelerate decomposition of Arctic soil carbon, but few controlled experiments have manipulated the entire active layer. To determine surface-atmosphere fluxes of carbon dioxide and methane under anticipated end-of-century warming, here we used heating rods to warm (by 3.8 °C) to the depth of permafrost in polygonal tundra in $Utqia\dot{g}vik$ (formerly Barrow), Alaska and measured fluxes over two growing seasons. We show that ecosystem respiration is ~30% higher in warmed plots than in control plots (0.99 μmol m -2 s -1 versus 0.67 μmol m -2 s -1 , p < 0.0001, n = 79). Additionally, the observed temperature sensitivity (Q 10 of 2.8) is higher than that imposed for soil in Earth system models or reported by arctic experiments warming only the surface. A shoulder-season warming experiment revealed that rapid snow melt, which is becoming a more common event, can result in large methane emissions that may have otherwise been oxidized to carbon dioxide. Thus, warming promotes greenhouse gas emissions from the whole, deepening active layer and may contribute to climate change amplification.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Impacts of benchmarking choices on inferred model skill of the Arctic–Boreal terrestrial carbon cycle

Abstract Land surface models require continuous validation against observations to improve and reduce simulation uncertainty. However, inferred model performance can be heavily influenced by subjective choices made in the selection and application of observational data products. A key area often misrepresented by models is the Arctic–Boreal region, which is a potential tipping point region in Earth’s climate system due to large permafrost carbon stocks that are vulnerable to release with climate warming. We use the International Land Model Benchmarking (ILAMB) framework to evaluate how the model skill of TRENDY-v9 models varies based on the choice of observational-based benchmark and how benchmarks are applied in model evaluation. This analysis uses global datasets integrated into ILAMB and new, regionally-specific observational products from the Arctic–Boreal Vulnerability Experiment. Our results cover the overall time period of 1979–2019 and show that model scores can vary substantially depending on the data product applied, with higher model scores indicating better model performance against observations. The lowest model scores occur when benchmarked against regional, compared to global, datasets. We also evaluate observed and modeled functional relationships between ecosystem respiration and air temperature and between gross primary production and precipitation. Here, we find that the magnitude and shape of the responses are strongly impacted by the choice of observational dataset and the approach used to construct the functional relationship benchmark. These results suggest that model evaluation studies could conclude a false sense of model skill if only using a single benchmark data product or if not applying regional data products when performing a regional model analysis. Collectively, our findings highlight the influence of benchmarking choices on model evaluation and point to the need for benchmarking guidelines when assessing model skill.

Poe, Jeralyn (ORCID:0000000318495278)↗

DOE OSTI2025

Shrub Expansion Simulations at Trail Valley Creek Tundra site using E3SM Land Model (ELM) Arctic-focused Version

The warming of the Arctic is causing substantial compositional, structural, and functional changes in tundra vegetation including shrub and densification in parts of the Arctic. Assessing the impact of these changes in vegetation composition on the Arctic’s carbon and energy budgets is important to constrain projected local and global surface-atmosphere exchanges. We conduct a sensitivity analysis of the projected surface energy fluxes, soil carbon pools, and carbon dioxide fluxes (net ecosystem exchange, gross primary production, and ecosystem respiration) between present day and 2100 to different shrub expansion rates and air temperature increases under future emission scenarios (intermediate – RCP4.5, and high – RCP8.5) using the Arctic-focused version of the Energy Exascale Earth System Model (E3SM) Land Model (ELM). We focus on Trail Valley Creek (TVC), a mineral upland tundra site located in the western Canadian Arctic, which is experiencing tall shrub densification and expansion. In this study, we run TVC under two different warming scenarios RCP4.5 and RCP 8.5 and simulate different shrubification rates projected until year 2100. In this repository, we include all the forcing, input, parameters, and output data corresponding to all the simulations performed. flmd.csv includes a detailed description of the datasets files.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Warming induces unexpectedly high soil respiration in a wet tropical forest

Abstract Tropical forests are a dominant regulator of the global carbon cycle, exchanging more carbon dioxide with the atmosphere than any other terrestrial biome. Climate models predict unprecedented climatic warming in tropical regions in the coming decades; however, in situ field warming studies are severely lacking in tropical forests. Here we present results from an in situ warming experiment in Puerto Rico, where soil respiration responses to + 4 o C warming were assessed half-hourly for a year. Soil respiration rates were 42-204% higher in warmed relative to ambient plots, representing some of the highest soil respiration rates reported for any terrestrial ecosystem. While respiration rates were significantly higher in the warmed plots, the temperature sensitivity (Q 10 ) was 71.7% lower, pointing to a mechanistic shift. Even with reduced Q 10 , if observed soil respiration rates persist in a warmer world, the feedback to future climate could be considerably greater than previously predicted or observed.

Science & Technology - Other Topics↗

DOE OSTI2026

Evaluation of top-down and bottom-up global terrestrial respiration estimates and their mismatch with model simulations

Terrestrial respiration is one of the most poorly understood processes in the global carbon cycle, making respiration predictions uncertain. However, expanding observations and machine learning approaches have led to a proliferation of estimates. We compiled total ecosystem and heterotrophic respiration estimates derived from top-down atmospheric inversions and bottom-up upscaling of ecosystem observations and compared them with dynamic vegetation models (DGVM) simulations over the 1980-2020 period. Our analysis revealed a convergence in mean annual global total ecosystem respiration estimates between top-down 97.1 (± SD 6.8) PgC yr-1 and bottom-up 98.5 (+/-13.4) PgC yr-1, which were both significantly lower than the ensemble mean from DGVMs estimates 133.7 (±4.7) PgC yr-1. We also found similar temporal trends between top-down estimates with a mean of 0.075 (±0.05) PgC yr-2, and bottom-up estimates of 0.05 (±0.05) PgC yr-2, which were 5 to 7 times smaller than the ensemble mean trend of 0.34 PgC yr-2 simulated by DGVMs. Global heterotrophic respiration showed much less agreement, ranging from top-down estimates of 42.7 (±4.0) PgC yr-1 to bottom-up estimates of 51.5 (±4.0) PgC yr-1 and a significantly larger ensemble model mean estimate of 60.8 PgC yr-1 (±1.9). The temporal trends in observation-based bottom-up estimates of heterotrophic respiration of 0.03 PgC yr-2 were five times lower than the model ensemble mean 0.15 PgC yr-2. Large regional disagreements in heterotrophic respiration estimates and simulations were evident in tropical and boreal latitudes. Therefore, improved regional and heterotrophic respiration estimates are necessary to reduce uncertainties regarding the future vulnerability of soil carbon.

Ballantyne, Ashley↗

DOE OSTI2025

Molecular mechanisms of mycorrhizal‐decomposer interactions and impacts on terrestrial biogeochemistry (Final Technical Report)

Soil microorganisms make nutrients available for plants and control a large portion of greenhouse gas emissions from terrestrial ecosystems by respiring CO 2 to the atmosphere, yet our understanding of how they do this is not clear enough to predict the rate of carbon (C) and nutrient flow through soils and the ecosystems they support. A common and abundant type of soil microorganism that associates with the roots of live plants, known as ectomycorrhizal fungi (EMF), is often able to control the amount of nutrients and C that are released from soil (e.g., as CO 2 respired to the atmosphere) during decomposition by microorganisms.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Point-scale organic-matter decomposition in streambeds is weakly associated with reach-scale respiration

Stream and river ecosystems play a central role in the movement and decomposition of particulate organic matter, serving as a conduit between terrestrial hillslopes and coastal environments. Microbial-catalyzed decomposition generates simpler organic molecules that fuel respiration, often in the sediments of these ecosystems. However, the degree of connection between sediment-associated respiration (ER??d) and organic-matter decomposition remains poorly understood. How that relationship compares to decomposition’s relationship with whole ecosystem (ERtot) and water column (ERwc) respiration is also not clear. We examined the link between particulate organic matter decomposition—using cellulose-based cotton strips as a standardized substrate—and all three components of respiration across 48 sites in the environmentally diverse Yakima River Basin (Washington State, USA). We hypothesized that decomposition within sediments would be most strongly related to ERsed, but decomposition rates were more closely associated with ERtot, with little connection to ERsed or ERwc. This suggests that particulate organic matter decomposition within stream/river sediments reflects integrated system respiration rather than processes confined to sediments or the water column alone. Further, across the basin, decomposition rates nearly spanned the previously reported global range for streams and rivers and were best explained by total dissolved nitrogen (TDN), sediment grain size, and aridity of the upstream drainage area. These results highlight the strong influence of land cover and basin-scale biophysical variation on sediment-associated decomposition processes and indicate that mechanistic models of organic matter decomposition in streams/rivers should account for coupled sediment–water–land interactions.

Stegen, James C. (ORCID:0000000191357424)↗

DOE OSTI2026

Zero Resistance Ammetry (ZRA) Measurements of Sediment Electrochemical Gradients, Old Woman Creek, Ohio, USA, June–November 2022

This dataset contains raw and processed zero resistance ammetry (ZRA) measurements collected from wetland sediments at Old Woman Creek, a freshwater estuary on Lake Erie, Ohio, USA, between June and November 2022. Measurements were obtained using a vertically deployed electrode array positioned at multiple depths within the sediment profile to capture electrochemical gradients associated with microbial activity and sediment geochemistry. The raw dataset consists of parsed instrument log files containing timestamps, electrode pair identifiers, and measured electrical potential (mV). The processed dataset includes standardized and quality-controlled values with instrument saturation limits removed and timestamps converted to ISO 8601 format. Electrode line identifiers were mapped to physical depths, enabling interpretation of depth-resolved electrochemical gradients. Instrument saturation values (−2048, −2047, 2047, and 2048 mV) were identified as measurement limits and excluded from quantitative analyses. All data parsing, processing, and quality control steps are documented in an accompanying R Markdown script, ensuring full reproducibility from raw instrument logs to final datasets.

EARTH SCIENCE > AGRICULTURE > SOILS > ELECTRICAL C↗