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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dataset for scientific paper "Simulated plant‑mediated oxygen input has strong impacts on fine‑scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands", a modeling study based on field observation at the tidal salt marshes of the Parker River Estuary, Massachusetts, United States

This dataset is the raw and processed data for the paper "Simulated plant ‑ mediated oxygen input has strong impacts on fine ‑ scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands". This study investigated how plant-mediated oxygen input affects subsurface biogeochemical reactions of organic carbon degradation and the resulting methane emissions of coastal wetlands by model simulation. We used the subsurface geochemical simulator PFLOTRAN for the modeling, which produced the simulated changes in porewater chemical substances and methane emissions over 10 days under different scenarios of plant-mediated oxygen input.Specifically, this dataset contains: 1) the input files for PFLOTRAN of all simulation runs conducted in this study. Those files are with an extension of ".in", containing information of the biogeochemical reaction network (stoichiometry, reaction rate, Monod constants, etc), fluid flow rate and oxygen concentration in the fluid which together simulated the plant-mediated oxygen input, the configuration of artificial reactions that simulated the methane fluxes, etc. The PFLOTRAN input files are text files, which can be opened by NotePad, but running these input files will require proper installation of PFLOTRAN (instruction: https://documentation.pflotran.org/user_guide/how_to/installation/installation.html). 2) the raw and processed model output from PFLOTRAN of all simulation runs, and 3) the python scripts used to process the raw model output, including random allocation of root cells, converting raw data into organized formats, calculating the methane fluxes based on the model output, data visualization, etc. The raw and processed model output from PFLOTRAN are in .spydata format, which can be viewed with Python. and 3) the python scripts for data processing and analysis are programming scripts, which can be opened with Python.This modeling work, in particular the model parameterization of root density and initial conditions of porewater concentrations of biogeochemical substances, was based on field measurements at the salt marsh of the Upper Parker River Estuary, Massachusetts, United States.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in-situ and remote sensing datasets

The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Drivers of Air-Sea CO2 Flux Seasonality and its Long-Term Changes in the NASA-GISS Model CMIP6 Submission.

Climate change will affect both the mean state and seasonality of marine physical and biogeochemical properties, with important implications for the oceanic sink of atmospheric CO2. Here, we investigate the seasonal cycle of the air-sea exchange of CO2 and pCO2,sw (surface seawater pCO2) and their long term changes using the CMIP6 submission of the NASA-GISS modelE (GISS-E2.1-G). In comparison to the CMIP5 submission (GISS-E2-R), we find that on the global scale, the seasonal cycles of the CO2 flux and NPP have improved, while the seasonal cycles of DIC, alkalinity, and macronutrients have deteriorated. Moreover, for all ocean biogeochemietry fields, changes in skill between E2.1-G and E2-R display large regional variability. For E2.1-G, we find similar modeled and observed CO2 flux seasonal cycles in the subtropical gyres, where seasonal anomalies of pCO2,sw and the flux are temperature-driven, and the Southern Ocean, where anomalies are DIC-driven. Biases in these seasonal cycles are largest in the subpolar and equatorial regions, driven by a combination of biases in temperature, DIC, alkalinity, and wind speed. When comparing the historical simulation to a simulation with an idealized increase in atmospheric pCO2, we find that the seasonal amplitudes of the CO2 flux and pCO2,sw generally increase. These changes are produced by increases in the sensitivity of pCO2,sw to its respective drivers. These findings are consistent with the notion that the sensitivity of pCO2,sw is expected to increase due to the increase of atmospheric pCO2, with changes in the seasonality of temperature, DIC, and alkalinity having secondary influences.

Air-Sea CO2↗
DOE OSTI2023

Future Response of Coastal Wetlands to Environmental Stresses: Algorithm Comparison of Numerical Models

Coastal wetlands are a critical component of the earth system that strongly influence the global water and biogeochemical cycles. They are also likely important sentinel of climate change. Because eco-geomorphological processes have long been recognized to be important for coastal wetland survival under accelerated sea-level rise (SLR), many eco-geomorphology models have been developed to assess the impact of climate change on coastal wetlands. Although these models differ substantially in complexity and numerical methods, few studies have investigated the algorithm-level uncertainties in these models. In this study, we developed a multiple-algorithm model framework of coastal wetlands that represents coastal hydrodynamics (such as water level, significant wave height and bottom shear stress) and four eco-geomorphological processes: mineral accretion, organic matter accretion, storm surge erosion and landward migration. We validated the model at three representative coastal wetland sites (Venice Lagoon, Plum Island Estuary and Hunter Estuary) for hydrodynamics, mineral accretion and organic matter accretion. Through model-data comparison, we showed that the model can well capture the dynamics of hydrodynamical and eco-geomorphological conditions in the study sites. Importantly, analysis of the multiple-algorithm simulations suggests that differences in the process representation of mineral and organic matter accretion may contribute to the recent contradicting predictions of coastal wetland evolution under accelerated SLR.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Variability in Modelled Airborne Dust Mineralogy Derived from Global Soil Composition Uncertainties

Dust aerosols consist on a variety of minerals with different physic and chemical properties. As such, they interact with short and long wave radiation, potentially form clouds, act as nutrients modulating biogeochemical cycles, or influence atmospheric chemistry, differently. Most current state-of-the-art Earth System Models (ESMs) neglect the complexity in dust composition, mainly due to computational constraints, but also to the existing uncertainties in the size resolved composition of parent soils, the resulting distribution of minerals in airborne dust, and the scarcity of observations to constrain them. Within this work, we assess the variability of global dust composition due to uncertainties in the characterization of the parent soil mineralogy. To that end, we consider two available global soil mineralogy atlases, developed by Claquin et al. (1999) –C1999- and Journet et al. (2014) –J2014-, which represent respectively 8 and 12 relevant minerals for climate (namely: illite, smectite/montmorillonite, kaolinite, calcite, gypsum, hematite, quartz, and feldspars in C1999, and those plus chlorite, vermiculite, goethite, and mica in J2014). Thanks to a recently developed feature of the MONARCH atmospheric-chemistry model, we are able to explicitly resolve the minerals’ atmospheric cycle. Therefore, we define two global experiments to assess changes on airborne dust composition attributed to the soil mineralogy assumptions and provide a measure of their variability. We also perform a preliminary evaluation of the global mineralogy results against available observations of mineral fractions in surface dust concentration. Our results will inform the climate modelling community about the potential variability in dust composition, an aspect that will gain relevance as ESMs continue growing in complexity and new processes to better characterize aerosols’ forcing or biogeochemical cycles are added. Further observational constraints, such as those that will derive from the EMIT NASA mission on soil composition or the FRAGMENT experimental campaigns on airborne dust characterization, will be key in the near future to improve our understanding of the impact of dust mineralogy on fundamental climate features.

Dust aerosols↗
DOE OSTI2026

Post-fire time series photos from five sites across the Oak Creek watershed, Washington

This dataset supports a broader study examining wildfire impacts on hydrologic connectivity across 5 sites within the Oak Creek watershed and the resulting biogeochemical impacts. Sites were selected using the Advanced Terrestrial Simulator (ATS) hydrologic model to identify locations with varying groundwater contributions and hydrologic responses across different burn severity scenarios. The Retreat Fire burned from July 23 to August 2, 2024, affecting all five sites. This dataset provides time series game camera photos, while the broader study includes continuous water quality monitoring, biogeochemical sampling of water and soils, precipitation data, and organic matter analysis. The other data types and additional metadata (include site environmental information) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3018020. Because this study is ongoing, this data package will be updated regularly to include newly collected photos. 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) readme; (5) field protocol; and (6) folders of game camera photos. The game camera photos are organized by site with subfolders by month of collection. The field metadata contains a subset of the information collected that is most relevant to photo-processing. The full set of field metadata can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3018020. All files are .csv, .pdf, or .jpg.

Burn severity↗
DOE OSTI2024

Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions

Methane (CH 4 ) is globally the second most critical greenhouse gas after carbon dioxide, contributing to 16%–25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane emission estimates from biogeochemistry models contain considerable uncertainty. One of the main sources of this uncertainty arises from the numerous uncertain model parameters within various physical, biological, and chemical processes that influence methane production, oxidation, and transport. Sensitivity Analysis (SA) can help identify critical parameters for methane emission and achieve reduced biases and uncertainties in future projections. This study performs SA for 19 selected parameters responsible for critical biogeochemical processes in the methane module of the Energy Exascale Earth System Model (E3SM) land model (ELM). The impact of these parameters on various CH 4 fluxes is examined at 14 FLUXNET- CH 4 sites with diverse vegetation types. Given the extensive number of model simulations needed for global variance-based SA, we employ a machine learning (ML) algorithm to emulate the complex behavior of ELM methane biogeochemistry. We found that parameters linked to CH 4 production and diffusion generally present the highest sensitivities despite apparent seasonal variation. Comparing simulated emissions from perturbed parameter sets against FLUXNET-CH 4 observations revealed that better performances can be achieved at each site compared to the default parameter values. This presents a scope for further improving simulated emissions using parameter calibration with advanced optimization techniques.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Impact of Crop Rotation and Spatially Varying Crop Parameters in the E3SM Land Model (ELMv2)

Abstract Earth System Models (ESMs) are increasingly representing agriculture due to its impact on biogeochemical cycles, local and regional climate, and fundamental importance for human society. Realistic large scale simulations may require spatially varying crop parameters that capture crop growth at various scales and among different cultivars, as well as common crop management practices, but their importance is uncertain, and they are often not represented in ESMs. In this study, we examine the impact of using constant versus spatially varying crop parameters using a novel, realistic crop rotation scenario in the Energy Exascale Earth System Model (E3SM) Land Model version 2 (ELMv2). We implemented crop rotation by using ELMv2's dynamic land unit capability, and then calibrated and validated the model against observations collected at three AmeriFlux sites in the US Midwest with corn soybean rotation. The calibrated model closely captured the magnitude and observed seasonality of carbon and energy fluxes across crops and sites. We performed regional simulations for the US Midwest using the calibrated model and found that spatially varying only a few crop parameters across the region, as opposed to using constant parameters, had a large impact, with the carbon fluxes and energy fluxes both varying by up to 40%. These results imply that large scale ESM simulations using spatially invariant crop parameters may result in biased energy and carbon fluxes estimation from agricultural land, and underline the importance of improving human‐earth systems interactions in ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Quantifying microbial roles in environmental iron oxidation via an integrated kinetics, `omics and metabolic modeling study (Final Report)

Iron oxyhydroxides are extremely reactive components of environmental systems, and therefore exert a strong influence on biogeochemical cycles. These oxyhydroxides strongly adsorb many biologically-relevant elements, including organic carbon and phosphate, as well as a wide range of metals including uranium and actinide species. Thus, the formation mechanism of iron oxyhydroxides are key to understanding both nutrient and contaminant cycling. Microorganisms can catalyze iron oxidation and promote the formation of Fe biominerals and thus are increasingly recognized as important players in biogeochemical cycling. However, it is completely unknown how much of environmental iron oxidation is biologically mediated versus abiotic, and various challenges in studying microbial iron oxidation have hindered accurate incorporation into hydrobiogeochemical models. The overarching goal of our work was to quantify and constrain microbial iron oxidation rates and use ‘omics to gain insight into the controls on this process, while developing tools to enable integration of biotic iron oxidation into hydrobiogeochemical models. Our work focused on the Savannah River Site (SRS) in South Carolina, where extensive microbial iron oxidation has been observed. At Tims Branch, part of the Argonne National Laboratory Wetland Hydrobiogeochemistry Science Focus Area (Argonne SFA), where groundwater discharges into a stream, iron-oxidizing microbial mats form and appear to be a major sink of uranium. In the wetlands that surround Tims Branch, there are wide swaths of iron microbial mats and flocs (mobilized mat). We measured biotic and abiotic iron oxidation rates using mats and water sampled from these sites and found that iron oxidation is primarily carried out by chemolithotrophic microorganisms. The resulting rate constants can be incorporated into models. These mats were characterized by metagenomics and metatranscriptomics, which showed that aerobic chemolithotrophs were the dominant iron-oxidizing bacteria (FeOB), and these included Gallionellaceae and Leptothrix, and possibly Rhodoferax, which is known as an Fe-reducer but may also oxidize Fe(II). This demonstrated that diverse FeOB can coexist and suggests that there are a range of niches and therefore drivers of chemolithotrophic iron oxidation. Analysis of reconstructed genomes strongly suggests that a major factor in diversity is carbon source, as genomes contained varied pathways for autotrophy and heterotrophy. We performed an in-depth analysis of Leptothrix ochracea genomes, since this sheath-former is one of the primary mat builders, yet its physiology remained unresolved. A combination of genomics, transcriptomics, and metabolic modeling suggest that L. ochracea grows mixotrophically using a combination of Fe(II) and organics for energy and both inorganic and organic carbon to create biomass. This contrasts with the largely autotrophic Gallionellaceae (Gallionella, Sideroxydans, and Ferriphaselus) also present in the mats and flocs. Remarkably, multiple FeOB, both Leptothrix and Gallionellaceae, showed activity in response to Fe(II) in live mat incubations. We tracked the gene expression of individual MAGs to Fe(II) and found that various autotrophic and heterotrophic FeOB responded to Fe(II), increasing expression of both carbon fixation and organic utilization genes. The results of the integrated field, kinetics, and omics studies give detailed insight into 1) the taxa that oxidize Fe, and 2) how they connect Fe, C, and N cycles. Towards the goal of connecting omics data to hydrobiogeochemical models, we worked with the KBase team to create a template metabolic model for chemolithotrophic iron oxidation. We initially modeled the well-characterized isolate Gallionellaceae Sideroxydans lithotrophicus, and also applied the model to the mixotroph L. ochracea. In all, we have characterized diverse FeOB in a representative wetland system and solved key problems that enable better incorporation of iron-oxidizing microbes into hydrobiogeochemical models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Bio-Optical Measurement and Modeling of the California Current and Polar Oceans

This Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project contract supports in situ ocean optical observations in the California Current, Southern Ocean, Indian Ocean as well as merger of other in situ data sets we have collected on various global cruises supported by separate grants or contracts. The principal goals of our research are to validate standard or experimental products through detailed bio-optical and biogeochemical measurements, and to combine ocean optical observations with advanced radiative transfer modeling to contribute to satellite vicarious radiometric calibration and advanced algorithm development. In collaboration with major oceanographic ship-based observation programs funded by various agencies (CalCOFI, US JGOFS, NOAA AMLR, INDOEX and Japan/East Sea) our SIMBIOS effort has resulted in data from diverse bio-optical provinces. For these global deployments we generate a high-quality, methodologically consistent, data set encompassing a wide-range of oceanic conditions. Global data collected in recent years have been integrated with our on-going CalCOFI database and have been used to evaluate Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) algorithms and to carry out validation studies. The combined database we have assembled now comprises more than 700 stations and includes observations for the clearest oligotrophic waters, highly eutrophic blooms, red-tides and coastal case two conditions. The data has been used to validate water-leaving radiance estimated with SeaWiFS as well as bio optical algorithms for chlorophyll pigments. The comprehensive data is utilized for development of experimental algorithms (e.g., high-low latitude pigment transition, phytoplankton absorption, and cDOM).

Mitchell, B. Greg↗
DOE OSTI2022

Integration of Omics into a New Comprehensive Rate Law for Competitive Terminal Electron-Accepting Processes in Reactive Transport Models: Application to N, Fe, S, and Contaminant Transformations in Stream and Wetland Sediments

Surface waters represent important sources of alternate energy and drinking water in the United States, and characterizing the biogeochemical processes that affect surface water quality is relevant to the DOE-BER mission. Sediment biogeochemical processes regulate the release of carbon (C), nutrients, and contaminants to surface waters and thus influence water quality. Sediment biogeochemical processes are dynamic and affected by the deposition and remobilization of solid material and changes in environmental conditions driven by water discharge variations. Wetlands are important natural filters of surface waters which may either trap, metabolize, or mobilize nutrients and contaminants. Despite their importance, biogeochemical processes regulating nutrient and contaminant release and C transformation in stream and wetland sediments cannot be predicted accurately by current mathematical models. These reactive transport models largely rely on detectable changes in geochemical conditions to activate metabolic processes, do not accurately account for the competition between microbial processes, and poorly constrain effects of hydrological perturbations on biogeochemical processes. In this BER-SBR exploratory project, metagenomic and geochemical signatures were combined to identify microbially-mediated redox processes in anaerobic stream and wetland sediments from the Savannah River Site (SRS, ANL SFA) and East Fork Poplar Creek (EFPC, ORNL SFA) that play important roles in C, uranium (U), and mercury (Hg) transformations. In addition, sediment incubations were conducted to examine the competition between anaerobic respiration processes Finally, new rate laws were developed for reactive transport models that rely on complementary metagenomic and geochemical signatures to identify the underlying anaerobic microbial processes in stream and wetland sediments, describe the competition between the dominant metabolic processes involved in nutrient release and U and Hg mobilization, and more accurately quantify carbon transformation and the response of microbial processes to changes in redox conditions associated with hydrological forcing. These rate laws were optimized in batch reactors with SRS wetland sediments, where iron and sulfate reduction dominate. Anaerobic carbon remineralization processes followed the expected thermodynamic sequence of microbial respiration with depth in both sediments, except that geochemical signals indicated that sulfate reduction was inactive in EFPC sediments and moderate in SRS wetland sediments. Estimates indicated that microbial iron reduction contributed to at least half of the production of reduced iron in these sediments. Incubations demonstrated that nitrate reduction, denitrification, and dissimilatory nitrate reduction to ammonium were active in the natural EFPC sediment and activated upon nitrate amendment in these nitrate-rich sediments. In turn, these processes were outcompeted by the addition of either iron oxides or sulfate as alternative terminal electron acceptors. Although geochemical products of sulfate reduction were not detected in the incubations, the abundance of sulfate reduction genes increased with depth in the sediment and was equally more pronounced in treatments amended with either iron oxides or sulfate. Simultaneously, anaerobic sulfide oxidizing bacteria coupling sulfide oxidation to DNRA (and not conventional denitrification) were apparently enriched over time, regardless of the treatments. These findings indicate that sulfate reduction is important in freshwater stream sediments and probably catalyzed by a cryptic sulfur cycle involving nitrogen species, in which the sulfur products from sulfate reduction are immediately removed by side reactions and not detectable by geochemical measurements alone. Similar experiments in SRS sediments, however, demonstrated little interaction between nitrogen and sulfur cycling microorganisms. Sulfate reduction was impacted by the addition of more thermodynamically favorable electron acceptors, suggesting either that iron-reducing microorganisms outcompeted sulfate-reducing microorganisms for organic substrate, depleting the stock of electron donor available for sulfate reduction, or that the cryptic sulfur cycle was shunted by the precipitation of FeS generated as a result of the abiotic reduction of iron oxides by dissolved sulfide. A diagnostic modeling exercise was conducted to further investigate the competition between terminal electron accepting processes. As conventional kinetic models typically do not account for cryptic cycles and used inaccurate formulations to describe competition between microbial communities, new metabolic rate laws were developed that explicitly express the electron acceptor-specific enzyme of each energetically favorable metabolic process based on gene abundance detected in the incubations. The model was tested with the sediment slurry incubation data to determine whether substrate competition could explain the decrease in sulfate reduction observed in the presence of iron oxide competitor. The model was able to reproduce geochemical concentrations really well in each treatment once the model was calibrated with the unamended control, suggesting that microbial competition was indeed driven by thermodynamic considerations. Overall, carbon remineralization processes and rates will be reproduced much more realistically with the new metabolic rate laws.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Coupling Surface Flow with High-performance Subsurface Reactive Flow and Transport Code PFLOTRAN

Water exchange between the surface and subsurface is important for both water resource management and environmental protection. In this paper, we develop coupled surface and subsurface flow simulation capability in a parallel subsurface flow and reactive transport code PFLOTRAN. We sequentially couple the diffusion wave-based surface flow with the subsurface flow governedby the Richards equation in PFLOTRAN. These two flow domains are linked with a boundary condition switching method that ensures continuity of pressure and flux at the surface-subsurface interface. We verify the coupled code against other existing hydrologic models and observation data using a number of numerical experiments. The coupled hydrological model exhibits good performance in strong parallel scaling tests. The new coupled surface and subsurface simulator significantly advance community simulation capability towards improving integrated hydrologic and biogeochemical understanding of complex systems such as watersheds and river corridors. Keywords: Surface flow, Integrated hydrological modeling, Boundary condition switching, Parallel computing

Wu, Runjian↗
DOE OSTI2024

Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Nutrient Cycling at a Coastal Terrestrial‐Aquatic Interface

Abstract The complex interactions among soil, vegetation, and site hydrologic conditions driven by precipitation and tidal cycles control the biogeochemical transformations and bi‐directional exchange of carbon and nutrients across the terrestrial–aquatic interfaces (TAIs) in coastal regions. This study uses a highly mechanistic model, Advanced Terrestrial Simulator (ATS)‐PFLOTRAN, to explore how these interactions affect exchanges of materials and carbon and nitrogen cycling. We used a transect in the Chesapeake Bay region that spans zones of open water, coastal wetland, transition, and upland forest. We designed several simulation scenarios to parse the effects of the individual controlling factors and the sensitivity of carbon cycling to reaction rate parameters derived from laboratory experiments. Our simulations reveal an active zone for carbon cycling under the transition zones between the wetland and the upland. Evapotranspiration is found to enhance the exchange fluxes between the surface and subsurface domains, resulting in a higher dissolved oxygen concentration in the TAIs. The transport of organic carbon derived from plant leaves and roots provide an additional source of organic carbon needed for the aerobic respiration and denitrification processes in the TAIs. The variability in reaction rate parameters associated with microbial activities is also found to play a dominant role in controlling the heterogeneity and dynamics of the simulated redox conditions. This modeling‐focused exploratory study enabled us to better understand the complex interactions among soil, water and microbes that govern the hydro‐biogeochemical processes at the TAIs, which is an important step toward representing coastal ecosystems in larger‐scale Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Biogeochemical dynamics and microbial community development under sulfate- and iron-reducing conditions based on electron shuttle amendment

Iron reduction and sulfate reduction are two of the major biogeochemical processes that occur in anoxic sediments. Microbes that catalyze these reactions are therefore some of the most abundant organisms in the subsurface, and some of the most important. Due to the variety of mechanisms that microbes employ to derive energy from these reactions, including the use of soluble electron shuttles, the dynamics between iron- and sulfate-reducing populations under changing biogeochemical conditions still elude complete characterization. Here, we amended experimental bioreactors comprised of freshwater aquifer sediment with ferric iron, sulfate, acetate, and the model electron shuttle AQDS (9,10-anthraquinone-2,6-disulfonate) and monitored both the changing redox conditions as well as changes in the microbial community over time. The addition of the electron shuttle AQDS did increase the initial rate of Fe III reduction; however, it had little effect on the composition of the microbial community. Our results show that in both AQDS- and AQDS+ systems there was an initial dominance of organisms classified as Geobacter (a genus of dissimilatory Fe III -reducing bacteria), after which sequences classified as Desulfosporosinus (a genus of dissimilatory sulfate-reducing bacteria) came to dominate both experimental systems. Furthermore, most of the ferric iron reduction occurred under this later, ostensibly “sulfate-reducing” phase of the experiment. This calls into question the usefulness of classifying subsurface sediments by the dominant microbial process alone because of their interrelated biogeochemical consequences. To better inform models of microbially-catalyzed subsurface processes, such interactions must be more thoroughly understood under a broad range of conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Upscaling Soil Organic Carbon Measurements at the Continental Scale Using Multivariate Clustering Analysis and Machine Learning

Abstract Estimates of soil organic carbon (SOC) stocks are essential for many environmental applications. However, significant inconsistencies exist in SOC stock estimates for the U.S. across current SOC maps. We propose a framework that combines unsupervised multivariate geographic clustering (MGC) and supervised Random Forests regression, improving SOC maps by capturing heterogeneous relationships with SOC drivers. We first used MGC to divide the U.S. into 20 SOC regions based on the similarity of covariates (soil biogeochemical, bioclimatic, biological, and physiographic variables). Subsequently, separate Random Forests models were trained for each SOC region, utilizing environmental covariates and SOC observations. Our estimated SOC stocks for the U.S. (52.6 ± 3.2 Pg for 0–30 cm and 108.3 ± 8.2 Pg for 0–100 cm depth) were within the range estimated by existing products like Harmonized World Soil Database, HWSD (46.7 Pg for 0–30 cm and 90.7 Pg for 0–100 cm depth) and SoilGrids 2.0 (45.7 Pg for 0–30 cm and 133.0 Pg for 0–100 cm depth). However, independent validation with soil profile data from the National Ecological Observatory Network showed that our approach ( R 2 = 0.51) outperformed the estimates obtained from Harmonized World Soil Database ( R 2 = 0.23) and SoilGrids 2.0 ( R 2 = 0.39) for the topsoil (0–30 cm). Uncertainty analysis (e.g., low representativeness and high coefficients of variation) identified regions requiring more measurements, such as Alaska and the deserts of the U.S. Southwest. Our approach effectively captures the heterogeneous relationships between widely available predictors and the current SOC baseline across regions, offering reliable SOC estimates at 1 km resolution for benchmarking Earth system models.

58 GEOSCIENCES↗
DOE OSTI2026

Depth-resolved carbon dioxide and methane concentrations in 522 lakes, ponds, and reservoirs worldwide

Lakes, ponds, and reservoirs (hereafter: “lakes”) are important sources of the greenhouse gases carbon dioxide (CO 2 ) and methane (CH 4 ). Emissions of CO 2 and CH 4 from lakes are regulated in part by in-lake processes, including the production and storage of gases in the lower parts of the water column (bottom waters). However, while substantial efforts have been made to improve estimates of greenhouse gas emissions from lakes, limited data on gas concentrations along depth profiles have prevented the incorporation of bottom-water processes in global emission estimates. Here, we present GHG-depths: the largest existing dataset of depth-profile CO 2 and CH 4 measurements worldwide, including 522 lakes across 38 countries and all seven continents. These data include contributions from 45 research teams and 56 published studies, totaling 2558 discrete sampling events. As global change continues to alter biogeochemical cycling in lakes, these data can help improve mechanistic models to better predict greenhouse gas production and emission from lakes worldwide.

Rabaey, Joseph S. [University of Minnesota, Duluth↗
NASA NTRS1988

Long-term climate change and the geochemical cycle of carbon

The response of the coupled climate-geochemical system to changes in paleography is examined in terms of the biogeochemical carbon cycle. The simple, zonally averaged energy balance climate model combined with a geochemical carbon cycle model, which was developed to study climate changes, is described. The effects of latitudinal distributions of the continents on the carbon cycle are investigated, and the global silicate weathering rate as a function of latitude is measured. It is observed that a concentration of land area at high altitudes results in a high CO2 partial pressure and a high global average temperature, and for land at low latitudes a cold globe and ice are detected. It is noted that the CO2 greenhouse feedback effect is potentially strong and has a stabilizing effect on the climate system.

Marshall, Hal G.↗
NASA NTRS1989

Estimating biogeochemical fluxes across sagebrush-steppe landscapes with Thematic Mapper imagery

Thematic Mapper (TM) satellite data were coupled to an ecosystem simulation model to simulate variation in nitrogen mineralization over time and space in a sagebrush steppe. This system of data inputs and calculations provides estimates of ecosystem properties including rates of biogeochemical processes over extensive and complex landscapes, and under changing management and climatic conditions. The landscape surface was divided into three sagebrush ecosystem types plus one other class consisting of nonsagebrush vegetation. This classification presented a complex mosaic of ecosystem types that shifted markedly in composition from one end of the 933-sq km study area to the other. Annual N-mineralization rates ranged from 5 to 25 kg N/ha among the three sagebrush types. The most active type comprised 42 percent of the entire area but contributed 60 percent to the nitrogen mineralization throughout the landscape.

Reiners, W. A.↗