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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Schneider Springs Fire Study 2023 for Ecosystem Respiration Rates: Surface Water Chemistry and Hydrologic Sensor Data across the Yakima River Basin, Washington, USA (v2)

This dataset supports a broader study examining the drivers of spatial variability in wildfire impacts across the Yakima River Basin. Data provided within this dataset were generated from sample collection across 17 total sites (8 sites affected by a recent wildfire, 9 sites unaffected by a recent wildfire) within multiple rivers throughout the Yakima River Basin in Washington, USA from May-July 2023. Fire affected sites are defined as those affected by the 2021 Schneider Springs Fire, based on the drainage area of the streams being within the 2021 Schneider Springs Fire burn perimeter or not (Figure 1, below). The contents include surface water geochemistry data (dissolved organic carbon; total dissolved nitrogen; total suspended solids); short-term sonde data (specific conductivity; turbidity; pH; chlorophyll A; temperature); stream depth data; stream velocity; manual chamber open channel respiration data; sensor time-series data (oxygen; water pressure; barometric pressure); field metadata (including qualitative information on in stream and river corridor characteristics); and environmental context photos taken in the field. The dataset also includes a summary file of the sensor data and plots of the sensor data. Sensors were only recovered at 15 out of the 17 sites, and not all sensors were recovered at all 15 sites (see Methods section for more details), therefore all data does not exist at all sites. Data from a 2022 study at the same sites, as well as additional sites, can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566. The data package was originally published in November 2023. It was updated in June 2025 (v2; 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. This dataset is comprised of one folder with field photos and one main data folder with two subfolders. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) field protocol; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) stream depth and averages. The sensor data subfolder consists of (1) sensor installation methods summary; (2) stream velocity; and (3) six subfolders. The BarotrollAtm (barometric pressure; temperature), DepthHOBO (water pressure; temperature), MantaRiver (specific conductivity; turbidity; pH; chlorophyll A; temperature), EXO (specific conductivity; pH; temperature), miniDOT (dissolved oxygen; temperature), and miniDOTManualChamber (dissolved oxygen; temperature) contain time-series data, plots, and summary files. The sample data subfolder consists of (1) total suspended solids (TSS) data; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (3) total dissolved nitrogen (TN) data and averages; and (4) methods codes. All files are .csv, .pdf, .jpg, .jpeg, or .mov.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Data from: "Ecophysiological variation in two provenances of Pinus flexilis seedlings across an elevation gradient from forest to alpine"

This archive contains data used to support conclusions drawn in “Ecophysiological variation in two provenances of Pinus flexilis seedlings across an elevation gradient from forest to alpine”, by Reinhardt et al., 2011. Data were collected over one summer season in plots within the Alpine Treeline Warming Experiment (ATWE), before climate manipulations began. The experiment was located on Niwot Ridge, in the Front Range of the Colorado Rocky Mountains. This data package includes five comma-separated-values (.csv) files, five Microsoft Excel (.xlsx) files, one .pdf file, and two types of geospatial files: keyhole markup language (.kml), and ESRI shapefiles (.shp). .csv files can be opened using any simple text-editing software (such as Notepad and TextEdit), R, and Microsoft Excel. .xlsx files can only be opened using Microsoft Excel. The .pdf file can be opened using Adobe Acrobat Reader or any other compatible file viewing software. The .kml file can be opened using Google Earth and Google Maps, and shapefiles can be opened using any software compatible with the file type, such as ESRI’s ArcGIS suite and QGIS.Data archived contain gas exchange and plant physiology measurements, non-structural carbohydrate data, among others. Geospatial files are also provided for additional locational context. The files and their contents in this data package are summarized under "Data Summary" in the included Data User's Guide. All files (excluding geospatial) are available in both Microsoft Excel and in .csv format, and are indicated in the Data Summary list as well.-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Climate change is predicted to cause upward shifts in forest tree distributions, which will require seedling recruitment beyond current forest boundaries. However, predicting the likelihood of successful plant establishment beyond current species’ ranges under changing climate is complicated by the interaction of genetic and environmental controls on seedling establishment. To determine how genetics and climate may interact to affect seedling establishment, we transplanted recently germinated seedlings from high- and low-elevation provenances (HI and LO, respectively) of Pinus flexilis in common gardens arrayed along an elevation and canopy gradient from subalpine forest into the alpine zone and examined differences in physiology and morphology between provenances and among sites. Plant dry mass, projected leaf area and shoot:root ratios were 12–40% greater in LO compared with HI seedlings at each elevation. There were no significant changes in these variables among sites except for decreased dry mass of LO seedlings in the alpine site. Photosynthesis, carbon balance (photosynthesis/respiration) and conductance increased >2× with elevation for both provenances, and were 35–77% greater in LO seedlings compared with HI seedlings. There were no differences in dark-adapted chlorophyll fluorescence (Fv/Fm) among sites or between provenances. Our results suggest that for P. flexilis seedlings, provenances selected for above-ground growth may outperform those selected for stress resistance in the absence of harsh climatic conditions, even well above the species’ range limits in the alpine zone. This indicates that forest genetics may be important to understanding and managing species’ range adjustments due to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Laboratory time series moisture manipulative experiment from sediment across the contiguous US: time series aerobic respiration and geochemistry (v2)

This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration across the contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS CONUS-Scale Model-Sample Study (CM). This study was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. The data package associated with the CM study is available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689. CM sampling began in April 2022 and ended in October 2023. This study uses subsamples from a subset of CM samples collected between June 2022 and June 2023. The original field samples were labeled as CM_###. Subsequent subsamples for this study were labeled as EC_###. The labels from the field samples and the EC subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EC_001 is a subsample from CM_001). See the critical details section below for more details on sample naming. This data package was originally published in August 2024. It was updated in February 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) adenosine triphosphate (ATP); (4) percent carbon and nitrogen; (5) effect size; (6) iron (II); (7) gravimetric moisture; (8) respiration rates and raw dissolved oxygen values; (9) specific conductance; (10) pH; (11) temperature; (12) a summary containing median values of each data type for each treatment (wet and dry); (13) methods codes; (14) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla FTICR-MS data. This folder contains three subfolders, one containing the sediment .xml data files, one containing the sediment CoreMS output files, the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

SPRUCE Sphagnum Growth and Photosynthesis Responses to Shading Treatments, 2021

This dataset reports growth, water content, nitrogen concentration, and photosynthesis of Sphagnum grown under shade cloth of different density in replicated plots adjacent to the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental study plots located in the S1-Bog. Data are reported for May to October 2021. Investigations were instigated from questions arising in the SPRUCE experiment where the Sphagnum-shrub-spruce/larch ecosystem is exposed to air and peat warming in combination with elevated atmospheric CO2. SPRUCE is located at the 8.1-ha S1 Bog forest site in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Thirty plots (35 × 35 cm) were established in May, 2021, in three blocks on unused large plots on the S-1 bog. Data are reported for growth of Sphagnum angustifolium/fallax and S. divinum growing in plastic columns within the shade plots. Growth is reported as dry mass of new tissue measured when the columns were harvested in October 2021. Additional measurements in the final harvest datasetinclude Sphagnum water content, new stem length, mass per unit length, and nitrogen content. Stem extension was measured periodically during the summer and reported in a separate datasetas stem length. Photosynthesis of Sphagnum angustifolium/fallax samples from hollows under low and high shade was measured in the laboratory. Responses of sphagnum to shading are important for understanding the future of peatland systems under the encroachment of shrubs and other woody plant species. This dataset contains three data files in comma-separated values (.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma-separated values (.csv) format and a user guide in PDF (*.pdf) format.

carbon dioxide flux↗
DOE OSTI2026

Post-fire time series of sensor and geochemistry sample data from surface water, groundwater, precipitation, soil, and vegetation across 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. Stream 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 in 2024, affecting the five study sites at varying burn severities. Each site is equipped with YSI EXO2 sondes logging sub-hourly throughout the year, and grab samples are collected approximately every six weeks. YSI sondes are used to measure temporally resolved proxies for groundwater inputs (specific conductivity) and organic matter (fluorescent dissolved organic matter; fDOM) along with basic water quality and depth. Grab samples of surface water, groundwater, and precipitation are analyzed for water stable isotopes and conductivity to understand endmembers for hydrologic mixing Grab samples of surface water, groundwater, soil water, and litter/vegetation/soil leachates are analyzed for organic matter composition measured by Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) to understand organic matter dynamics. Game camera photos are provided in a separate data package available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3018598. Future versions of this dataset will include time series data from YSI EXO2 sondes (fDOM, dissolved oxygen, temperature, depth, specific conductance, turbidity, pH), BaroTROLL sensors (air temperature and barometric pressure), rain gauges (precipitation), and data from the soil and vegetation samples. Because this study is ongoing, this data package will be updated regularly to include newly collected data and the additional data types. 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) a folder of field photos; (2) a folder of surface water sample data; (3) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data; (4) a data checks report; (5) file-level metadata; (6) data dictionary; (7) field metadata; (8) readme; (9) international generic sample number (IGSN) mapping file; and (10) field protocols. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) total dissolved nitrogen data and averages; (3) stable water isotopes and averages; (4) methods codes; (5) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the processed data and three subfolders, one containing the .xml files, one containing the water 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, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4.

Biogeochemistry↗
DOE OSTI2021

Vegetation Warming Experiment: 15N Uptake Experiment Arctagrostis latifolia Root Traits, Utqiagvik (Barrow), Alaska, 2018

This dataset consists of measured A. latifolia root traits (specific root length (SRL), mass, length, C and N content) from vegetation warming experiment enclosures and paired control plots located on the BEO, Utqiagvik, Alaska. Vegetation warming chambers (Zero Power) were deployed on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. These chambers (Figure 1) consistently elevated air temperatures by approximately 4°C using a self-venting system described by Lewin et al (2017). Five chambers were deployed from June 17, 2018 to September 24, 2018 on the BEO within a 1 km2 area centered on 71.275N, -156.641W. Each chamber was co-located with an ambient plot where temperatures were not manipulated on patches of tundra containing the target species Arctagrostis latifolia. An intensive field campaign in late July investigated the impact of warming had on A. latifolia biomass, chemistry, and uptake of 15N labeled ammonia that was injected into the surface soils for one week. Initial measurements were taken on July 21, 2018. Harvest occurred on July 27, 2018. Water-extractable nutrients in soils were measured in July following harvests of A. latifolia plants and underlying soils. Availability of ammonia, nitrate, and phosphate throughout the growing season was measured by extracting nutrients bound to anion and cation binding resins deployed from July through September. Environmental variables (thaw depth, surface soil temperatures, surface soil moisture) were measured. Leaf traits and root traits of A. latifolia were also measured. Files include one *.csv data file and one *.pdf user guide. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Warming amplifies the variability of methane emissions from a coastal wetland, 2025, Maryland.

These data accompany the published paper Lewis et al., 202X and are from a brackish coastal wetland in situ soil warming experiment (GENX) equipped with automated flux chambers. Methane (CH4) and carbon dioxide (CO2) fluxes were measured in 12 automated chambers using custom-built automated chambers connected to an LI-7810 CH4/CO2 analyzer. The chambers are 1.5 m tall and contain the dominant vegetation species of the site (Schoenoplectus americanus, Spartina patens, and Distichlis spicata). The chambers are also distributed across a soil warming gradient, ranging from ambient to 6°C above ambient, that was started in February 2022. This dataset contains the following files: (1) CH4 and CO2 fluxes from each chamber for March to November 2025, statistics for each flux, and environmental data (water depth, salinity, air temperature) at the time of the flux measurement; (2) 15-minute soil temperature data for each chamber; (3) Aboveground vegetation biomass (total and by species) and stem counts and dimensions for S. americanus; (4) Elevation for each chamber. All data processing code is available on Github.

Coastal wetland↗
DOE OSTI2025

Reproductive and leaf litterfall fluxes in forest ecosystem sites globally (1950-2022)

Forest allocation of net primary productivity (NPP) to reproduction is poorly quantified globally, despite its critical role in forest regeneration and a well-supported trade-off with allocation to growth. Although field measurements of total NPP are rare, our work finds that a proxy for reproductive carbon allocation constructed from leaf (L) and reproductive (R) litterfall fluxes, R/(R+L), is strongly correlated with R/NPP, facilitating analysis across a wide range of sites where biometric estimates of NPP are not available (R² = 0.85; Hanbury-Brown et al., 2022, Ward et al., in prep). To investigate relationships between ecosystem-scale reproductive allocation (RA) and climate, soil fertility, and stand age gradients, we conducted a literature search and synthesized 824 observations of annual average leaf and reproductive litterfall fluxes across forest sites globally. The zip file includes 1) a folder Data/ containing the litterfall data ("GlobalForestRA_data.csv") and metadata ("GlobalForestRA_metadata.doc") files. The data file includes geographic coordinates, long-term mean annual temperature and precipitation (1970-2000, extracted from WorldClim2.1), leaf and reproductive litterfall fluxes, sampling interval and protocols, forest characteristics (dominant leaf morphology, information pertaining to forest age and successional stage, and disturbance history) and soil properties (% sand, %silt, %clay, total phosphorus (P), nitrogen (N), cation exchange capacity (CEC) and pH) extracted from SoilGrids250 and from on-site measurements, where available. The metadata file contains information about each variable reported in the data file, including data sources, processing methods, and all references. The Data folder contains two additional files used to create Figure 1; these are described in greater detail in the README.2) R scripts GloalForestRA_analysis.r and GlobalForestRA_SI.r and a folder /Functions used to produce results, figures, and tables in the manuscript Ward et al. (in press)3) a README file describing how the data and R scripts can be used to reproduce statistical results, figures, and tables found in the manuscript. Ward et al. (in press)This repository can also be found at: https://github.com/r-ward/Global_Analysis_ForestRA.Ward, R.E., Zhang-Zheng, H. Aernethy, K., Adu-Bredu, S., Arroyo, L., Bailey, A. et al. (in press). Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally. Ecology Letters. Hanbury-Brown, A.R., Ward, R.E. & Kueppers, L.M. (2022). Forest regeneration within Earth system models: current process representations and ways forward. New Phytol., 235, 20–40.Ward et al. (2025), Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally, in prep.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

NGEE Arctic Plant Traits: Fine Roots, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2016

Soil cores were collected from twelve vegetation biomass plots at the Kougarok hillslope in late July of 2016. The sampled plots were located across six ecotypes present at this site (n=2 replicates per ecotype). Soil cores were separated into depth intervals in the field and frozen for transport to Oak Ridge National Laboratory. Data package contains one *.csv and one *.pdf.Laboratory sample processing of these soils generated depth-specific data on soil properties as well as fine root biomass, length, %C, %N, delta13C, and delta15N. Only live fine roots were analyzed. Fine roots were not separated by species or plant functional type.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs

This submission aimed to assess differences in short-term step warming manipulations and long-term chronic response to climate change in Alaskan ecosystems. Briefly, climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (< 10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.The model used in the current study is available publicly (https://github.com/jinyun1tang/ECOSYS), and the current submission contains the python/ matlab codes for analyzing output from the model (includng a readme file to explain the codes). The benchmark data, also enclosed, was collected from a range of published and publicly available sources (extracted using GRABIT: https://www.mathworks.com/matlabcentral/fileexchange/7173-grabit). These sources describe warming induced changes in tundra/ boreal ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Duke Forest FACE (FACTS-I): Plant and Soil Response Data

This dataset describing the responses of plant and soil pools and fluxes to elevated atmospheric CO2 concentration and increased nitrogen supply was collected from Duke Forest Free Air CO2 Enrichment (FACE) – Forest-Atmosphere Carbon Transfer and Storage (FACTS-I) experiment from 1996 to 2012. The dataset includes data files for allometry (diameter at breast height, tree height, and height to live crown base), leaf area index, biomass (stem, branch, foliage, and root biomass, tree density, and basal area), net primary productivity (stem, branch, foliage, reproductive, and coarse root NPP), sap flux density, soil CO2 efflux, and stem temperature. Data files were formatted as .csv (Microsoft Excel or other spreadsheet programs can be used to read the format) and file descriptions, including variable name, unit, and data range, can be found in ‘FileDescription_[data_name].txt’ files. The Duke FACE experiment was in a loblolly pine (Pinus taeda L.) plantation established in 1983. Naturally regenerated broadleaved species including sweetgum (Liquidambar styraciflua L.) and tulip poplar (Liriodendron tulipifera L.), mostly in the overstory, and winged elm (Ulmus alata Michx.) and red maple (Acer rubrum L.) were common in the understory. The FACE experiment commenced with two plots (plots 7-8) in 1994 (Oren et al. 2001), with six additional plots (plots 1-6) coming online on 27 August 1996. CO2 enrichment was terminated on 31 October 2010 and post-enrichment data collection continued through 2012. Complete fertilization was applied annually to half of plots 7-8 from 1998 to 2004. The nutrient addition experiment expanded to half of plots 1-6 with a common protocol of N-fertilization in 2005 and continued until 2012. The levels of treatment in this dataset were expressed as ambient CO2 (AMB) or elevated CO2 (ELE) for CO2 treatment and control soil (CONT) or fertilized soil (FERT) for N treatment, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of burning on soil properties and respiration; Wood Buffalo National Park, Canada; June 2019

In this study, we used burn simulations on boreal forest soil under high and low moisture conditions to investigate the effect of burning on soil temperature, soil properties such as pH, total C and total C, and soil respiration. Location and site characteristic data of 19 sampling locations within Wood Buffalo National Park, Canada are included in "sampling-site-characteristics.csv". File "Temp-all-burns.csv" contains temperature data collected 2 to 9 cm below the soil surface during 2 min. heat treatment (i.e. burn simulation) and the following 5-24 hrs. Following the burn simulations, total respiration from burned and unburned soil was collected via KOH base traps for up to 6 months ("raw-conductivity-readings.csv"). The metadata file ("all-sample-metadata.csv") contains measurements of soil pH, total C, and total N of O horizon and underlying mineral soil as well as model fits for respiration data.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2024

Biogeochemistry simulations for the Salt Marsh Accretion Response to Temperature eXperiment (SMARTX)

Coastal ecosystems have been largely ignored in Earth system models but are important zones for carbon and nutrient processing. Interactions between water, microbes, soil, sediments, and vegetation are important for mechanistic representation of coastal processes and ecosystem function. To investigate the role of these feedbacks, we used a reactive transport model (PFLOTRAN) that has the capability to be connected to the Energy Exascale Earth System Model (E3SM). PFLOTRAN was used to incorporate redox reactions and track chemical species important for coastal ecosystems as well as define simple representations of vegetation dynamics. Our goal was to incorporate oxygen flux, salinity, pH, sulfur cycling, and methane production along with plant-mediated transport of gases and tidal flux. Using porewater profile and incubation data for model calibration and evaluation, we were able to create depth-resolved biogeochemical soil profiles for saltmarsh habitat and use this updated representation to simulate direct and indirect effects of elevated CO2 and temperature on subsurface biogeochemical cycling. We found that simply changing the partial pressure of CO2 or increasing temperature in the model did not fully reproduce observed changes in the porewater profile, but the inclusion of plant or microbial responses to CO2 and temperature manipulations was more accurate in representing porewater concentrations. This indicates the importance of characterizing tightly coupled vegetation-subsurface processes for developing predictive understanding and the need for measurement of plant-soil interactions on the same time scale to understand how hotspots or moments are generated.Included in this data package are PFLOTRAN input (PFLOTRAN input files and chemical database) files for simulating single column biogeochemistry, root, and tide interactions at the Global Change Research Wetland (Kirkpatrick Marsh; Edgewater, MD). The biogeochemical network includes soil organic matter decomposition, nitrogen, iron, and sulfur cycling, and methanogenesis. Reduced species can be oxidized and plant processes include oxygen and nutrient priming, methane release, and nutrient uptake.Inputs:TAI_database.dat - geochemical database for reactions, more information on database structure and variables can be found here https://www.pflotran.org/documentation/user_guide/cards/pages/geochemical_database.htmlswamp.in - input file for biogeochemical network in PFLOTRANswamp_eCO2.in - input file for biogeochemical network in PFLOTRAN with input gas partial pressures/concentrations adjusted for elevated CO2 treatmentsOutputs:swamp_obs_0.tec - hourly porewater concentrations from from multiple depths in the soil columnswamp_eCO2_obs_0.tec - hourly porewater concentrations from multiple depths in the soil column for elevated CO2 treatmentsPFLOTRAN code access: https://github.com/fmyuan/pflotran-elm-interface.git

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Seedling nitrogen uptake and rhizodeposition between mycorrhizal types

Tree mycorrhizal associations are associated with patterns in N cycling and soil organic matter (SOM) storage, however, we still lack a mechanistic understanding of what tree and fungal traits drive these patterns and how they will respond to global changes in soil N availability. To address this knowledge gap, we investigated how arbuscular mycorrhizal (AM)- and ectomycorrhizal (EcM)-associated seedlings alter rhizodeposition in response to increased inorganic N acquisition. Specifically, we conducted this greenhouse experiment in a sealed labeling chamber with an enriched 13Carbon atmosphere and 15Nitrogen enriched fertilizer over the course of five months from April 2021 - August 2021. To include the variability across tree species, we grew eight species of seedlings belonging to eight families that were either arbuscular (Acer rubrum, Nyssa sylvatica, Thuja occidentalis, and Prunus seritina) or ectomycorrhizal-associated (Quercus rubra, Tilia americana, Pinus strobus, and Betula lenta). We measured rhizodeposition (mg 13C), plant N uptake from fertilizer (mg N), net soil carbon, and the abundance of mycorrhizal fungi (ITS sequencing and qPCR). We also characterized fungal (ITS2) and bacterial (16S) soil communities.The data from this project are ".csv" files that can up downloaded into a folder, and then run in the associated R markdown scripts after changing the source folder location at the top of the script. These data include raw outputs and processed files (using the R markdown files) for seedling growth and biomass, 15N content, soil 13C content, raw reads and processed file versions for fungal and bacterial ASVS, and a final summary file used for modeling. R software is needed to run these data, and the packages needed are listed at the top of the R markdown file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Soil biogeochemical properties and metrics of tree-mycorrhizal dominance for a 25-Ha forest in South Central Indiana, USA.

This data package contains a dataset used in the papers “Seeing the forest for all the trees: Mycorrhizal-associated nutrient economies are modulated by stem density and the synchrony between overstory and understory communities” and “Mycorrhizal associations of tree species influence soil nitrogen dynamics via effects on soil acid–base chemistry”. Four csv files are included along with a dataset. The dataset features chemical soil properties for a single sampling campaign within the 25 Ha Lilly-Dickey Woods Smithsonian Forest Global Earth Observatory (ForestGEO) plot in South Central Indiana, USA (ldw_dat_raw.csv). Also included are separate files focused on pH (pH_data.csv), carbon and nitrogen (CN_data.csv), and nitrification rates (Nitrification_data.csv). These variables are commonly associated with the tree-mycorrhizal dominance of forest stands. In these data subsets, each soil variable was matched to a 10 meter radius neighborhood wherein metrics of tree-mycorrhizal dominance (basal area, stem count, importance value, etc.) were calculated. Models between these soil variables and dominance metrics were used to investigate how different assessments of mycorrhizal associated nutrient economies (MANE) capture these relationships. This research was performed as a part of the Smithsonian ForestGEO project. This data package can be used to explore spatial variability in soil chemistry within a mature hardwood forest, or it can be combined with the included tree data, other fine-scale spatial information, or other tree inventory data for the site to evaluate how soil chemistry varies with tree community composition or edaphic or topographic properties.

Craig, Matthew [ORNL] (ORCID:0000000288907920)↗
DOE OSTI2022

Belowground respiration, root traits, and soil characteristics of an East Tennessee deciduous forest, 2019-2020

This dataset contains empirical physiological, morphological, and chemical data of root systems, and elemental, nutrient content for soils collected on forty individuals of eight temperate tree species, between June 2019 and July 2020 at The University of Tennessee Forest Research Center and Arboretum in Oak Ridge, Tennessee. The project used a novel methodology to empirically derive estimates of the autotrophic and heterotrophic components of soil respiration in-situ. The project consists of two measurement approaches. The first set of measurements uses a standard approach for measuring specific root respiration on excised root systems. The second used “in-situ root trays” This dataset includes 10 data files in comma separate (*.csv) ASCII format. Data include measurements of leaf and root functional traits for excised root systems and for living root systems housed within in-situ root trays, data on soil carbon and nitrogen pools, in-situ measurements of soil moisture and temperature, data on soil respiration rates for in-situ root trays (both as soil mass-based fluxes, and soil-area based fluxes), and data on the geographic coordinates and tree sizes of study trees. Forty study trees of eight temperate tree species were studied (five individuals per species). Two in-situ root trays were installed per species, each housing one entire root system comprising < 3 root orders, and still being attached to the tree via transportive root. All respiration measurements were conducted with the Li-6800 portable photosynthesis system (Li-COR, Lincoln, NE, USA). Root respiration measurements of excised root tissues were made using the Li-6800 and the Walz 3010-GWK1 gas exchange chamber (Heinz Walz GmbH, Effeltrich, Germany). Root scan images were analyzed using WinRHIZO. These images are companion files to this dataset and are contained in two compressed (*.zip) folders. Additional metadata are provided: 10 data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

EARTH SCIENCE > BIOSPHERE > VEGETATION > LEAF CHAR↗
DOE OSTI2026

Meteorological and Soil Data from Ecohydrology Sensor Towers at Pump House and Snodgrass Mountain in East River Watershed, Colorado, 2019-2025

This data package includes hourly meteorological and soil sensor data at eight ecohydrology monitoring sites in East River Watershed, Colorado as part of the Watershed Function Scientific Focus Area (WFSFA) research led by Lawrence Berkeley National Lab (LBNL). Four field sites were located on the hillslope of East River (ER) near Pump House (PH) at Mount Crested Butte (ER-PHS1 to 4), and the other four are in the Snodgrass Mountain (SG) area (SG-EHS5 to 8). In terms of vegetation cover, three sites are in montane grasslands (ER-PHS1, ER-PHS2, and SG-EHS5), three are below evergreen conifer canopy (ER-PHS3, SG-EHS6, and SG-EHS7), and two are below deciduous aspen canopy (ER-PHS4 and SG-EHS8). The monitoring period began in October 2019 at the East River sites, in October 2020 at SG-EHS5 and SG-EHS6, and in October 2021 at SG-EHS7 and SG-EHS8. In September 2024, all four East River sites were fully retired. The four Snodgrass Mountain sites remain active. Each site is equipped with a comprehensive suite of meteorological sensors on a tripod and soil sensors that measure weather, energy fluxes, and soil variables. This data package includes measurements from ten different types of sensors and up to thirteen individual sensors per site, including (1) a weather station (measurement height ranges from 2.8~3.8 meters (m) above ground), (2) a quantum sensor for photosynthetic active radiation (PAR) (2.4~3.3m), (3) a net radiometer (1.7~2.1m), (4) an infrared radiometer (1.6~2.2m), (5) a sonic distance sensor (1.5~1.9m), (6) a soil carbon dioxide (CO2) flux chamber (0m), (7) a soil heat flux plate (-0.05m below ground), (8) a soil oxygen sensor (-0.3m), (9) a soil water potential sensor (-0.3m), and (10) soil water content sensors at 3~4 depths (-1.15 ~ -0.1m). A total of twenty-three variables is reported in this data package, including (1) atmospheric variables: air temperature (TA), atmospheric pressure (PA), vapor pressure (VP), and vapor pressure deficit (VPD), (2) precipitation variables: rain precipitation (P) and snow depth (D_SNOW), (3) energy fluxes variables: four-component net radiation (NETRAD) (shortwave/longwave incoming/outgoing radiation, SW_IN, SW_OUT, LW_IN, LW_OUT), photosynthetic photon flux density (PPFD), and soil heat flux (G), (4) soil variables: soil water content (SWC), soil water potential (SWP), soil temperature (TS), soil bulk electrical conductivity (COND_SOIL), and soil gaseous oxygen concentration (O2_SOIL), (5) wind variables: two-dimensional wind speed (WS), gust speed (WS_MAX), and wind direction (WD), and (6) surface variables: surface infrared temperature (T_CANOPY) and soil CO2 flux (CO2_SOIL). Please see the Methods section for data processing and QA/QC steps taken to generate the hourly datasets. The following files are included in this data package (notes on version: v{x}-{y}, where x is the metadata version, and y is the data version, when applicable): (1) “metadata_site_v{x}-{y}.csv” - a site metadata file that summarizes location information of all sites, including site ID, description, coordinates, timeframe, elevation, and vegetation cover, (2) “metadata_instrument_v{x}-{y}.csv” - an instrument metadata file that summarizes sensor information of all sites, including sensor manufacturer and model, measurement height, and sampling and averaging interval of all variables, (3) "data_{SITE_ID}_v{x}-{y}.csv" - eight data files that contain hourly data of each site indicated by {SITE_ID} in the filename, (4) “/figure/data_{SITE_ID}_v{x}-{y}.png" - eight figures that help visualize data of each site indicated by {SITE_ID} in the filename, (5) “/photo/*” - photos of each site indicated by {SITE_ID} in the filename, and (6) four file level metadata (flmd.csv) and data dictionary (*_dd.csv) files that summarize file, header, column, and variable information of all files. Notes: (1) Measurement height: Each variable name is followed by conventional positional qualifiers “H_V_R”, where H indicates the relative horizontal positions of that specific variable, V the vertical positions, and R the replicates. In this data package, only the vertical qualifier V varies, and V increases from the highest vertical position (V=1) to the lowest. Variables with the same qualifier are not necessarily measured by the same sensor, and the same variable with the same qualifier across different sites are not necessarily measured at the same height. Please refer to “metadata_instrument.csv” for the sensor information and measurement heights, and whether a variable is measured below the canopy. (2) Variable availability: Snow depth is not available at ER-PHS3 and SG-EHS7. SWC, soil temperature, and soil bulk EC at the deepest depth (<-1m) are not available at SG-EHS6 and SG-EHS7. The missing value code for numeric variables is -9999, except for SWP. For SWP, the missing value code is +9999, because SWP values are negative. (3) Sampling frequency: Please refer to “metadata_instrument.csv” for the increase of sampling frequency of some variables from 30-min to 1-min at ER-PHS1 to 4 in July 2020. (4) Sensors: While the methods of each sensor are not detailed, all sensors are commercially available, and their methods can be found in their manuals. Please refer to “metadata_instrument.csv” for the sensor manufacturer and model information. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗