Search NASA⌕ Search

SEARCH · Search NASA

Results for “file format”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (August 2015)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken August 29, 2015 at a location (KB1) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Sediment samples from a deep soil pit were collected from 0 to 234 cm depth below surface at discrete depths every ~10-20 cm for microbial analyses. 13 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0131241. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores).This dataset includes a zip file of 2216 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type

54 ENVIRONMENTAL SCIENCES↗

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (June to October 2019)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken at three time points from June 12, 2019 to October 23,2019 at a location (PTT1) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Sediment samples were collected from 60 to 180 cm below surface every 30cm for microbial analyses through metagenomic sequencing. 15 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0131241. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 780 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. A sample metadata file (samples.csv) that contains site information has also been included.

54 ENVIRONMENTAL SCIENCES↗

Metagenome-assembled genomes from Wind River Basin floodplain sediments Riverton, Wyoming site (May to September 2017)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken roughly every month in the period May 18 to September 13 in 2017 at a location (Pit2) close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site in the Wind River Basin (WRB). The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Cores were taken with a hand-auger and separated into 5-20 cm segments based on soil horizonation down to 150 cm depth below surface. Each segment was subsampled for microbial analyses. Corresponding 16S rRNA gene amplicon data is available at the NCBI Single Read Archive (SRA) Database BioProject ID PRJNA626616, and soil geochemistry data at doi:10.15485/1631972. 40 metagenomes were sequenced through JGI and can be found under Gold sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 6993 MAG fasta files and a csv file with quality, taxonomic classification (GTDB RS220), and metagenome accessions for MAGs generated from the Wind River Basin (WRB). This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗

Topography, surface water distribution and subsurface structure in 2023 across an Arctic coastal tundra site near Utqiagvik, Alaska

Subsurface electrical resistivity tomography (ERT), active layer thickness measurements, photogrammetry, and topographic data were collected in September 2023 along a 475 m long, 20 m wide corridor that traverses various polygon types within the Barrow Environmental Observatory (BEO) on the Alaskan Arctic Coastal Plain, approximately 4 miles from the Beaufort Sea near Utqiaġvik, Alaska. These measurements were designed to assess decadal changes in surface water distribution, topography, and subsurface structure across this dynamic landscape. This archive contains the datasets acquired in 2023 and references to the datasets acquired previously at the same location. The ERT survey was conducted along the 475 m transect using 0.5 m electrode spacing and a roll-along acquisition strategy. Thaw layer thicknesses were measured with a tile probe along the same transect. Photogrammetry data were acquired using an unoccupied aerial vehicle (UAV) and were used to generate a digital elevation model and an RGB mosaic. A real-time kinematic (RTK) GPS was used to survey the ERT electrodes and the ground control points for the aerial imagery. The dataset contains 5 *.csv data files, 6 *.csv metadata files, and 6 *.tif files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was 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↗

Stream bed topography in 2016 at the Lower Montane site in the East River Watershed, Colorado

This dataset contains stream bed topography data from the Lower Montane site in the East River Watershed, Colorado. It is intended to support hydro-biogeochemical analyses for the Watershed Function Scientific Focus Area (SFA). The stream bed was surveyed using a RTK-GPS (Real-Time Kinematic Global Positioning System) and a total station at hundreds of locations during two field campaigns, conducted in October 2015 and October 2016. The two surveys were merged into a single product under the assumption of minimal changes in stream bed topography between the years. A LiDAR (Light Detection and Ranging) derived ground surface elevation product from 2015 (see reference below) was used to interpolate the stream bed topography and estimate water depth at the time of the LiDAR survey. The dataset includes three GeoTIFF products, two *.csv data files, and three *.csv metadata files. Feel free to contact the author with any questions.

54 ENVIRONMENTAL SCIENCES↗

Soil moisture and temperature from 2019 to 2024 along northeast- and southwest-facing hillslopes at the Lower Montane site in the East River Watershed, Colorado

Soil moisture, temperature, and electrical conductivity have been monitored at multiple depths (between 10 and 50 cm) at 4 locations along a northeast-facing slope and 3 locations on the opposite southwest-facing slope at the Lower Montane site in the East River Watershed, Colorado, from Oct 2019 to Oct 2024. The purpose of this data is to inform hydro-biogeochemical analyses for the Watershed Function Scientific Focus Area (SFA). Two locations on the northeast-facing slope were reinstalled in 2020 due to damage from wildlife, and thus data for these sites are provided in two distinct files. Overall, the data are reported in 9 CSV files containing the measurements, and the locations are provided in the Sensor_Location.csv file. There is a total of 10 *.csv data files and 3 *.csv metadata files. Older datasets associated with the northeast-facing slope are provided in another archive (see reference). These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales. Feel free to contact the author with any questions or collaboration interests.

54 ENVIRONMENTAL SCIENCES↗

Metagenome-assembled genomes measured at 3 depths during snowmelt period in East River, CO (March, May, and June, September 2017)

Snowmelt is a critical biogeochemical period that accounts for large nitrogen (N) export events from high-elevation watersheds. Soil microbial populations bloom and immobilize N during snowmelt, yet the population size crashes in spring, which releases a pulse of soil N. We sought to discover the N sources fueling this microbial bloom and determine the fate of N following microbial die-off. Here, focusing on the snowmelt period within a headwater catchment of the Upper Colorado River Basin (East River, CO), we deployed strain-resolved metagenomics to identify the metabolic pathways and processes that mobilize soil N during and after snowmelt. Soil metagenome samples were taken from 6 snowpits from 3 depths (0-5cm, 5-15cm, >15cm) at 4 time points during snowmelt period (March 2017, May 2017, and June 2017, September 2017) generating 48 metagenomes. We reconstructed 474 metagenome-assembled genomes (MAGs) across all metagenomes.All 48 metagenomes were sequenced at JGI and raw data can be found under JGI (Joint Genome Institute) GOLD Study Gs0135149. Metagenome assemblies from IMG under the same study were used for genome binning. This dataset (1) a zip file of 474 MAGs (as fasta files, Gs0135149_bins_tar.gz), (2) sample metadata file with sample IGSNs (International Generic Sample Numbers) (samples.csv), (3) bounding box coordinates for the sampled locations (Gs0135149.kml), (4) metagenome metadata file listing IMG/M (Integrated Microbial Genomes/Metagenomes) metagenome accessions linking samples to metagenomes (metagenomes.csv), (5) location metadata file (locations.csv), (6) file-level metadata file (flmd.csv) and (7) data dictionary (dd.csv) file.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↗

Organic Matter Composition in June 2023 and September 2023 Across the McKenzie Sub-Basin Impacted by the 2020 Holiday Farm Fire

This dataset represents results from a field study aiming to understand the variability in post-fire responses of dissolved organic matter and determine drivers of post-fire responses. Samples were collected at 58 sites within the McKenzie River Watershed (Oregon, USA) that were upstream, within, and downstream of the Holiday Farm Fire burn perimeter. The samples were collected in June 2023 and September 2023 during storm events, approximately 3 years post-fire. Samples were characterized for benezenepolycarboxylic acids (BPCA) and ultra-high resolution mass spectrometry. Dissolved organic carbon and optics (absorbance and fluorescence) data can be found in a separate data packages (https://ir.library.oregonstate.edu/concern/datasets/zc77sz60m, https://ir.library.oregonstate.edu/concern/datasets/mc87q034m). Related data from a subset of sites from 2020-2022 can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1869708 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2478546. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset contains (1) file-level metadata; (2) data dictionary; (3) data package readme; (4) metadata; (5) methods information; (6) benzene polycarboxylic acid (BPCA) concentration data; (7) Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) methods; (8) folder of high resolution characterization of organic matter via 12 Tesla FTICR-MS data generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This package contains the following file types: csv, xml, pdf.

54 ENVIRONMENTAL SCIENCES↗

Laboratory time series moisture manipulative experiment from sediment across San Antonio, Texas: time series aerobic respiration and geochemistry

This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration. 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 Allison Veach collaboration (AV1). The data package associated with the AV1 study is available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2529428. AV1 sampling occurred across 7 perennial and 7 intermittent streams in San Antonio, Texas. Each stream/site was visited both in summer during base flow (July-September 2023) and winter during peak flow (January-February 2024). This study uses subsamples from a subset of AV1 samples. The original field samples were labeled as AV1_###. Subsequent subsamples for this study were labeled as EV_###. The labels from the field samples and the EV subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EV_001 is a subsample from AV1_001). See the critical details section below for more details on sample naming. 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 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) effect size; (2) iron (II); (3) gravimetric moisture; (4) respiration rates; (5) raw dissolved oxygen values and plots; (6) specific conductance; (7) pH; (8) temperature; (9) a summary containing mean, median, and standard deviation values of each data type for each treatment (wet and dry); and (10) methods codes. All files are .csv or.pdf.

54 ENVIRONMENTAL SCIENCES↗

Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry at Council Road Site Mile Marker 71, Seward Peninsula, Alaska, 2023

Data collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by centrifuging soil cores and also by field collection with porewater samplers (rhizons). Gas data consists of CO2, CH4 and N2O surface soil fluxes measured with a portable FTIR analyzer. Plant and root data consists of biomass, root length, diameter and mass. Soil data consists of total C and N. Air, water and soil samples span two main locations: a thermokarst wetland and an upland tussock. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was 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).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2, CH4 and N2O?Description of the contents of this data package: This dataset contains 5 different individual .csv files containing plant, soil, water and gas data. No software is needed to utilize them. PFTCover: Plant functional type ground cover in 1x1 meter plots. SoilCores: Solidphase and porewater phase soil biogeochemical variablesPlantData: Above and belowground plant traits. GasFlux: Surface plant-soil gas measurementsFieldPorewater: Field collected porewater biogeochemical variables

54 ENVIRONMENTAL SCIENCES↗

Metagenome-assembled genomes from topsoils along a hillslope water gradient across early snowmelt to late summer in East River, CO

Drought is changing the American Mountain West at unprecedented rates with unknown consequences to soil microbiome composition and function. As a part of LBNL Watershed Science Focus Area (SFA), we investigated shifts in microbial community and transcriptional activity on a subalpine conifer-meadow transition zone throughout the summer of 2023 as soil dried down. This work took place in Crested Butte, CO on Snodgrass mountain, using a proxy for drought conditions.Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal community at 0-10cm from three sites along a hillslope water gradient across five timepoints from early snowmelt to late summer. 42 metagenomes were sequenced at Joint Genome Institute (JGI) and can be found under the JGI GOLD (Genomes Online Database) sequencing project Gs0166660. Metagenomes were assembled through an inhouse pipeline (see methods), binned using four autobinners (concoct, maxbin2, metabat2, and vamb) and consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>70%) and contamination (<10%), and dereplicated at 95% ANI using drep. This dataset (1) a zip file of 157 MAGs (as fasta files, Gs0166660_bins_tar.gz), (2) sample metadata file with sample IGSNs (International Generic Sample Numbers) (samples.csv), (3) bounding box coordinates for the sampled locations (Gs0166660.kml), (4) metagenome assembly and coassembly metadata file listing IMG/M (Integrated Microbial Genomes/Metagenomes) metagenome accessions linking samples to metagenomes (EastRiver_Drought_ESSDive_Metadata.csv), (5) location metadata file (locations.csv), (6) file-level metadata file (flmd.csv) and (7) data dictionary (dd.csv) file.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↗

Vegetation transect surveys from 2022 and 2023 within the Kougarok Fire Complex (KFC) on the Seward Peninsula in Alaska, USA

This dataset contains recorded vegetation classifications from 16 transects within the Kougarok Fire Complex (KFC) area in Alaska. Each transect is 50 meters long, and vertical vegetation profiles were sampled every 50cm, resulting in 101 points recorded for each transect. At each point, a vertical rod was inserted in the ground and any living plant or substrate touching the rod was recorded from top to bottom. For each plant, the plant functional type (PFT) and species name was identified and recorded. The file "flmd.xlsx" provides file level meta data for all other included files. The file (transect_metadata.csv) contains descriptive information about each of the 16 transects (field observation year and date; latitude and longitude GPS measurements of the 0, 25, and 50 meter points; and whether that area burned during the 1971, 1997, 2002, 2015, and/or 2019 fires). The files (PFT_names.csv and species_names.csv) map the short hand labels for the plant function type (PFT) and species used in the transect surveys to their full names. The remaining files are named for each transect, and contain the results of the vegetation survey for each transect. These files contain the plant functional type and the species identified at each point. Points along the transect with more than one species at that point are listed vertically from top to bottom in these files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was 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↗

Snow Depth Datasets for Snodgrass Catchment, Colorado, Water Year 2022-2023

This data package presents snow depths data from distributed temperature probes at 18 locations near Snodgrass catchment, Colorado. These data show that snow melt-out dates are approximately one or two weeks later under evergreen forests compared to other vegetation types even at the same elevation. These data were collected to understand how snowmelt heterogeneity impacts headwater hydrology, including streamflow and groundwater levels. They were also used to compare with process-based model simulations of snow depth to evaluate whether the model accurately represents snowmelt dynamics and their effects on headwater hydrology. Snow_DTPs_locations.csv includes all probes locations and their associated elevation and vegetation types. Snow_Depth_Snodgrass_WY2022_2023.csv includes processed snow depths datasets for Water Year (WY) 2022 and 2023. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. Several probes have recordings for WY 2021.

54 ENVIRONMENTAL SCIENCES↗

Montane Conifer, Aspen, Meadow, and Sagebrush Metagenome Resolved Genomes and Traits in East River Watershed, Colorado, USA

Climate change is driving vegetation shifts in mountain watersheds, with unknown impacts on biogeochemical cycles. We hypothesize that these shifts will reshape soil microbiomes and associated biogeochemical processes. As a part of Lawrence Berkeley National Laboratory (LBNL) Watershed Science Focus Area (SFA), we assessed microbiome and microbial functional trait differences between soils under conifer, aspen, forby meadows, and sagebrush across the East River Watershed, CO, controlling for elevation and aspect.Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from soils 0-20cm in depth across three locations in the watershed—Headwaters, Upper Reaches, and Lower Reaches from August 3-11th 2016. Each location was further subdivided into two blocks, with one block on a west facing aspect, and two on the east aspect of the valley. Within blocks, two samples per vegetation type were taken (one at each depth). This resulted in 66 samples, which were sequenced at JGI and can be found under the Joint Genome Institute (JGI) Genomes Online Database (GOLD) sequencing project Gs0118068. Metagenomes were assembled through an inhouse pipeline (see methods), binned using four autobinners (concoct, maxbin2, metabat2, and vamb) and consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>75%) and contamination (<25%), and dereplicated at 95% ANI using drep. The dataset includes a zip file of 687 genomes (Vegtype_MAGS.zip), the accession numbers for the underlying metagenomes, a csv file with MAG quality metrics and taxonomy from Genome Taxonomy Database (GTDB) and National Center for Biotechnology Information (NCBI) taxonomic representative genome proteins (EastRiver_Vegtype_drep_genome_info.csv), and a file containing MAG quality metrics and taxonomy (gtdb_drep_bin_taxonomy.csv). The dataset additionally includes a sample metadata file (EastRiver_Vegtype_sample_metadata.csv), a metadata file used to register associated samples with IGSNs (International Generic Sample Numbers) (samples.csv), a Google KML file for the sampled locations (sample_collection_sites.kml), a location metadata file (locations.csv), a file-level metadata file (flmd.csv), and a data dictionary (dd.csv) file.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↗

Data from: “Bald Cypress (Taxodium distichum) Knees Are Methane Sources Controlled by Geomorphology, Climate, and Hydrologic Extremes”

This dataset is associated with the manuscript “Bald Cypress (Taxodium distichum) Knees Are Methane Sources Controlled by Geomorphology, Climate, and Hydrologic Extremes”. Bald cypress “knees” (aboveground woody roots) have been shown to contribute to wetland methane (CH4) efflux, with large variation within and between studies. To explain this variation, we investigated spatial (i.e., across knee surface, within sites, between sites) and temporal dynamics of CH4 fluxes from knees. Methane fluxes were collected from September 2022 to August 2024 at three locations in western Kentucky, USA, within the Mississippi Alluvial Valley: a main channel (semi-permanently flooded), side channel (seasonally flooded), and reservoir edge (artificially flooded). Knee CH4 fluxes (“Ross_et_al_Knee_Flux_Data.csv”) were measured from multiple heights on knees (20, 40, and 60 cm) of various sizes (knee straight height ranged from 24 to 93 cm) using a LiCOR LI-7810 CH4/CO2/H2O Trace Gas Analyzer. The dataset also includes environmental variables collected with each knee measurement, including water level adjusted for knee-to-knee elevational differences, subsurface and air temperature, and humidity. Soil CH4 fluxes (“Ross_et_al_Soil_Flux_Data.csv”) were also collected adjacent to knees (starting in April 2023) when water levels didn’t overtop soil collars, using a LiCOR Smart Chamber and calculated in SoilFluxPro software. The soil flux dataset includes associated variables collected by the Smart Chamber. Three separate files (“*_Water_Level.csv”) are included for water level and subsurface temperature data collected at each site using HOBO U20L barometric pressure loggers. Each file type (knee flux, soil flux, water level) has an associated data dictionary (“*_dd.csv”). For specifics on methodology used and calculations, see the associated manuscript. The R script includes code used for figures and analyses reported in the manuscript.

54 ENVIRONMENTAL SCIENCES↗

Temporal Study 2022-2024: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, Turbidity, Chlorophyll A, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin in Washington, USA

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides periodic (bi-weekly or monthly) in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata collected at six sites across the Yakima River Basin in Washington, USA. Sample and sensor data from previous years (2021-2022) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054, respectively. Related sample data from 2022-2024 are available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2562910. 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 contains a folder of environmental context photographs and videos and (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) field protocols; (6) international generic sample number (IGSN) mapping file; (7) handheld sensor data; and (8) two sensor subfolders. Each sensor subfolder (BarotrollAtm and MantaRiverData) contains a subfolder containing sensor time series data and plots. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL sensor pressure and air temperature data. The MantaRiverData subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and chlorophyll A. All files are .csv, .pdf, .jpg, .jpeg, .mp4, .png, or .mov.

54 ENVIRONMENTAL SCIENCES↗

Groundwater elevation data for monitoring wells within the East and Taylor River basins, Colorado (USA)

This dataset is comprised of temporal variations in groundwater elevation data for the 24 monitoring wells located throughout the East River watershed. Seasonal to annual variations in groundwater elevations are a critical property of mountainous watersheds needed to understand both hydrological and below ground biogeochemical processes. Such data serve as a critical constraint for numerical models describing coupled groundwater-surface water behavior within the watershed. Additionally, the offset between the maximum and minimum groundwater elevations defines the extent of the bedrock weathering zone, with annual excursions in the groundwater hydrographic (i.e., the rising and falling hydrographic limbs) imposing primary controls on bedrock saturation state and redox conditions that govern biogeochemical reactions impacting nitrogen, carbon, and metals cycling. Manufacturer-specific software is used to download pressure data from each transducer, with broadly available spreadsheet software (e.g. Microsoft Excel) used to convert temporal variations in water pressure to elevations in units of meters above mean sea level. As additional monitoring wells are installed within the East River watershed and new groundwater monitoring wells are installed in the Taylor River watershed, temporal groundwater elevation data will be included as a part of this master dataset. Details regarding the metadata associated with each monitoring well location, including well depths, screened intervals, well location coordinates, and bedrock type, are included, as is a standard operating procedure for generating groundwater elevation data from water pressure values recorded by the pressure transducers. This dataset includes: (1) a zip file (East_River_Watershed_Compiled_Groundwater_Elevation_Data_Plots.zip), containing (a) PNG of groundwater hydrographs, (b) a CSV file with groundwater elevation data, and (c) CSV file containing metadata organized by location; (2) an Excel file (East_River_Watershed_Compiled_Groundwater_Elevation_Data_Plots.xlsx) with the groundwater elevation data, groundwater hydrographs, and metadata organized by location; (3) a Word file (Groundwater_elevation_data_protocols.docx) and a PDF file version (Groundwater_elevation_data_protocols.pdf) containing field protocols and methods; (4) a location metadata (locations.csv) file; (5) a file level metadata (flmd.csv); and (6) data dictionary (dd.csv) file.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↗

COMPASS-FME Synoptic Site Characterization

This dataset contains soil biogeochemical and physicochemical characterization data for the COMPASS-FME synoptic sites.This dataset also contains data for the paper Patel et al. 2025 "Transition zones at the changing coastal terrestrial-aquatic interface", https://doi.org/10.1029/2025JG008978.Coastal soils are a significant but highly uncertain component of global biogeochemical cycles. These systems experience unique spatial and temporal variability in biogeochemical processes, driven by wetland-to-upland gradients and hydrological fluctuations. We studied drivers of coastal soil variability (a) at regional scales and (b) across transects from upland forest to wetland, in two contrasting regions — Lake Erie, a freshwater lacustrine system, and Chesapeake Bay, a saltwater estuarine system. Salinity-related analytes were a key driver of soil variability, not just in the saltwater system, but surprisingly, also in the freshwater system. We had hypothesized linear trends in biogeochemical parameters along the TAI – however, contrary to expectations, transition soils were not consistently intermediate between upland and wetland endmembers; the non-monotonic trends of carbon, phosphorus, iron along our transects suggest that these are key analytes to study in our regions. Rapidly changing soil factors across coastal gradients provide insights into which soil processes may act as precursors to ecosystem shifts. Our comprehensive soil characterization across the coastal transects provides essential data for mechanistic modeling of ecosystem dynamics.The data are provided as processed, csv files. Raw data and processing scripts can be accessed on GitHub (https://github.com/COMPASS-DOE/cmps-soil_characterization).A note on the nomenclature: the experimental design represents three points along the coastal gradient -- upland, transition, and wetland. "wetland" is referred to as "marsh" in the corresponding paper. The two terms can be used interchangeably for the sites in this study.

54 ENVIRONMENTAL SCIENCES↗