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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Soil Characterizations of Five Urban Sites in Knoxville, Tennessee. 2024-2025

This dataset includes soil characterizations from five urban parks in Knoxville, Tennessee, USA: Cumberland Estates Park (CEP), Socially Equal Energy Efficient Development (SEED), West View Park (WVP), Victor Ashe Park (VAP), and West Hills Park (WHP). The dataset consists of seven CSV files reporting the data from the measurements of gravimetric moisture content, pH, total carbon and nitrogen, soil texture, dissolved organic carbon and nitrogen, and microbial biomass carbon and nitrogen derived from these soil cores. During five separate sampling events conducted in 2024 and 2025, five soil cores were collected at each site within 3 meters of the remote soil monitoring equipment. In 2025, an additional three soil cores were collected adjacent to the monitoring equipment at each site to assess soil bulk density. This dataset is part of a larger study investigating the effects of soil moisture and plant evapotranspiration on ambient temperature and relative humidity across multiple urban parks in Knoxville, Tennessee.

Mayes, Melanie A [ORNL] (ORCID:0000000163689210)↗
DOE OSTI2024

Patch-level CO2 and CH4 fluxes and porewater concentrations in experimental wetlands, 2 PPT saltwater intrusion simulations, Aug-Oct 2022: Louisiana

This dataset contains carbon dioxide (CO2) and methane (CH4) flux measurements from patches of wetland vegetation dominated by Typha domingensis and Panicum hemitomon, which were conducted to assess flux responses to acute saltwater intrusion. The measurements occurred before, during, and after simulated acute saltwater intrusion events of low concentrations of ~ 2 PPT. The measurements comprise gas fluxes from the wetland surface (i.e., soil-water column and vegetation) and fluxes from the soil-water column exclusively. These two sets of fluxes are separated into two files and are complemented with four more files containing porewater concentrations of CO2 and CH4 collected at 0-5 cm, 10-15 cm, and 20-25 cm depth increments, spectral indices measurements, biomass, and sediment elevation table measurements. The files can be opened with regular text editors or spreadsheet programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes

This dataset serves as supplementary information for the paper by Ciulla F. and Varadharajan C. A Network Approach for Multiscale Catchment Classification using Traits (see reference 1). It contains environmental and physical catchment traits, such as temperatures, precipitation, land use and human interference, from 9067 sites across the contiguous United States (CONUS). The purpose of this dataset is to provide information for a better trait-based categorization of river catchments in the CONUS using networks as an analytical tool. The traits variables match the ones present in the GAGES-II dataset and the preprocessing steps are described in the Methods section (processed_dataset.csv). Additionally we include the topologies (nodes, edges and clusters, also referred as classes) of the catchment network and traits network generated by said dataset (csv and json files). A series of tables support the information carried by the network providing more detailed descriptions of cluster components (SI1.pdf). A summary of all the plots of clusters of catchments with at least 50 nodes is provided (SI2.pdf). The characteristic traits for each cluster of catchments is presented as z-score (traits_categories_zscores_per_catchment_class.csv). The link to the hydrological behavior of clusters of catchments is displayed by boxplots, each describing a particular river discharge index (SI3.pdf). Both csv and json files can be read by common text editors but the data contained into them can be better handled using programming languages like python and database oriented libraries like pandas. Pdf files can be read by any pdf reader software.[02-23-2024] Update: The code and datasets necessary to reproduce the results of the study are available as a zipped repository (code_datasets_catchments_similarity.zip).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Chamber flux measurements at US-ORv located in Columbus, OH from 2010 to 2014

Closed and flow through chamber methane and carbon dioxide flux measurements were taken at different water depths, vegetation cover types, and times of day at the Wilma H. Schiermeier Olentangy River Wetland Research Park (ORWRP) from 2010 to 2014 to investigate the effects of these variables on gas exchange. The ORWRP consists of two urban experimental wetland basins constructed in 1994 within the footprint of the AmeriFlux tower US-ORv that was functional from 2011 to 2016. Chamber measurements are separated into flow through and closed chamber files (flow_through.csv, closed_chamber.csv) with location labels corresponding with coordinates listed in the metadata file (Location_ID.csv). All files are .csv and could be viewed or analyzed with Excel, MATLAB, Python, or R.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC CHEMISTRY↗
DOE OSTI2023

Continuous soil temperature and soil deformation measurements, Teller road Mile 47, Nome, Alaska.

The dataset comprises Soil Temperature and Deformation monitoring data gathered from a watershed situated along the Nome-Teller road at Mile 47 in Alaska. Its primary objective is to enhance comprehension of deformation mechanisms in permafrost environments by using 51 probes designed following Wielandt et al. (2022). The dataset comprises a description of Probe_ID, Location, start time, end time and probe length in the "ProbesLocations_StartEndDates.csv" file, the 51 data files encapsulated within "Data_files.zip" and the computed deformation for 2023 and 2022 in "Deformation_T47.zip".Each file in Data_files.zip is named as followed "ProbeId_StartMonth_EndMonth.csv". Within each file, the initial column denotes the timestamp in UTC, followed by the sensor’s battery voltage and temperature and acceleration values (X, Y, Z) in subsequent columns. The data collection frequency is set at 30-minute intervals. Each file in Deformation_T47.zip is named as followed "ProbeId_Temp_def_year.csv". Within each file, the initial column denotes the timestamp in UTC, followed by the temperature at each sensor and cumulative deformation from last to first sensor in subsequent columns. The data collection is daily averaged.This dataset forms an integral component of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). 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↗
DOE OSTI2025

Multiple RGB ortho-mosaics and digital surface models in 2017 and 2018 across the Lower Montane site in the East River Watershed, Colorado

Aerial imagery was collected at the Lower Montane site (Pumphouse) in the East River Watershed, Colorado during the spring, summer, and fall seasons of 2017 and 2018 to improve the understanding of seasonal vegetation dynamics and their drivers. The datasets include Red-Green-Blue (RGB) ortho-mosaics and digital surface models (DSMs) inferred from the Unoccupied Aerial System (UAS) acquired aerial RGB imagery for June 3, June 19, July 7, and August 14, 2017, and for March 14, April 26, June 1, June 18, July 6, and August 7, 2018. Real-Time Kinematic Global Positioning System (RTK-GPS) surveyed Ground control points (GCPs) were used to increase the reconstruction accuracy. The reconstructed RGB mosaics and DSMs have been trimmed to cover a similar spatial domain. The accuracy of the RGB mosaics is considered high (~10 cm). DSM accuracy is highest (~10 cm) where sufficient GCPS are available, and more difficult to assess elsewhere (see reconstruction reports for uncertainty estimates). The dataset includes a total of 20 GeoTIFF (.tif) files, 10 PDF (.pdf) files, 3 data CSV (.csv) files, and 2 metadata CSV (.csv) files. Feel free to contact the authors with any questions or collaboration interests.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↗
DOE OSTI2022

Bulk density, grain size, carbon content and isotopes, and nitrogen content of floodplain sediment along the Koyukuk River, Alaska collected in Summer 2018.

The dataset is comprised of grain size, bulk density, carbon and nitrogen content, stable carbon isotopes, and radiocarbon content of soils sampled on the floodplain of the Koyukuk River near Huslia, AK. This dataset was collected to characterize sediment properties and floodplain organic carbon stocks in the discontinuous permafrost floodplain of the Koyukuk River. The data help quantify the flux and storage of sediment and carbon between the Koyukuk River and the surrounding floodplain as the river migrates laterally. The samples were collected in June 27 - July 9, 2018. The soil samples come from a total of 24 locations and were sampled in the upper 490 cm of the river cutbanks, point bars, and floodplain. Samples were analyzed for bulk density, full particle size distribution, nitrogen content and carbon content and isotopes, though not all samples were included in each analysis. An additional 10 samples of floodplain woody debris were measured for radiocarbon content. Data, detailed methods, analyses, and interpretations were previously published at: Douglas, M. M., Lingappa, U. F., Lamb, M. P., Rowland, J. C., West, A. J., Li, G., et al. (2021). Impact of river channel lateral migration on microbial communities across a discontinuous permafrost floodplain. Applied and Environmental Microbiology, 87(20), AEM.01339-21. https://doi.org/10.1128/AEM.01339-21 Douglas, M. M., Li, G. K., Fischer, W. W., Rowland, J. C., Kemeny, P. C., West, A. J., et al. (2022). Organic carbon burial by river meandering partially offsets bank erosion carbon fluxes in a discontinuous permafrost floodplain. Earth Surface Dynamics, 10(3), 421–435. https://doi.org/10.5194/esurf-10-421-2022 The dataset is comprised of a total of three separate data files based on the sample type and analysis, including a file that lists the sample locations, permafrost presence, and geomorphic landform.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Bulk density, grain size, carbon, and nitrogen content of floodplain fine sediment along the East River, Colorado collected from 2014 to 2017

The dataset is comprised of grain size, bulk density, carbon and nitrogen content of soils sampled on the floodplain of the East River 4 to 11 km downstream of Gothic, CO near Crested Butte. This dataset was collected to characterize the sedimentological properties and carbon inventory of the East River floodplain. The data help quantify the flux and storage of sediment and carbon between the East River and the alluvial floodplain bounding the river. The samples were collected between 2014 and 2017. The soil samples come from a total of 156 locations and were sampled in the upper 40 to 60 cm of the floodplain and in abandoned channel segments or oxbows. Not all samples were analyzed for all properties, but 26 samples were analyzed for bulk density, full particle size distribution, carbon, and nitrogen content. An additional 48 samples were analyzed for particle size fraction greater than and less than 2 mm and total organic content determined by loss on ignition. The dataset is comprised of a total of six separate data files based on the sample type and analysis and another file lists the sample identifications and locations of samples with a complete suite of analyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Temperature, Humidity, and Time-Lapse Video Data from Yosemite National Park, Water Year 2024

This dataset contains time-lapse imagery and distributed measurements of air temperature, relative humidity, dew point, and soil temperature across Yosemite National Park from October 2023 to September 2024. Instruments were deployed at 10 sites in two cross-valley transects as part of the DOE Grant: Seasonal Cycles Unravel Mysteries of Missing Mountain Water organized by Jessica Lundquist (University of Washington), Rosemary Carroll (Desert Research Institute), and Ethan Gutmann (National Center for Atmospheric Research). The data are intended to support hydrologic modeling efforts to better resolve the fate of mountain water, and are published to support studies of surface climate or hydrologic processes in complex terrain. Measurements were collected with low-cost data loggers installed 2 m high on evergreen trees or buried just below the soil surface. A time-lapse camera at one site captures valley-scale seasonal snow cover variability.Dataset files are organized by site and variable (air measurements, ground measurements, or time-lapse video). Air and ground measurements are packaged in LoggerData.zip, and time-lapse imagery is compiled into a short video stored in TimelapseVideos.zip. File-level metadata contains details for each file included in the dataset. A data dictionary provides units and descriptions for column or row names in all files. The locations metadata file describes site characteristics, locations, and associated GPS methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Classified channel masks of the East River, Colorado, U.S.A and areas of floodplain erosion and accretion ranging from 1955 to 2015

This dataset provides four sets of geotiffs used for the mapping and analysis an alluvial floodplain reach of the East River, downstream of Gothic, CO, U.S.A near Crested Butte. The files include binary masks of the river channel at five in intervals from 1955 to 2015. Another set of rasters provide a map of the channel centerline pixels of the river for each date. Also included in the dataset are rasters of the areas of channel change due to migration over 8 time intervals. The masks were generated from aerial and satellite imagery collected on seven dates over a sixty-year timespan: 1955, 1973, 1983, 1990, 2001, 2011, and 2015. The masks were analyzed using the Spatially Continuous Riverbank Erosion and Accretion Measurements (SCREAM) software detailed in Rowland et al. 2016 to create the channel centerlines and the change area rasters. The change masks were generated for the following time periods: 1955-1973; 1955-2015; 1973-1983; 1983-1990; 1990-2001; 2001-2011; 2001-2015; and 2011-2015.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

UAS remote sensing (DJI Phantom 4 RTK platform): RGB orthomosaic, digital surface and canopy height models, plant functional type map, Seward Peninsula, Alaska, 2019

Airborne remote sensing data collected using a DJI Phantom 4 RTK unoccupied aerial system (UAS) ? operated by the University of Maine Wheatland Geospatial Lab (https://wheatlandlab.org/). This package includes data from 17 flights flown over the NGEE-Arctic Council, Kougarok, Kougarok Mile80, Teller, and Teller Mile32 sites in July 2019. The Phantom 4 RTK is a drone platform that collects very high spatial resolution optical red/green/blue (RGB) imagery. Derived image products include point cloud, ortho-mosaiced RGB, a digital surface model (DSM) using the structure from motion (SfM) technique, and a canopy height model (CHM). Unprocessed and processed data products (1,000+ files) are included in this package (processing levels 0-3). Data and metadata are provided as text (*.txt, *.json, *hdr,), ENVI image file (*.dat), point cloud (*.laz) and image (*.jpg, *.tif, *png) formats. 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↗
DOE OSTI2024

Aqueous Organic Matter from Kougarok Fire Complex, Alaska, 2023

Chemical analyses of aqueous organic matter extracted by filtration from a small set of organic layer samples collected from burned and unburned tussock tundra sites in the Kougarok Fire Complex, near Nome, Alaska. There are five files in *.csv format with one data file and four data description files including data dictionary, methods, terminology, and file-level metadata.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↗
DOE OSTI2025

Soil microbial ecology and microbiome-metabolite linkages improve understanding of ecosystem states along terrestrial-aquatic interfaces

These data are from Bandopadhyay et al., "Soil microbial ecology and microbiome-metabolite linkages improve understanding of ecosystem states along terrestrial-aquatic interfaces". This study aims to understand the soil microbial ecology along terrestrial-aquatic interfaces of a freshwater and estuarine region and how it relates to organic matter. We analyzed soil microbial (16S rRNA gene) and organic matter (Fourier-transform ion cyclotron resonance mass spectrometry, FTICR-MS) composition from upland (forested), transition (stressed forest), and wetland positions at three sites in each of the Lake Erie (freshwater) and Chesapeake Bay (estuarine) regions. This dataset includes 16S rRNA gene amplicon data (only processed file types included here) and organic matter composition from FTICR-MS data (raw and processed files included here) from upland (forested), transition (stressed forest), and wetland positions at three sites in each of the Lake Erie and Chesapeake Bay regions. These sites are part of the COMPASS-FME project (https://compass.pnnl.gov/FME/COMPASSFME). File formats and software needed to access files: 16S rRNA gene amplicon data: These files follow the format reported here https://ess-dive.gitbook.io/amplicon-sequencing-reporting-format#updates-in-v1.0.1. As per this format, there are four file types reported: 1. Taxon tables (also called sequence-by-sample or OTU (operational taxonomic unit)/ESV (exact sequence variant) tables) : available in a .txt file format and accessible using TextEdit or MS Excel. 2. Representative sequences (also called consensus sequences) : available in a .fasta format and accessible using TextEdit. 3. Sequencing metadata : available in a MS Excel workbook file format and CSV file format 4. Bioinformatic metadata : available in a MS Excel workbook file format and CSV file format FTICR-MS data: 1. Raw data converted to a processed file with intensities of the peaks in the given samples : available in a MS Excel CSV file format 2. Processed file used in analyses and visualizations (appended as icr_long_) : available in a MS Excel CSV file format 3. Metadata file for ICR features (appended as icr_meta) : available in a MS Excel CSV file format

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Spatially Averaged Ice Contents of Ice-Wedge Polygon Cross-Sections to 3-m Depth, July 2013, Utqiagvik, Alaska

This dataset contains spatially averaged estimates of ice content (volume percent) for two-dimensional cross-sectional profiles (from trough center to trough center to a depth of 3 meters) of low- and flat-centered ice-wedge polygons (three of each type) located near Utqiagvik, Alaska. A combination of soil pits, trenches, and cores were used to describe, sample, and map the cross-section stratigraphy of soil horizons and ice wedges for each polygon at 6 depth intervals. Observed soil horizons were assigned to four types with increasing amounts of organic components (mineral, mineral/organic, organic/mineral, and organic). The average ice contents of each soil horizon type below the permafrost boundary and wedge ice were weighted by their cross-sectional area fractions to calculate spatially averaged estimates of ice content for each polygon. In the active layer, spatially averaged estimates of volumetric water contents were similarly determined and reported here as “ice” content to enable estimates of the soil’s structurally competent porosity and excess ice in permafrost layers. In this dataset, the file AK13_ice_contents.csv includes cross-sectional area fractions and spatially averaged ice contents for soil layers and horizon types at the six depth intervals. The file AK13_permafrost_ice_fractions.csv contains the calculated partitioning of ice contents into pore ice and excess ice fractions for the three permafrost-dominated depth intervals. In addition, there is a data dictionary file for each of these data files and a file-level metadata file. These data were generated by the Department of Energy’s Soil Carbon Response to Environmental Change Scientific Focus Area and were used as inputs to model simulations examining the consequences of thaw-affected subsidence and microtopography change on active layer thickness of low-relief polygonal tundra landscapes in a warming Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Microbial community data from throughfall exclusion experiment: Metadata, SI, community composition, LefSe, and FunGuilR data tables from PARCHED Panama tropical forest soils, 2024-2025

Soil contains more carbon (C) than terrestrial vegetation and the atmosphere combined, with some of the largest terrestrial C stocks in tropical rainforests. Soil microbes decompose organic matter, playing a vital role in the storage or loss of soil C. With climate change, drought conditions are predicted to increase in many tropical regions, including both chronic drying and extended drought, potentially influencing these processes. This project explored the effects of chronic and seasonal drying on soil microbial communities across four distinct tropical forests in a long-term drying experiment. We investigated the effects of a chronic drying manipulation on soil microbial community abundance and variation across different forests and seasons. We also compared findings with previously published data from these forests after short-term drying. This project used soils from a long-term drying experiment established in 2018 across four seasonal lowland forests in Panama. Soils were collected from 0 – 10 cm depths during three seasonal periods in control and drying plots in 2024 and 2025 from a total of 32 plots (n = 4 per forest per treatment). The forests varied in baseline rainfall and soil fertility. We calculated alpha and beta diversity indices and compared taxonomic community composition. We found significant biogeographic variation in microbial diversity and taxonomy, with significant differences across the forests and significant effects of the drying treatment. Metadata and sample IDs are within Metadata_16S.csv and Metadata_ITS.csv. Relative abundance tables of every sample at every season are shown in the Excel workbooks 16S Relative Abundance.xlsx and ITS Relative Abundance.xlsx. They are then also shown in CSV files by each taxonomic level. Linear discriminant analysis effect size (LefSe) tables are shown for the full 16S and ITS datasets (n = 96), subsets for every site at every season (n = 8), and then for the forests with each plot merged by season (n = 8). FunGuildR data table of ITS data is uploaded.

Bacteria↗
DOE OSTI2024

Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics (Blodgett, CA)

This dataset contains data on daily soil temperature, moisture and flux, and soil carbon stock and root biomass across a soil profile down to 100 cm depth at Blodgett Forest Research Station, CA, USA. These data were generated to determine if modeling of an experimental soil warming of 4C showed increased soil CO2 emissions and changes in bulk soil carbon stocks with depth consistent with field observations, as part of the study: Riley et al. (2025) Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics in Journal of Advances in Modeling Earth Systems. This research was performed within the framework of the TES Belowground Biogeochemistry SFA project, in particular association with a 1 m-deep experimental soil heating experiment at the University of California Blodgett Forest Research Station, California (120 ° 39′40′′W; 38 ° 54′43′′N). Continuous data were collected at the plot level, and bulk soil carbon and root biomass were sampled once a year from each plot from 0-100 cm, in 10 cm intervals. Measurements relevant to the current study include soil temperature and soil volumetric water content measured continuously at multiple depths in the top meter; fine root biomass and SOC stocks measured from annual soil cores. Soil flux was continuously monitored using a LI-8100 Automated CO2 Flux System in conjunction with the LI-8150 Multiplexer (Licor, Nebraska, USA). Soil flux was determined using SoilFluxPro software, with flux values showing an R² fit of less than 0.9 being excluded from the analysis. Data were collected from each paired plot (1-3): one control (C) and one heated (H).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

NEON AOP Survey of Upper East River CO Watersheds: LAZ Files, LiDAR Surface Elevation, Terrain Elevation, and Canopy Height Rasters

Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest surrounding Crested Butte, CO with remotely sensed data, including LiDAR. The flight box design encompassed the watersheds, surveying a total area of 334 km2 across 72 lines. The instrument used was an Optech Gemini, with a pulse density of 2-9 pulses m-2 across the study area (see final report document for detailed information (Goulden and Musinsky 2020). These LiDAR data are the primary data that were provided by NEON, and include both LiDAR source data and derived surface products. The source data are contained in 'crbu_laz.zip' and 'classified_point_cloud.zip. 'classified_point_cloud.zip' represents an additional processing level on 'crbu_laz.zip'. The derived products are 'dsm_mosaic_min_phase_me.tif', 'dtm_mosaic_min_phase_me.tif', and 'tch_mosaic_min_phase_me.tif'. These files are raster mosaics of a digital surface elevation model (DSM), digital terrain elevation model (DTM), and a canopy height model (CHM) at 1 m resolution with a height threshold of > 2 m, respectively, in geotiff (.tif) format. 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. [UPDATE] On 06/26/2026 the files 'crbu_laz.zip' and 'classified_point_cloud.zip' were replaced with original output files from NEON to address zip file corruption and naming errors. No changes were made to the underlying data. (See Methods Step 2 for details).

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2020

Gap-filled water quality, Normalized Differenced Vegetation Index, total nitrogen (nitrate and ammonia) deposition, and land cover data trends for the Continental United States

The purpose of this work was to quantify trends in water quality, total nitrogen deposition, vegetation, and land-use trends for the Continental United States (CONUS). This dataset contains gap-filled daily and yearly in-stream carbon (C) and nitrogen (N) concentrations, discharge, and calculated exports from United States Geological Survey (USGS) National Water Information System (NWIS) stations across the United States of six different nitrogen parameters (Supplementary Table A1), one carbon parameter, and temperature (USGS, 2016, 2018) (https://waterdata.usgs.gov/nwis). The final water quality dataset is merged with the normalized differenced vegetation index (NDVI), total deposition (TDEP), landcover, and elevation datasets. All data are available at the CONUS scale as well as at the scale of hydrologic unit codes: (HUC) HUC8, HUC6, HUC4, and HUC2 watersheds. There are two zip files associated with this data package. I split the data into two equal sized zip files to comply with the data size limits, however the datasets are the same within each zip file. All data files can be read in directly into the R software.

54 ENVIRONMENTAL SCIENCES↗