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Inelastic neutron scattering data measured on ARCS, CNCS, and HYSPEC are provided here. The .nxs files contain complete datasets and the .txt/.dat files contain the data slices extracted from those datasets and used to generate the figures presented in the manuscript. The datasets have been reduced using MANTID and SHIVER.
-Contents of the Data Repository: - Polarized neutron diffraction data acquired in the (HK0) scattering plane. - Inelastic neutron scattering (INS) data from both unpolarized and polarized measurements with an incident neutron energy of Ei =9 meV.- - Reduced multidimensional single-crystal datasets (MDE) and corresponding S(Q,ω) slices used to generate all figures presented in the manuscript. - Julia source code and supporting input files used for spin-wave calculations, model fitting, and simulation of neutron scattering intensity maps.
To reduce the geothermal exploration risk, a feasibility study is performed for a deep direct-use system proposed at the West Virginia University (WVU) Morgantown campus. This study applies numerical simulations to investigate reservoir impedance and thermal production. Because of the great depth of the geothermal reservoir, few data are available to characterize reservoir features and properties. As a result, the study focuses on the following three aspects: 1. model choice for predicting reservoir impedance and thermal breakthrough: after investigating three potential models (one single permeability model and two dual permeability models) for flow through fractured rock, it is decided to use single permeability model for further analysis; 2. well placement (horizontal vs. vertical) options: horizontal well placement seems to be more robust to heterogeneity and the impedance is more acceptable; 3. Prediction uncertainty: the most influential parameters are identified using a First-Order-Second-Moment uncertainty propagation analysis, and the uncertain range of the model predictions is estimated by performing a Monte Carlo simulation. Heterogeneity has a large impact on the perdition, therefore, is considered in the predictive model and uncertainty analysis. The numerical model results and uncertainty analysis are used for economic analysis. The dataset submitted here support the described study. Manuscript is submitted to Geothermics, will be linked once paper is accepted.
Characterizing the stimulation mode of a fracture is critical to assess the hydraulic efficiency and the seismic risk related to deep fluid manipulations. We have monitored the three-dimensional displacements of a fluid-driven fracture during water injections in a borehole at ~1.5 km depth in the crystalline rock of the Sanford Underground Research Facility (USA). The fracture initiates at 61% of the minimum horizontal stress by micro-shearing of the borehole on a foliation plane. As the fluid pressure increases further, borehole axial and radial displacements increase with injection time highlighting the opening and sliding of a new hydrofracture growing ~10 m away from the borehole, in accordance with the ambient normal stress regime and in alignment with the microseismicity. Our study reveals how fluid-driven fracture stimulation can be facilitated by a mixed-mode process controlled by the complex hydromechanical evolution of the growing fracture. The data presented in this submission refer to the SIMFIP measurements and analyses of the stimulation tests conducted on the 164 ft (50 m) notch of the Sanford Underground Research Facility (SURF), during the EGS-Collab test 1. In addition to the datafiles, there is the draft of a manuscript submitted to Geophysical Research Letters (GRL).
This dataset encompasses the development of a geothermal energy system for the West Woodlawn neighborhood in Chicago, Illinois. This project is part of a broader initiative to design and deploy geothermal heating and cooling systems at a community scale. The dataset includes thermal conductivity test results, calculations for borehole sizing based on the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) method, as well as simulated thermal loads based on actual energy usage from individual buildings. Also provided here are files used for numerical modeling via COMSOL Multiphysics to simulate borefield design and subsurface thermal behavior. Two manuscripts are attached, which outline the broad objectives of the project and a description of the numerical modeling methodology and results.
This dataset provides a set of experimental data on the performance of lost circulation materials (LCMs) used in geothermal drilling operations. It includes results from four distinct tests: thermal degradation, viscosity measurements, compression tests, and high-temperature flow loop experiments. The materials tested, such as cedar fiber, cotton seed hulls, magma fiber, microcellulose, and sawdust, were analyzed under a range of conditions to assess their effectiveness in mitigating fluid losses in geothermal wells. Data on thermal degradation explores mass loss, water loss, and gas release for each material when subjected to temperatures between 90C and 250C. Viscosity measurements capture the behavior of LCM mixtures under different temperatures, while compression tests investigate the structural integrity of both undegraded and thermally degraded materials. The high-temperature flow loop experiments simulate geothermal well conditions, analyzing how different materials and mixtures affect fluid flow and sealing performance in a fractured reservoir environment. In addition to the experimental data, the dataset includes photos documenting the materials, schematics of test setups, and several published manuscripts that provide detailed insights into the experimental methods and findings.
Abstract We conducted low-temperature photoluminescence (PL) spectroscopy experiments on individual WS 2 and MoSe 2 nanoribbons prepared by gold-assisted exfoliation from the slanted surface of bulk crystals with a vicinal and stepwise pattern. The nanoribbons are predominantly monolayer and have widths varying from hundreds of nanometers down to tens of nanometers. Most MoSe 2 NRs display an emission profile similar to 2D excitons of MoSe 2 monolayers. In contrast, WS 2 nanoribbons are characterized with sharp emission peaks that can be attributed to the emission from localized excitons or trions. Moreover a broad low energy emission peak can be also observed from some of the WS 2 nanoribbons, which originates from bilayer regions. In this manuscript, we analyze spectral diffusion behavior along with pump power and temperature dependence of the localized exciton emission peaks, shedding light on potential of TMDC nanoribbons in sensing and opto-electronic applications.
This dataset contains the underwater 360-degree video files recorded with a Boxfish 360 camera in La Jolla, CA, near a gravity base anchor of the CalWave xWave wave energy converter in December 2021 over three days, at dawn, noon, and dusk. It was generated to test the ability of using this type of camera mounted on an aluminum frame as a video lander to monitor the artificial reef effect of marine energy devices and associated seafloor structures. The Boxfish 360 is made of 3 cameras each recording its own set of videos. The videos are MOV files that can be viewed individually with any video reader but need to be stitched together to create the 360-degree footage. This dataset contains all the raw video files collected at dawn, noon and dusk on 11/30/2021, 12/01/2021 and 12/02/2021, for about 1h each time. This dataset is associated with the journal manuscript below (linked in resources): Hemery, L.G.; Mackereth, K.F.; Gunn, C.M.; Pablo, E.B. Use of a 360-Degree Underwater Camera to Characterize Artificial Reef and Fish Aggregating Effects around Marine Energy Devices. J. Mar. Sci. Eng. 2022, 10, 555. https://doi.org/10.3390/jmse10050555
This data package contains a series of datasets aimed at understanding the seasonal origins of water used by the dominant conifer species, Abies lasiocarpa and Picea engelmannii, in the East River Watershed. There is a distinct difference in the stable isotopic ratio of summer rain and snowpack and thus by tracking the isotopic ratio of the xylem water in trees, it is possible to separate when a tree is using snow vs. summer rain. Following typical protocols, we sampled and extracted water from soils in the "Research Meadow" near Gothic, CO within the East River Watershed through the 2016 growing season. The stable isotopic ratio of these waters were then measured. Using values of the isotopic ratio of precipitation and snowpack from that season, we develop a mixing model to show how the trees transitioned from use of snowpack to summer in late July. We extended the information on the seasonal origins of water from 2016 back until 1980 by using measurements of the isotopic ratio of cellulose from trees in the Research Meadow. The isotopic ratio of tree ring cellulose records a signal both of the Vapor Pressure Deficit at the leaf-atmosphere boundary and also the source water for the trees. We concluded from this extended analysis that the trees underwent transitions between periods where snow was the dominant water source and summer rain was the dominant water source. More details on this analysis can be found in the publication: Persistence and Plasticity in Conifer Water Use Strategies. JGR Biogeoscience. DOI 10.1029/2018JG004845. The dataset specifically includes stable isotope measurements of xylem and soil water for Spruce and Fir trees at the Rocky Mountain Biological Lab's Research Meadow as well as snowpack and precipitation stable isotopes from nearby National Atmospheric Deposition Program sites. Associated meteorological data is included, which is needed to understand the source water for the trees based on the cellulose measurements.This dataset was updated in June 2021 also include intra-ring measurements of the d18O and d13C of cellulose these same species of trees at the Ziegler Reservoir site in Snowmass, CO. These are listed as files: "Interglaciald18OCellulose.csv", "Interglaciald13OCellulose.csv" and "Modernd13CCellulose.csv". The intent of these measurements was to assess whether common conifers (abies and picea) had undergone ecophysiological or ecohydrological changes during the last period in Earth's history was warmer than today, i.e. the last Interglacial (116,000 to 130,000 years ago). This site was chosen because it is a location where subfossil wood from this critical warm period was discovered. We measured the d18O and d13C of the subfossil trees following the same protocol as the modern samples which included chemical extraction of cellulose and isotope ratio mass spectrometry. We found that the trees showed little difference in water use efficiency but utilized more summer rain during the interglacial period. This analysis and detailed methods are provided in the following manuscript: Wetter summers mitigated temperature stress on Rocky Mountain forests during the last interglacial warm period which is in revision at GRL but is available as a preprint here: 10.1002/essoar.10506740.2
This package includes geospatial data layers developed to investigate how environmental gradients—specifically topography and near-surface soil properties—drive the spatial arrangement of dominant plant communities in mountainous watersheds. The geospatial products, which support the analysis of these ecological relationships, are derived from airborne hyperspectral and LiDAR datasets acquired by the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP), in conjunction with an extensive ground field campaign conducted in summer 2018. This work is part of the DOE Watershed Function Science Focus Area (SFA) and features geospatial datasets developed based on observations and ground data collected at East River, Colorado, in collaboration with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey in June 2018. Classification Map: - Classification Map (PNG, GeoTIFF): Derived from hyperspectral and LiDAR airborne data using a machine learning approach. - Class Code Mapper (CSV): Associates pixel values with corresponding vegetation/non-vegetation classes. - Classification Reference Data (CSV): Reference data used in the machine learning procedure. LiDAR-Derived Products: - Topographical Metrics (GeoTIFFs): Elevation, slope, curvature, TWI, TPI, solar insolation, and canopy height model (CHM), smoothed with a 5x5 pixel window. Vegetation Indices: - GeoTIFFs of NDVI, NDNI, NDWI: Vegetation indices derived from hyperspectral data. Urban Masks: - Urban Mask (GeoTIFF): Applied to the mapping to convert bare soil classes to urban classes. Software Compatibility: GeoTIFFs: Can be visualized with GIS software or libraries that support GeoTIFF images. CSV Files: Can be opened with any software that handles comma-separated values. The FLMD file provides details and links to the source datasets used to derive the products. The manuscript (in the Method session) provides details on how each product was derived. 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 2026-03-25: Since the original dataset publication date of 02/28/2020, this package has a new classification map derived by an improved methodology. This update also includes additional ground data that improved the representation of some of the communities. See the methods for further details on what has changed between versions.
This data package contains root trait data collected from 170 plots of rapidly expanding shrub genera (Alnus, Betula, and Salix) and a widespread sedge (Eriophorum vaginatum) along a latitudinal and temperature gradient in northern Alaska. The trait data were collected in July 2017 and include root architecture (root diameter and branching patterns), mycorrhizal colonization (%), nitrogen concentration (%), delta 15N (per mil), and vertical root biomass. These raw data support a submitted manuscript that examines the distribution and interspecific variations of absorptive root traits of shrubs and graminoids across the graminoid-dominated nutrient-poor arctic tundra and reveals how deciduous shrub expansion affects plant nutrient acquisition strategies in tundra ecosystems. Data are presented by site (n=5) and patch (shrub or sedge plot) in separate csv files. The location data are provided in the “plot coordinates” file; all other files contain the data in the file title. Detailed methods are in Chen et al. (2020).2023/07/20 Update: The latest version of this dataset publication is version 2.0. The latest version of the data package was updated to include the alder nodule biomass dataset (alder nodule biomass.csv) and associated metadata (metadata_alder nodule biomass.csv). The name of the previous metadata file was updated (metadata_ root traits and biomass.csv ) to distinguish it from the new metadata file.
Surface water and pore water samples were collected at five sites along a shoreline transect of the Columbia River, southeastern WA, USA in 2017. This dataset is comprised of (1) high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) and (2) a metadata csv file. The FTICR-MS files are .xml, and the data package includes instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user’s specific needs. The data are associated with the publication “Using community assembly metrics from metacommunity ecology to understand environmental metabolomes” that will be published in Nature Communications (Danczak et al.). The study aimed to investigate gaps in understanding the spatiotemporal organization of environmental metabolomes to improve the ability to predict ecosystem function. Associated sequencing data will be published via NCBI. The access information for NCBI and the publication DOI will be added to this abstract when they are available. Please use the data package’s DOI to cite the data package. We ask that you acknowledge the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Subsurface Biogeochemical Research (SBR) program when using the data. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include data package authors as co-authors.
This data package contains data that were used to support conclusions drawn in “Growth strategies and threshold responses to water deficit modulate effects of warming on tree seedlings from forest to alpine”, by Lazarus, Castanha et al. 2017. Data were collected at field sites within the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA, and at the U.S. Geological Survey laboratory located in Boise, Idaho. This archive contains comma-separated-values (.csv) files, as well as the same files in Microsoft Excel (.xlsx) format, which can be opened by either Microsoft Excel, R, or any simple text editor program. There are two types of geospatial data files: .kml and ESRI shapefiles (.shp). The kml files contain placemarks, which can be opened by Google Earth, or Google Maps. The ESRI shapefiles can be opened by any geographic information system application that can read shapefiles, including ESRI's entire ArcGIS suite, and QGIS. We asked whether and how tree species differences in response to water deficit relates to their establishment along the gradient from forest to alpine. To do this, we compared growth and moisture stress responses in first-year seedlings of three species planted in common gardens subject to a factorial of heating and watering treatments below, at, and above tree line. This combination of an elevation gradient alongside warming and watering treatments enabled us to observe species differences in seedling responses to a broad set of climatic conditions.Entire seedlings were harvested at c. 3- and again at 9 weeks of age following germination/emergence in the experimental plots, and we then measured dry mass (DM) of above and belowground parts, root length, root mass fraction (RMF), relative growth rates (RGRs) from seed to 3 weeks and from 3 to 9 weeks, turgor-loss point (TLP), and photosynthetic WUE (as δ13C). Also included in this dataset (but not described in the manuscript) are measures of specific leaf area (SLA) and other variables generated by pressure-volume curves (saturated water content, osmotic potential at full turgor, elastic modulus).
Columbia River hyporheic zone sediments from the Hanford Site 300 Area in eastern Washington were incubated in a full factorial design with different organic matter (OM) amendments. The aim of the experiment was to test the influence of OM thermodynamics on aerobic respiration across different organic carbon pools and concentrations. This dataset is comprised of (1) a csv with high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory), (2) a csv with sample IDs, replicates, amendments, dissolved oxygen (DO) measurements, and sampling time points, (3) a csv with sample IDs, replicates, respiration rates, FTICR summary metrics, and relative abundance of chemical classes; and (4) a csv with the number of chemical transformations in each sample replicate (microcosm). The data are associated with the publication “Carbon Limitation Leads to Thermodynamic Regulation of Aerobic Metabolism” published in ES&T Letters (Garayburu-Caruso et al., 2020). Please use the data package’s DOI to cite the data package. We ask that you acknowledge the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Subsurface Biogeochemical Research (SBR) program when using the data. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include data package authors as co-authors.
This dataset contains data used for the paper "Soil carbon dynamics during drying vs. rewetting: importance of antecedent moisture conditions". The Related References field will be updated with a full citation when available.Soil moisture influences soil carbon dynamics, including microbial growth and respiration. The response of such ‘soil respiration’ to moisture changes is generally assumed to be linear and reversible, i.e. to depend only on the current moisture state. Current models thus do not account for antecedent soil moisture conditions when determining soil respiration or the available substrate pool. We conducted a laboratory incubation to determine how the antecedent conditions of drought and flood influenced soil organic matter (SOM) chemistry, bioavailability, and respiration. We sampled soils from an upland coastal forest, Beaver Creek, WA USA, and subjected them to drying and rewetting treatments. For the drying treatment, field moist soils were saturated and then dried to 75, 50, 35, and 5 % saturation. In the rewetting treatment, field moist soils were air-dried and then rewet to 35, 50, 75, and 100 % saturation. We measured respiration and water extractable organic carbon (WEOC) concentrations and used 1H-NMR and FT-ICR-MS to characterize the WEOC pool across the treatments. The drying vs. wetting treatment strongly influenced SOM bioavailability, as rewet soils (with antecedent drought) had greater WEOC concentrations and respiration fluxes compared to the drying soils (with antecedent flood). In addition, air-dry soils had the highest WEOC concentrations, and the NMR-resolved peaks showed a strong contribution of protein groups in these soils. Both NMR and FT-ICR-MS analyses indicated increased contribution of complex aromatic groups/molecules in the rewet soils, compared to the drying soils. We suggest that drying introduced organic matter into the WEOC pool via desorption of aromatic molecules and/or by microbial cell lysis, and this stimulated microbial mineralization rates. Our work indicates that even short-term shifts in antecedent moisture conditions can strongly influence soil C dynamics at the core scale. The predictive uncertainties in current soil models may be reduced by a more accurate representation of soil water and C persistence that includes a mechanistic and quantitative understanding of the impact of antecedent moisture conditions.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv and .txt format, which can be accessed and processed using MS Excel or R. NMR data are provided as raw output data (accessed in Bruker TopSpin or MestreNova) as well as the MestreNova-processed files. This archive can also be accessed on GitHub at https://github.com/kaizadp/hysteresis_and_soil_carbon (DOI: 10.5281/zenodo.4432885).
This dataset contains data used for the paper "Soil texture and environmental conditions influence the biogeochemical responses of soils to drought and flooding". The Related References field will be updated with a full citation when available.Climate change is intensifying the global water cycle, with increased frequency of drought and flood. Water is an important driver of soil carbon dynamics, and it is crucial to understand how moisture disturbances will affect carbon availability and fluxes in soils. Here we investigate the role of water in substrate-microbe connectivity and soil carbon cycling under extreme moisture conditions. We collected soils from Alaska, Florida, and Washington USA, and incubated them under Drought and Flood conditions. Drought had a stronger effect on soil respiration, pore-water carbon, and microbial community composition than flooding. Soil response was not consistent across sites, and was influenced by site-level pedological and environmental factors. Soil texture and porosity can influence microbial access to substrates through the pore network, driving the chemical response. Further, the microbial communities are adapted to the historic stress conditions at their sites and therefore show site-specific responses to drought and flood.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv and .txt format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/TES_3Soils_2021 (DOI: 10.5281/zenodo.4792655).
This dataset contains data used for the paper: Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter. Soil Biology and Biochemistry 156, 108185. doi:10.1016/j.soilbio.2021.108185On April 2018 (after 4.5 years of warming), we collected O-horizon (organic horizon) material and soil core down to 90 cm depth from a whole-soil warming experiment in a mixed-coniferous temperate forest, located at the University of California Blodgett experimental forest in the foothills of the Sierra Nevada, CA USA. The goal was to assess how 4.5 years of +4 °C whole-soil warming affected the quantity and quality of soil organic matter. Cores were collected from 6 experimental plots (three replicated blocks); samples were collected in 10 cm increments from 0 to 90 cm depth.This dataset contains a compressed (.zip) archive of the data used for this manuscript. The dataset includes files in .xlsx format, which can be accessed and processed using MS Excel or R. Carbon and nitrogen concentrations, as well as stable carbon isotope composition ((δ13C) and solvent extractable lipid biomarker (alkanoic acids and alkanes) data are provided as processed data files. Diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy data are provided as raw output and processed data files.The dataset files "Blodgett_warming_Data" and "Blodgett_warming_raw_data.xlsx" were updated on July 7, 2021. The following updates were made: (1) specification of the units of measurements in the dataset (the unit of measurement was missing in some parameters) and (2) the column name "pulled depth" was changed to "pooled depth" in the updated data files.
This data package is associated with the manuscript “Disturbance Triggers Non-Linear Microbe-Environment Feedbacks, in revision in Biogeosciences (Sengupta et al. and 2021;https://bg.copernicus.org/preprints/bg-2021-51/). The study used hyporheic zone sediments as a model system to provide an integrated view of how disturbance modulates linkages among microbial ecology, biogeochemistry, and organic matter thermodynamics. Laboratory experiments exposed hyporheic sediment to varying wetting/drying dynamics. Data types include dissolved oxygen rates used to derive respiration rates, Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data used to derive thermodynamic properties of organic matter, and microbial community assembly metrics derived from amplicon-sequence data of putatively active (cDNA) and whole community (gDNA). The outcomes of the study are condensed into a broadly applicable conceptual model linking external forcing, internal dynamics, and history. This data package is comprised of a file-level metadata (FLMD) csv, metadata csv, and seven folders that contain csv files, R scripts, xml files, and associated documentation: (1) Rates, (2) bNTI, and (3) FTICR, (4) Statistics_Analyses, (5) Raw OTU Beta dispersion Analysis, (6) bMNTD Randomizations, and (7) Data Dictionaries. The FLMD file has a description of each file included in the data package.