Filter Results
72183 results
  • RT XFEL structure of CypA solved using MESH injection system
    Data Types:
    • Dataset
  • In July-August 2018, we collected 88 filtered pore water samples at 20 cm depth and analyzed them for anions, cations, dissolved organic carbon, dissolved organic matter (DOM) quality, and standard water quality parameters. Vertical hydraulic head gradients were measured to assess the potential for upward or downward water flow and sediment grab samples were taken for grain size analyses to constrain the relationship between streambed morphology and water flow. Lastly, DNA was extracted from pore water filters for a 16S rRNA gene sequencing analysis. This allowed for a high-resolution characterization of streambed hydrology and biogeochemistry during base flow. Data.csv includes coordinates, time of sampling, grain size analysis D10 values, vertical hydraulic head gradients, microbiological diversity metrics, and multiple chemical analyses. ReadMe.txt contains all information regarding sampling procedure, analysis instrumentation, and reporting limits. Microbiological sequences analyzed here have been deposited in the NCBI Sequence Read Archive and may be accessed using accession number PRJNA527829.
    Data Types:
    • Dataset
  • This data package contains data used in the publication, "Volatile monoterpene ‘fingerprints’ of resinous Protium tree species in the Amazon rainforest. Phytochemistry. 2019 Apr 1;160:61-70." Data was collected from species within the NGEE Tropics site in Manaus, Brazil. Included are volatile monoterpene compositions of tree trunk resins from 15 tree species among 77 individuals belonging to the genus Protium. We hypothesized that by normalizing the abundances of 28 monoterpenes in each individual, a unique Protium monoterpene ‘fingerprint’ pattern exists for each of the 15 species.
    Data Types:
    • Dataset
  • To understand how redox processes influence carbon, nitrogen, and iron cycling within the intrameander hyporheic zone, we developed a biotic and abiotic reaction network and incorporated it into the reactive transport simulator PFLOTRAN. Two dimensional reactive flow and transport simulations were performed (1) to evaluate how transient hydrological conditions control the lateral redox zonation within an intrameander region of the East River in Colorado and (2) to quantify the impact of a single meander on subsurface exports of carbon and other geochemical species to the river. This data package includes simulated hydrologic and geochemical data from 23 Oct 2015 to 22 Oct 2016.
    Data Types:
    • Dataset
  • Raw soil water content data from K34 tower site on a plateau near Manaus, Brazil. Attached files include data, related metadata excel files, and sensor manual PDFs. All sensors on a single Campbell CR3000 data logger were installed near ground on the K34 tower. Additional file level metadata is contained in the referenced dataset.
    Data Types:
    • Dataset
  • QA/QC-ed meteorological drivers of the PNM site
    Data Types:
    • Dataset
  • Discharge data collected at the East River in the Upper Colorado River Basin for the Lawrence Berkeley National Laboratory's Watershed Function Scientific Focus Area. Files contain instantaneous observed discharge data, corrected 10 min and mean daily discharge. Several sites also contain temperature and transducer depth. Please contact Rosemary Carroll if you have any questions or wish to access the raw data.
    Data Types:
    • Dataset
  • Although bedrock weathering strongly influences water quality and global carbon and nitrogen budgets, the weathering depths and rates within subsurface are not well understood nor predictable. Determination of both porewater chemistry and subsurface water flow are needed in order to develop more complete understanding and obtain weathering rates. In a long-term field study, we applied a multiphase approach along a mountainous watershed hillslope transect underlain by marine shale. Here we report three findings. First, the deepest extent of the water table determines the weathering front, and the range of annually water table oscillations determines the thickness of the weathering zone. Below the lowest water table, permanently water-saturated bedrock remains reducing, preventing deeper pyrite oxidation. Secondly, carbonate minerals and potentially rock organic matter share the same weathering front depth with pyrite, contrary to models where weathering fronts are stratified. Thirdly, the measurements-based weathering rates from subsurface shale are high, amounting to base cation exports of about 70 kmolc ha−1 y−1, yet consistent with weathering of marine shale. Finally, by integrating geochemical and hydrological data we present a new conceptual model that can be applied in other settings to predict weathering and water quality responses to climate change.
    Data Types:
    • Dataset
  • This dataset contains leaf and ecosystem monoterpene emissions and normalized ratios as a function of leaf and canopy temperature during the 2015/6 El Nino in the central Amazon. Also included are 13C-labeled monoterpene data during leaf photosynthesis under 13CO2. Data was used in the publication, "Monoterpene ‘thermometer’of tropical forest-atmosphere response to climate warming." See the below Dataset Reference field for the complete publication citation.
    Data Types:
    • Dataset
  • The Camp Fire rapidly spread across a landscape in Butte County, California, toward the city of Paradise in the early morning hours of 8 November 2018. GEE acquires L8 data products from USGS that include Real-Time Tier 1 DN values, representing scaled, calibrated at-sensor radiance, and Level-1 Precision Terrain (L1TP) processing. We carried out additional processing on the pre- and post-fire images, including an illumination correction to account for effects of steep topography, and radiometric normalization to ensure homogeneity between images. We also identified and processed high-quality images for both the pre-fire condition(25 Oct 2013), and the post-fire burn scar (26 Dec 2018). Using the tools we provided in the paper, we estimate that, over the first hour, the Camp Fire was consuming ~200 ha/minute of vegetation with a linear spread rate of 14 km over the fire’s first 25 minutes, or ~33km/hr. We briefly discuss broader use of remote sensing and geospatial analysis for fire research and risk management. A visualization app (sliderApp) that includes pre-fire, active fire, and post-fire images: https://caralyngorman.users.earthengine.app/view/camp-fire-sliding-map-3-9-19
    Data Types:
    • Dataset
4