skip to main content
DOE Data Explorer title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Columbia River Surface Water and Pore Water Unaligned FTICR-MS Data Associated with “Using Community Assembly Metrics from Metacommunity Ecology to Understand Environmental Metabolomes”

Abstract

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)more » 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.« less

Authors:
ORCiD logo ; ORCiD logo ; ORCiD logo ; ORCiD logo ; ORCiD logo ; ORCiD logo ; ORCiD logo ; ORCiD logo
  1. Pacific Northwest National Laboratory
  2. University of Arizona/Pacific Northwest National Laboratory
Publication Date:
DOE Contract Number:  
DOE Award #54737
Product Type:
Dataset
Research Org.:
Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States); River Corridor and Watershed Biogeochemistry SFA
Sponsoring Org.:
U.S. DOE > Office of Science > Biological and Environmental Research (BER)
Subject:
54 ENVIRONMENTAL SCIENCES
Keywords:
FTICR-MS; River corridor; Pore water; Hyporheic zone; River; Stream; Organic matter; FTICR-MS; Metabolite; Metabolomics; Mass spectrometry; Null modeling; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER
OSTI Identifier:
1675028
DOI:
10.15485/1675028

Citation Formats

Danczak, Robert E, Chu, Rosalie K, Fansler, Sarah J, Goldman, Amy E, Graham, Emily B, Tfaily, Malak, Toyoda, Jason G, and Stegen, James C. Columbia River Surface Water and Pore Water Unaligned FTICR-MS Data Associated with “Using Community Assembly Metrics from Metacommunity Ecology to Understand Environmental Metabolomes”. United States: N. p., 2020. Web. doi:10.15485/1675028.
Danczak, Robert E, Chu, Rosalie K, Fansler, Sarah J, Goldman, Amy E, Graham, Emily B, Tfaily, Malak, Toyoda, Jason G, & Stegen, James C. Columbia River Surface Water and Pore Water Unaligned FTICR-MS Data Associated with “Using Community Assembly Metrics from Metacommunity Ecology to Understand Environmental Metabolomes”. United States. doi:10.15485/1675028.
Danczak, Robert E, Chu, Rosalie K, Fansler, Sarah J, Goldman, Amy E, Graham, Emily B, Tfaily, Malak, Toyoda, Jason G, and Stegen, James C. 2020. "Columbia River Surface Water and Pore Water Unaligned FTICR-MS Data Associated with “Using Community Assembly Metrics from Metacommunity Ecology to Understand Environmental Metabolomes”". United States. doi:10.15485/1675028. https://www.osti.gov/servlets/purl/1675028. Pub date:Wed Jan 01 00:00:00 EST 2020
@article{osti_1675028,
title = {Columbia River Surface Water and Pore Water Unaligned FTICR-MS Data Associated with “Using Community Assembly Metrics from Metacommunity Ecology to Understand Environmental Metabolomes”},
author = {Danczak, Robert E and Chu, Rosalie K and Fansler, Sarah J and Goldman, Amy E and Graham, Emily B and Tfaily, Malak and Toyoda, Jason G and Stegen, James C},
abstractNote = {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.},
doi = {10.15485/1675028},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {1}
}

Dataset:

Save / Share: