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  • Rural Digital Europe
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Worthington, Thomas A.; Spalding, Mark; Landis, Emily; Maxwell, Tania L.; +3 Authors

    Tidal marsh ecosystems are heavily impacted by human activities, highlighting a pressing need to address gaps in our knowledge of their distribution. To better understand the global distribution and changes in tidal marsh extent, and identify opportunities for their conservation and restoration, it is critical to develop a spatial knowledge base of their global occurrence. Here, we develop a globally consistent tidal marsh distribution map for the year 2020 at 10-m resolution. To map the location of the world’s tidal marshes we applied a random forest classification model to earth observation data from the year 2020. We trained the classification model with a reference dataset developed to support distribution mapping of coastal ecosystems, and predicted the spatial distribution of tidal marshes between 60°N to 60°S. We validated the tidal marsh map using standard accuracy assessment methods, with our final map having an overall accuracy score of 0.852. We estimate the global extent of tidal marshes in 2020 to be 52,880 km2 (95% CI: 32,030 to 59,780 km2) distributed across 120 countries and territories. Tidal marsh distribution is centred in temperate and Arctic regions, with nearly half of the global extent of tidal marshes occurring in the temperate Northern Atlantic (45%) region. At the national scale, over a third of the global extent (18,510 km2; CI: 11,200 – 20,900) occurs within the USA. Our analysis provides the most detailed spatial data on global tidal marsh distribution to date and shows that tidal marshes occur in more countries and across a greater proportion of the world’s coastline than previous mapping studies. Our map fills a major knowledge gap regarding the distribution of the world’s coastal ecosystems and provides the baseline needed for measuring changes in tidal marsh extent and estimating their value in terms of ecosystem services. This dataset accompanies the preprint https://doi.org/10.1101/2023.05.26.542433 The dataset consists 154 ,10 degree raster tiles. To identify the raster tile(s) you require refer to TidalMarsh_Exports.shp shapefile.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

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    figshare
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    figshare
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      figshare
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      figshare
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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  • Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Haefele, Rahimi) ending 2016-09-12

    https://doi.org/10.2...arrow_drop_down
    https://doi.org/10.25909/22911...
    Dataset . 2023
    License: CC BY NC
    Data sources: Datacite
    https://doi.org/10.25909/22911...
    Dataset . 2023
    License: CC BY NC
    Data sources: Datacite
    https://doi.org/10.25909/22911...
    Dataset . 2023
    License: CC BY NC
    Data sources: Datacite
    https://doi.org/10.25909/22911...
    Dataset . 2023
    License: CC BY NC
    Data sources: Datacite
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  • Location for the backend data storage associated with a database VM as established in relation to the prawn ITRH work.

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  • This repository is a hub for various wildlife projects led by Kyall Zenger from 2015 till present. Data is associated with the following projects: Genomic comparisons reveal biogeographic and anthropogenic impacts in the koala (Phascolarctos cinereus): a dietary-specialist species distributed across heterogeneous environments. Genome-wide SNP loci reveal novel insights into koala (Phascolarctos cinereus) population variability across its range. Domestication in Aquaculture Fishes- Elucidating the Genetic Consequences in Nile Tilapia The behavioural and molecular ecologies of the southern blue-ringed octopus, Hapalochlaena maculosa (Cephalopoda: octopodidae). Genetic structure, population connectivity and taxonomic identity of the black-lip pearl oyster Pinctada margaritifera (Bivalvia: Pteriidae), across its Indo-Pacific distribution. Genomic epidemiology of community-associated Staphylococcus aureus in northern Australia and Papua New Guinea. These projects are associated with multiple funders and grants.

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  • Authors: Eldering, Annmarie;

    This data set consists of a set of monthly NetCDF files containing the GOSAT quality filtered and bias corrected XCO2 values derived from the version 9 (v9) Atmospheric Carbon Observations from Space (ACOS) Level 2 full physics (L2FP) retrieval algorithm. Only the most essential variables for each satellite observation are preserved in these "superlite" files: latitude and longitude (both at the surface viewing location), the unique sounding identification number (format is: 4 digit year, 2 digit month, 2 digit day, 2 digit hour, 2 digit minute, 2 digit second), and the estimated dry-air mole fraction of total column carbon dioxide in parts per million. The monthly files also contain the set of operational L2FP "lite" files from which the data was extracted, and which can be downloaded from the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) (10.5067/VWSABTO7ZII4). This superlite "teaser" product is a companion to the recently published journal article "An eleven year record of XCO2 estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm" in Earth System Science Data by T.E. Taylor, et al. (https://doi.org/10.5194/essd-2021-247) It is meant to provide entry level users with a light weight satellite product for initial exploration. Interested users of the superlite product are encouraged to reach out to Tommy Taylor (tommy.taylor@colostate.edu) and/or Dr. Chris O'Dell (christopher.odell@colostate.edu) with questions on best uses practices for the GOSAT v9 XCO2 data. Related Publication: An eleven year record of XCO2 estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm Thomas E. Taylor et al Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA Earth System Science Data https://doi.org/10.5194/essd-2021-247 eng Contact person: Thomas E. Taylor Tommy.Taylor@colostate.edu

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Liao, Hua;

    Replication Data for "The demand for coal among China’s rural households: Estimates of price and income elasticities" THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DANS-EASYarrow_drop_down
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    DANS-EASY
    Dataset . 2021
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Mendeley Data; NARCIS
    Dataset . 2021
    License: CC BY NC
    Data sources: Datacite; NARCIS
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Mendeley Data
    Dataset . 2021
    License: CC BY NC
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Mendeley Data
    Dataset . 2021
    License: CC BY NC
    Data sources: Mendeley Data
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Mendeley Data
    Dataset . 2021
    License: CC BY NC
    Data sources: Mendeley Data
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      DANS-EASY
      Dataset . 2021
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Mendeley Data; NARCIS
      Dataset . 2021
      License: CC BY NC
      Data sources: Datacite; NARCIS
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Mendeley Data
      Dataset . 2021
      License: CC BY NC
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Mendeley Data
      Dataset . 2021
      License: CC BY NC
      Data sources: Mendeley Data
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Mendeley Data
      Dataset . 2021
      License: CC BY NC
      Data sources: Mendeley Data
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Salter, William T.; Shrestha, Arjina; Barbour, Margaret M.;

    Additional file 5. Windows batch file to run the “Autocleanscript.mlx” meshlab script on multiple models sequentially. Please ensure you change the filepaths in the code to the folder containing raw dense point clouds.ply files from VisualSFM, the output file path and the file location of the “Autocleanscript.mlx” file.

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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      figshare
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Salter, William T.; Shrestha, Arjina; Barbour, Margaret M.;

    Additional file 1. Arduino program for 3D scanner. Please refer to comments embedded in code to customise capture sequence. Upload to Arduino board using the Arduino IDE software available from https://www.arduino.cc/ .

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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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  • Authors: Arias-Ortiz, Ariane; Masque��, Pere; Paytan, Adina; Baldocchi, Dennis D.;

    Soil cores were collected at wetlands that had been restored for a minimum of 10 years with managed hydrology in Twitchell and Sherman Islands in the western portion of the Sacramento-San Joaquin Delta, California. The goal of the study was to measure soil carbon accumulation rates since restoration for comparison with multiyear net atmospheric carbon exchange measured by eddy covariance towers. Soil cores were sliced at 1 to 3 cm-thick intervals and analyzed for bulk density, organic matter, organic and inorganic carbon, total nitrogen and their stable isotopes, and 210Pb specific activities. Emergent vegetation was present at the sites. Dominant species at the core locations included Schoenoplectus acutus, Typha sp, and Phragmites sp. This dataset accompanies the paper Arias-Ortiz et al. under consideration in JGR: Biogeosciences.

    https://doi.org/10.2...arrow_drop_down
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Worthington, Thomas A.; Spalding, Mark; Landis, Emily; Maxwell, Tania L.; +3 Authors

    Tidal marsh ecosystems are heavily impacted by human activities, highlighting a pressing need to address gaps in our knowledge of their distribution. To better understand the global distribution and changes in tidal marsh extent, and identify opportunities for their conservation and restoration, it is critical to develop a spatial knowledge base of their global occurrence. Here, we develop a globally consistent tidal marsh distribution map for the year 2020 at 10-m resolution. To map the location of the world’s tidal marshes we applied a random forest classification model to earth observation data from the year 2020. We trained the classification model with a reference dataset developed to support distribution mapping of coastal ecosystems, and predicted the spatial distribution of tidal marshes between 60°N to 60°S. We validated the tidal marsh map using standard accuracy assessment methods, with our final map having an overall accuracy score of 0.852. We estimate the global extent of tidal marshes in 2020 to be 52,880 km2 (95% CI: 32,030 to 59,780 km2) distributed across 120 countries and territories. Tidal marsh distribution is centred in temperate and Arctic regions, with nearly half of the global extent of tidal marshes occurring in the temperate Northern Atlantic (45%) region. At the national scale, over a third of the global extent (18,510 km2; CI: 11,200 – 20,900) occurs within the USA. Our analysis provides the most detailed spatial data on global tidal marsh distribution to date and shows that tidal marshes occur in more countries and across a greater proportion of the world’s coastline than previous mapping studies. Our map fills a major knowledge gap regarding the distribution of the world’s coastal ecosystems and provides the baseline needed for measuring changes in tidal marsh extent and estimating their value in terms of ecosystem services. This dataset accompanies the preprint https://doi.org/10.1101/2023.05.26.542433 The dataset consists 154 ,10 degree raster tiles. To identify the raster tile(s) you require refer to TidalMarsh_Exports.shp shapefile.

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    ZENODO
    Dataset . 2023
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    ZENODO
    Dataset . 2023
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  • Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Haefele, Rahimi) ending 2016-09-12

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    https://doi.org/10.25909/22911...
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    https://doi.org/10.25909/22911...
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    https://doi.org/10.25909/22911...
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  • Location for the backend data storage associated with a database VM as established in relation to the prawn ITRH work.

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  • This repository is a hub for various wildlife projects led by Kyall Zenger from 2015 till present. Data is associated with the following projects: Genomic comparisons reveal biogeographic and anthropogenic impacts in the koala (Phascolarctos cinereus): a dietary-specialist species distributed across heterogeneous environments. Genome-wide SNP loci reveal novel insights into koala (Phascolarctos cinereus) population variability across its range. Domestication in Aquaculture Fishes- Elucidating the Genetic Consequences in Nile Tilapia The behavioural and molecular ecologies of the southern blue-ringed octopus, Hapalochlaena maculosa (Cephalopoda: octopodidae). Genetic structure, population connectivity and taxonomic identity of the black-lip pearl oyster Pinctada margaritifera (Bivalvia: Pteriidae), across its Indo-Pacific distribution. Genomic epidemiology of community-associated Staphylococcus aureus in northern Australia and Papua New Guinea. These projects are associated with multiple funders and grants.

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  • Authors: Eldering, Annmarie;

    This data set consists of a set of monthly NetCDF files containing the GOSAT quality filtered and bias corrected XCO2 values derived from the version 9 (v9) Atmospheric Carbon Observations from Space (ACOS) Level 2 full physics (L2FP) retrieval algorithm. Only the most essential variables for each satellite observation are preserved in these "superlite" files: latitude and longitude (both at the surface viewing location), the unique sounding identification number (format is: 4 digit year, 2 digit month, 2 digit day, 2 digit hour, 2 digit minute, 2 digit second), and the estimated dry-air mole fraction of total column carbon dioxide in parts per million. The monthly files also contain the set of operational L2FP "lite" files from which the data was extracted, and which can be downloaded from the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) (10.5067/VWSABTO7ZII4). This superlite "teaser" product is a companion to the recently published journal article "An eleven year record of XCO2 estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm" in Earth System Science Data by T.E. Taylor, et al. (https://doi.org/10.5194/essd-2021-247) It is meant to provide entry level users with a light weight satellite product for initial exploration. Interested users of the superlite product are encouraged to reach out to Tommy Taylor (tommy.taylor@colostate.edu) and/or Dr. Chris O'Dell (christopher.odell@colostate.edu) with questions on best uses practices for the GOSAT v9 XCO2 data. Related Publication: An eleven year record of XCO2 estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm Thomas E. Taylor et al Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA Earth System Science Data https://doi.org/10.5194/essd-2021-247 eng Contact person: Thomas E. Taylor Tommy.Taylor@colostate.edu

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Liao, Hua;

    Replication Data for "The demand for coal among China’s rural households: Estimates of price and income elasticities" THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

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    Mendeley Data; NARCIS
    Dataset . 2021
    License: CC BY NC
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    Dataset . 2021
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    Dataset . 2021
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    Dataset . 2021
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    Authors: Salter, William T.; Shrestha, Arjina; Barbour, Margaret M.;

    Additional file 5. Windows batch file to run the “Autocleanscript.mlx” meshlab script on multiple models sequentially. Please ensure you change the filepaths in the code to the folder containing raw dense point clouds.ply files from VisualSFM, the output file path and the file location of the “Autocleanscript.mlx” file.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Salter, William T.; Shrestha, Arjina; Barbour, Margaret M.;

    Additional file 1. Arduino program for 3D scanner. Please refer to comments embedded in code to customise capture sequence. Upload to Arduino board using the Arduino IDE software available from https://www.arduino.cc/ .

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  • Authors: Arias-Ortiz, Ariane; Masque��, Pere; Paytan, Adina; Baldocchi, Dennis D.;

    Soil cores were collected at wetlands that had been restored for a minimum of 10 years with managed hydrology in Twitchell and Sherman Islands in the western portion of the Sacramento-San Joaquin Delta, California. The goal of the study was to measure soil carbon accumulation rates since restoration for comparison with multiyear net atmospheric carbon exchange measured by eddy covariance towers. Soil cores were sliced at 1 to 3 cm-thick intervals and analyzed for bulk density, organic matter, organic and inorganic carbon, total nitrogen and their stable isotopes, and 210Pb specific activities. Emergent vegetation was present at the sites. Dominant species at the core locations included Schoenoplectus acutus, Typha sp, and Phragmites sp. This dataset accompanies the paper Arias-Ortiz et al. under consideration in JGR: Biogeosciences.

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    Dataset . 2021
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    https://doi.org/10.25573/serc....
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      Dataset . 2021
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      https://doi.org/10.25573/serc....
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