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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: Creel, Roger; Miesner, Frederieke; Austermann, Jacqueline; Wilkenskjeld, Stiig; +1 Authors

    Data files used to make the main and supplementary figures in Creel, R.C., Miesner, F., Wilkenskjeld, S., Austermann, J., Overduin, P., Glacial Isostatic Adjustment speeds past and future Arctic subsea permafrost thaw (2024). Please contact Roger Creel (roger.creel@whoi.edu) if any files are missing and he will update this repository to include them. 

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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/
    ZENODO
    Dataset . 2024
    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/
      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
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    Authors: Huber, Sandra J.; Schlidt, Vanessa; Seitz, H.-Michael; Kniest, Jorit F.; +3 Authors

    This is the Supporting Information S1 of the article: ‘Assessment of chalk as an archive for the lithium isotope composition of seawater’, published in the Journal Geochemistry, Geophysics, Geosystems in 2024.Text and Figure S1 provide information about the calibration of the column chemistry with a carbonate sample.Table S1-S3 provide further sample information and the measuring results (δ7Li, [Li] and E/Ca ratios) for all samples used in the study.

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2024
    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/
      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2024
      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: Aumont, Olivier; Rodgers, Keith;

    The repository contains the version of PISCES that was used to investigate the role played by low latitudes and the Southern Ocean at sustaining export production and PP in the low latitudes. This code is based on version 3.6 of NEMO and the repository only includes routines that have been changed with respect to this version. The code is in Fortran 90.

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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: Anadón, JD;

    Dataset for: Anadón JD, O Piñeiro, A Ruhi, J Hornstein, JR Waldman "Decoupled shifts of dominant and rarer fish species as a response to warming and extreme events in a large estuary" Ecosphere, in press. Uploaded 23/01/2024 Contains five numbered files: 0: Readme file 1: Raw dataset from the seine sampling in Jamaica Bay, as obtained from the annual seine survey of young striped bass (Morone saxatilis) by the New York State Department of Environmental Conservation (NYSDEC). 2. Standardized-by-sampling-effort dataset, and obtained from the raw dataset (1). See main text and supplementary materials for sampling effort and seines per month and year. 3. Species abundance x year matrix for analyses. This is the matrix used for NMDS (untransformed) and all posterior analyses, and obtained from the standardized dataset (2). 4. Environmental data in Jamaica Bay used in this work (i.e. annual values) as obtained from the NYC Water Quality Survey database, collected by the NYC Department of Environmental Protection. See main text for selection of sampling stations and averaging. 5. Species traits dataset used for analyses, with data obtained from www.Fishbase.org and authors´ knowledge (i.e. migrant/resident). All original data employed in this work (i.e. files 1, 4, 5) comes from publicly available datasets. See further information on the main text of the publication and its references.

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2024
      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: van der Loos, Luna; Steinhagen, Sophie; Stock, Willem; Weinberger, Florian; +3 Authors

    This folder contains the electronic supplementary materials for: "Chapter 5. Osmoregulation underpins functional stability of Ulva-associated bacterial communities in the Baltic Sea" which is part of the PhD thesis "Ulva-microbial interactions linked to the environment: variation and acclimation" by Luna van der Loos (submitted in 2024) Contents: Table S1: metadata of 91 samples Table S2: metadata of bacterial genomes used in the comparison between seawater and Ulva-derived bacteria Table S3: overview of the 639 Ulva-associated MAGs Table S4: overview of the KEGG modules identified in each MAG Supplementary Figures: additional figures

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: Teske, Vanessa; Timmermann, Ralph; Semmler, Tido;

    This dataset includes the minimal data necessary to reproduce the findings of Teske et al., in revision. Output of model simulations with the global climate model AWI-CM is provided for one ensemble of five historical simulations (hist1 - hist5) and four climate scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5), including the ensemble of five SSP3-7.0 scenario simulations, as well as information on the model grid. historical period hist1 monthly means for sea ice concentration, sea ice formation, sea ice thickness, surface stress, salinity and potential temperatureyearly means of salinity and potential temperature hist2 monthly means for sea ice concentration, sea ice formation, surface stress, salinity and potential temperatureyearly means for salinity and potential temperature hist3 monthly means for sea ice concentration, sea ice formation, surface stress, salinity and potential temperatureyearly means for salinity and potential temperature hist4 monthly means for sea ice concentration, sea ice formation, surface stress, salinity and potential temperatureyearly means for salinity and potential temperature hist5 monthly means for sea ice concentration, sea ice formation, surface stress, salinity and potential temperatureyearly means for salinity and potential temperature CO2 emission scenario SSP1-2.6 monthly means for sea ice concentration, sea ice formation, surface stress and potential temperatureyearly means for salinity and potential temperature SSP2-4.5 monthly means for sea ice concentration, sea ice formation and surface stressyearly means for salinity and potential temperature SSP3-7.0_1 monthly means for sea ice concentration, sea ice formation, surface stress and salinityyearly means for salinity and potential temperature SSP3-7.0_2 monthly means for sea ice concentration, sea ice formation, surface stress and salinityyearly means for salinity and potential temperature SSP3-7.0_3 monthly means for sea ice concentration, sea ice formation, surface stress and salinityyearly means for salinity and potential temperature SSP3-7.0_4 monthly means for sea ice concentration, sea ice formation, surface stress and salinityyearly means for salinity and potential temperature SSP3-7.0_5 monthly means for sea ice concentration, sea ice formation, surface stress and salinityyearly means for salinity and potential temperature SSP5-8.5 8-hourly means for 10m-wind monthly means for sea ice concentration, sea ice formation, sea ice thickness, surface stress, salinity and potential temperatureyearly means for salinity and potential temperature Depending on the scenario and variable in question, the variables are provided for the periods 1850-2014 or 2000-2014 for the historical simulations, and 2015-2100 for the scenario simulations. Monthly sea ice concentrations are provided for the time periods 2000-2014, 2036-2050 and 2086-2100.

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: Szymczycha, Beata; Saghravani, Seyed Reza; Böttcher, Michael Ernst; Hong, Wei-Li; +3 Authors

    A nutrient distribution such as phosphate (PO₄³⁻), ammonium (NH₄⁺), nitrate (NO₃⁻), dissolved silica (Si), total dissolved nitrogen (TN), dissolved organic nitrogen (DON) together with dissolved organic carbon (DOC) and inorganic carbon (DIC), was investigated during a high melting season in 2021 in the western Spitsbergen fjords (Hornsund, Isfjorden, Kongsfjorden, and Krossfjorden). Both the water column and the pore water were investigated for nutrients and dissolved carbon distribution and gradients. The water column concentrations of most measured parameters such as PO₄³⁻, NH₄⁺, NO₃⁻, Si, and DIC showed significant changes among fjords and water masses. In addition, pore water gradients of PO₄³⁻, NH₄⁺, NO₃⁻, Si, DIC and DOC revealed significant variability between fjords and are likely substantial sources of the investigated elements for the water column. The obtained dataset reflects differences in hydrography and biogeochemical ecosystem function of the western Spitsbergen fjords and may form the base for further modelling of physical oceanographic and biogeochemical processes within the investigated fjord systems.

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: Alglave, Baptiste;

    This data set are spatial predictions from a spatio-temporal model developped to integrate scientific survey data and commercial catch declaration data to infer fish distribution. Maps are available at a monthly time step between 2008 and 2018 for hake (Merluccius merluccius), sole (Solea solea) and sea bass (Dicentrarchus labrax) of the Bay of Biscay.

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2024
    License: CC BY
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      ZENODO
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      ZENODO
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    Authors: Krastel, Sebastian;
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    Authors: Ballantyne, John;

    We introduce BSMArt, a python program for the exploration of parameter spaces of theories Beyond the Standard Model. Especially designed for use with the SARAH family of tools, it is also sufficiently flexible to be used with a wide variety of external codes. BSMArt contains the first public release of the Active Learning scan by the same authors; but contains several additional scanning algorithms, ranging from the very simple to MultiNest and Diver. A BSMArt scan can be set up in a matter of minutes with only minimal editing of configuration files; installation scripts for all relevant tools and examples are provided.

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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: Creel, Roger; Miesner, Frederieke; Austermann, Jacqueline; Wilkenskjeld, Stiig; +1 Authors

    Data files used to make the main and supplementary figures in Creel, R.C., Miesner, F., Wilkenskjeld, S., Austermann, J., Overduin, P., Glacial Isostatic Adjustment speeds past and future Arctic subsea permafrost thaw (2024). Please contact Roger Creel (roger.creel@whoi.edu) if any files are missing and he will update this repository to include them. 

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    ZENODO
    Dataset . 2024
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      ZENODO
      Dataset . 2024
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    Authors: Huber, Sandra J.; Schlidt, Vanessa; Seitz, H.-Michael; Kniest, Jorit F.; +3 Authors

    This is the Supporting Information S1 of the article: ‘Assessment of chalk as an archive for the lithium isotope composition of seawater’, published in the Journal Geochemistry, Geophysics, Geosystems in 2024.Text and Figure S1 provide information about the calibration of the column chemistry with a carbonate sample.Table S1-S3 provide further sample information and the measuring results (δ7Li, [Li] and E/Ca ratios) for all samples used in the study.

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    ZENODO
    Dataset . 2024
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    ZENODO
    Dataset . 2024
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      ZENODO
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      ZENODO
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    Authors: Aumont, Olivier; Rodgers, Keith;

    The repository contains the version of PISCES that was used to investigate the role played by low latitudes and the Southern Ocean at sustaining export production and PP in the low latitudes. This code is based on version 3.6 of NEMO and the repository only includes routines that have been changed with respect to this version. The code is in Fortran 90.

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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: Anadón, JD;

    Dataset for: Anadón JD, O Piñeiro, A Ruhi, J Hornstein, JR Waldman "Decoupled shifts of dominant and rarer fish species as a response to warming and extreme events in a large estuary" Ecosphere, in press. Uploaded 23/01/2024 Contains five numbered files: 0: Readme file 1: Raw dataset from the seine sampling in Jamaica Bay, as obtained from the annual seine survey of young striped bass (Morone saxatilis) by the New York State Department of Environmental Conservation (NYSDEC). 2. Standardized-by-sampling-effort dataset, and obtained from the raw dataset (1). See main text and supplementary materials for sampling effort and seines per month and year. 3. Species abundance x year matrix for analyses. This is the matrix used for NMDS (untransformed) and all posterior analyses, and obtained from the standardized dataset (2). 4. Environmental data in Jamaica Bay used in this work (i.e. annual values) as obtained from the NYC Water Quality Survey database, collected by the NYC Department of Environmental Protection. See main text for selection of sampling stations and averaging. 5. Species traits dataset used for analyses, with data obtained from www.Fishbase.org and authors´ knowledge (i.e. migrant/resident). All original data employed in this work (i.e. files 1, 4, 5) comes from publicly available datasets. See further information on the main text of the publication and its references.

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    ZENODO
    Dataset . 2024
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    ZENODO
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      ZENODO
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    Authors: van der Loos, Luna; Steinhagen, Sophie; Stock, Willem; Weinberger, Florian; +3 Authors

    This folder contains the electronic supplementary materials for: "Chapter 5. Osmoregulation underpins functional stability of Ulva-associated bacterial communities in the Baltic Sea" which is part of the PhD thesis "Ulva-microbial interactions linked to the environment: variation and acclimation" by Luna van der Loos (submitted in 2024) Contents: Table S1: metadata of 91 samples Table S2: metadata of bacterial genomes used in the comparison between seawater and Ulva-derived bacteria Table S3: overview of the 639 Ulva-associated MAGs Table S4: overview of the KEGG modules identified in each MAG Supplementary Figures: additional figures

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    ZENODO
    Dataset . 2024
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    ZENODO
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