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  • Energy Research
  • 11. Sustainability
  • 14. Life underwater

  • Authors: orcid Oates, Lucy;
    Oates, Lucy
    ORCID
    Harvested from ORCID Public Data File

    Oates, Lucy in OpenAIRE
    Edwards, Alison; Bueren, Ellen van; Ersoy, Aksel;

    This file includes the metadata of 107 articles that were included in a systematic literature review and subsequent corpus-based discourse analysis.

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    Authors: orcid bw Grill, Günther;
    Grill, Günther
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Grill, Günther in OpenAIRE
    Thieme, Michele;

    This repository contains spatial data and metadata for the research article: Thieme M.L. et al. (2021). Navigating trade-offs between dams and river conservation. Global Sustainability 4, e17, 1–7. https://doi.org/10.1017/sus.2021.15

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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
    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/
    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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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/
      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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      Smithsonian figshare
      Dataset . 2021
      License: CC BY
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    Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.HighResMIP.CNRM-CERFACS.CNRM-CM6-1-HR' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CNRM-CM6-1-HR climate model, released in 2017, includes the following components: aerosol: prescribed monthly fields computed by TACTIC_v2 scheme, atmos: Arpege 6.3 (T359; Gaussian Reduced with 181724 grid points in total distributed over 360 latitude circles (with 720 grid points per latitude circle between 32.2degN and 32.2degS reducing to 18 grid points per latitude circle at 89.6degN and 89.6degS); 91 levels; top level 78.4 km), atmosChem: OZL_v2, land: Surfex 8.0c, ocean: Nemo 3.6 (eORCA025, tripolar primarily 1/4deg; 1442 x 1050 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: Gelato 6.1. The model was run by the CNRM (Centre National de Recherches Meteorologiques, Toulouse 31057, France), CERFACS (Centre Europeen de Recherche et de Formation Avancee en Calcul Scientifique, Toulouse 31057, France) (CNRM-CERFACS) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.

    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/ World Data Center fo...arrow_drop_down
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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      World Data Center for Climate
      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/
      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Torre, I (via Mendeley Data);

    Database of Crocidura russula abundance obtained by the SEMICE small mammal monitoring program by using standardised sampling stations between 2008-2017.

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    B2FIND
    Dataset . 2020
    Data sources: B2FIND
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Mendeley Data
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Mendeley Data
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      B2FIND
      Dataset . 2020
      Data sources: B2FIND
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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    Authors: Piper, Adam T.; Manes, Costantino; Siniscalchi, Fabio; Marion, Andrea; +2 Authors

    Anthropogenic structures (e.g. weirs and dams) fragment river networks and restrict the movement of migratory fish. Poor understanding of behavioural response to hydrodynamic cues at structures currently limits the development of effective barrier mitigation measures. This study aimed to assess the effect of flow constriction and associated flow patterns on eel behaviour during downstream migration. In a field experiment, we tracked the movements of 40 tagged adult European eels (Anguilla anguilla) through the forebay of a redundant hydropower intake under two manipulated hydrodynamic treatments. Interrogation of fish trajectories in relation to measured and modelled water velocities provided new insights into behaviour, fundamental for developing passage technologies for this endangered species. Eels rarely followed direct routes through the site. Initially, fish aligned with streamlines near the channel banks and approached the intake semi-passively. A switch to more energetically costly avoidance behaviours occurred on encountering constricted flow, prior to physical contact with structures. Under high water velocity gradients, fish then tended to escape rapidly back upstream, whereas exploratory ‘search’ behaviour was common when acceleration was low. This study highlights the importance of hydrodynamics in informing eel behaviour. This offers potential to develop behavioural guidance, improve fish passage solutions and enhance traditional physical screening. Fish_detections_UL_CHFish positions derived from acoustic telemetry contained within excel file with 5 columns. 'Record' denotes tag detection numbered consecutively in sequence; 'tag_number' denotes the fish identification number; ‘PosX’ denotes fish x coordinate in UTM; ‘PosY’ denotes fish y coordinate in UTM, ‘Treatment’ denotes experimental treatment

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    ZENODO
    Dataset . 2015
    License: CC 0
    Data sources: ZENODO
    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/
    B2FIND
    Dataset . 2015
    Data sources: B2FIND
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    EASY
    Dataset . 2015
    Data sources: EASY
    DRYAD
    Dataset . 2015
    License: CC 0
    Data sources: Datacite
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    BIP!Powered by BIP!
    visibility25
    visibilityviews25
    downloaddownloads3
    Powered by Usage counts
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      ZENODO
      Dataset . 2015
      License: CC 0
      Data sources: ZENODO
      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/
      B2FIND
      Dataset . 2015
      Data sources: B2FIND
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      EASY
      Dataset . 2015
      Data sources: EASY
      DRYAD
      Dataset . 2015
      License: CC 0
      Data sources: Datacite
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    Authors: Lukas, Roger; orcid bw Karl, David Michael;
    Karl, David Michael
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Karl, David Michael in OpenAIRE

    Nets are towed obliquely at approx. 1 knot, from the surface to approx. 175 m. Towing time is approx. 20 minutes. Zooplankton (weak swimmers >200µm) are collected using oblique tows of a 1 m**2 net (3m length) with 202µm mesh Nitex netting.

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    B2FIND
    Dataset . 1999
    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/
    PANGAEA
    Dataset . 1999
    Data sources: PANGAEA
    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/
    PANGAEA
    Dataset . 1999
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 1999
      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/
      PANGAEA
      Dataset . 1999
      Data sources: PANGAEA
      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/
      PANGAEA
      Dataset . 1999
      License: CC BY
      Data sources: PANGAEA
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    Authors: YU, Yongqiang;

    Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CAS.FGOALS-f3-L' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The FGOALS-f3-L climate model, released in 2017, includes the following components: atmos: FAMIL2.2 (Cubed-sphere, c96; 360 x 180 longitude/latitude; 32 levels; top level 2.16 hPa), land: CLM4.0, ocean: LICOM3.0 (LICOM3.0, tripolar primarily 1deg; 360 x 218 longitude/latitude; 30 levels; top grid cell 0-10 m), seaIce: CICE4.0. The model was run by the Chinese Academy of Sciences, Beijing 100029, China (CAS) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.

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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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  • Authors: orcid bw Grebmeier, Jacqueline M.;
    Grebmeier, Jacqueline M.
    ORCID
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    Grebmeier, Jacqueline M. in OpenAIRE
    orcid Cooper, Lee W.;
    Cooper, Lee W.
    ORCID
    Harvested from ORCID Public Data File

    Cooper, Lee W. in OpenAIRE

    The Pacific sector of the Arctic Ocean is experiencing major reductions in seasonal sea ice extent and increases in sea surface temperatures. One of the key uncertainties in this region is how the marine ecosystem will respond to seasonal shifts in the timing of spring sea ice retreat and/or delays in fall sea ice formation. Variations in upper ocean water hydrography, planktonic production, pelagic-benthic coupling and sediment carbon cycling are all influenced by sea ice and temperature change. To more systematically track the broad biological response to sea ice retreat and associated environmental change, an international consortium of scientists have developed a coordinated “Distributed Biological Observatory” (DBO) that includes selected biological measurements at multiple trophic levels, along with satellite and mooring measurements. The DBO currently focuses on five regional biological “hotspot” locations along a latitudinal gradient that allows for consistent sampling and monitoring at five biologically productive locations across a latitudinal gradient: DBO 1 (SLIP)-south of St. Lawrence Island (SLI), DBO2 (Chirikov)-north of SLI, DBO3 (southern Chukchi Sea), DBO4-NE Chukchi Sea,and DBO5-Barrow Canyon. This dataset contains benthic macroinfaunal population level from sediment samples collected at each station for the United States Coast Guard Cutter (USCGC) Healy cruise-Leg 1 in 2017, identified by station number (#), Station name (Stn. Name), Date (mm/dd/yy), latitude (°N), longitude (°W), and station depth (m). The following macroinfaunal parameters were determined: abundance, wet weight biomass (grams of wet weight per meters squared), dry weight biomass (grams of Carbon per meters squared), and taxon type.

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    Authors: orcid bw Swart, Neil Cameron;
    Swart, Neil Cameron
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    Swart, Neil Cameron in OpenAIRE
    orcid bw Cole, Jason N.S.;
    Cole, Jason N.S.
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    Cole, Jason N.S. in OpenAIRE
    orcid bw Kharin, Viatcheslav V.;
    Kharin, Viatcheslav V.
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    Kharin, Viatcheslav V. in OpenAIRE
    Lazare, Mike; +17 Authors

    Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CCCma.CanESM5-CanOE.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CanESM5-CanOE climate model, released in 2019, includes the following components: aerosol: interactive, atmos: CanAM5 (T63L49 native atmosphere, T63 Linear Gaussian Grid; 128 x 64 longitude/latitude; 49 levels; top level 1 hPa), atmosChem: specified oxidants for aerosols, land: CLASS3.6/CTEM1.2, landIce: specified ice sheets, ocean: NEMO3.4.1 (ORCA1 tripolar grid, 1 deg with refinement to 1/3 deg within 20 degrees of the equator; 361 x 290 longitude/latitude; 45 vertical levels; top grid cell 0-6.19 m), ocnBgchem: Canadian Ocean Ecosystem (CanOE) with OMIP prescribed carbon chemistry, seaIce: LIM2. The model was run by the Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC V8P 5C2, Canada (CCCma) in native nominal resolutions: aerosol: 500 km, atmos: 500 km, atmosChem: 500 km, land: 500 km, landIce: 500 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: orcid bw Clarke, Harry;
    Clarke, Harry
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    orcid bw D'Olivo, Juan Pablo;
    D'Olivo, Juan Pablo
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    D'Olivo, Juan Pablo in OpenAIRE
    orcid bw Conde, Mario;
    Conde, Mario
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    Evans, Richard; +1 Authors

    Preliminary ages were assigned to sample datasets by assigning seasonal trace element ratios minima and maxima in datasets to warmest and coolest months in satellite SST records and then linearly interpolating in-between

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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2019
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2019
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2019
      License: CC BY
      Data sources: PANGAEA
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