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  • Authors: Kerr, Joanna; Rickaby, Rosalind E M; Yu, Jimin; Elderfield, Henry; +1 Authors

    Glacial-interglacial changes in deep Indian and Pacific Ocean carbonate ion concentration ([CO32−]) are mainly driven by two mechanisms that operate on different timescales: 1) a long-term increase during glaciation caused by a reduction in carbonate deposition on shelf areas (i.e, the coral reef hypothesis), and 2) transient carbonate compensation responses to changes in deep ocean carbon storage. To investigate these mechanisms, we use benthic B/Ca to reconstruct deep water [CO32-] in cores from the deep Indian and Equatorial Pacific Oceans during the past five glacial cycles. Based on our reconstructions, we suggest that the redistribution of carbonate deposition from shelf areas to the deep ocean raised deep water [CO32−] on average by 7.3 ± 0.5 (SE) umol/kg during glaciations. Oceanic carbon reorganizations during major climatic transitions caused deep water [CO32−] deviations away from the long-term trend and carbonate compensation processes subsequently acted to restore new steady state conditions. Glacial-interglacial trends in [CO32−] are generally in good agreement with records of sediment carbonate contents (%CaCO3), suggesting that seafloor %CaCO3 is dominated by changes in carbonate preservation in deep water at our studied sites. Supplement to: Kerr, Joanna; Rickaby, Rosalind E M; Yu, Jimin; Elderfield, Henry; Sadekov, Aleksey Y (2017): The effect of ocean alkalinity and carbon transfer on deep-sea carbonate ion concentration during the past five glacial cycles. Earth and Planetary Science Letters, 471, 42-53

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    Authors: Paul, Allanah Joy; Arístegui, Javier; Bach, Lennart Thomas; Hernández-Hernández, Nauzet; +3 Authors

    This data was collected during an short-term incubation experiment in March 2017 that investigated the response of a surface plankton community to upwelling. This experiment was carried in the framework of the SFB754-funded KOSMOS mesocosm study that took place in La Punta, Callao, Peru between February-April 2017. A total of six different treatments were used to disentangle chemical and biological characteristics of deep water that influence surface plankton blooms: 2 different deep water sources with different nutrient concentrations; 3 treatments to distinguish the effects of inorganic nutrients, organic nutrients and deep water microbial populations. Measured variables include inorganic nutrient concentrations, phytoplankton abundances, Chlorophyll a, cDOM, and rates of leucine aminopeptidase activity.

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    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2022
      Data sources: B2FIND
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    Authors: Bailey, Ian; Hemming, Sidney R; Reilly, Brendan T;

    Ar-Ar ages of 58 individual hornblendes and micas picked from a discrete iceberg-rafted layer deposited ~1.2 Ma at IODP U1538. The layer was recovered 310.79–310.82 meters below sea floor in Hole U1538A-36X-3W. All hornblende and mica (mostly biotite) were handpicked from the 250-μm to 1-mm size fraction, with additional mica picked from the 63–250-μm size fraction. Hornblende, biotite and standards were irradiated at the Cd-lined in-core facility (CLICIT) at the Oregon State reactor. 40Ar/39Ar ages were obtained using single-step CO2 laser fusion at the Lamont Doherty Earth Observatory argon geochronology lab (AGES: Argon Geochronology for the Earth Sciences) to release argon, followed by cleanup with Zr-Ar getters heated at 2-amps. Extracted and cleaned gases were measured on a VG5400 noble gas mass spectrometer in peak hopping mode on an analogue multiplier, using the program Massspec. Nuclear interference corrections used values for OSU from Renne et al. (1998), and data were also corrected for background and mass discrimination using measured blanks and air pipettes. J values used to calculate ages were based on co-irradiated Fish Canyon sanidine standard (28.201±0.046 Ma; Kuiper et al. (2008), with decay constants from Min et al. (2000)).

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    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2022
      Data sources: B2FIND
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    Authors: Zamanillo, Marina; Simó, Rafel;

    Dataset abstract TEP are operationally defined as gel particles that are retained on 0.4 ��m polycarbonate filters and stained with the cationic copper phthalocyanine dye Alcian Blue 8GX at pH 2.5. CSP are gel particles retained on 0.4 ��m polycarbonate filters that are stained with a solution of Coomassie Brilliant Blue G (CCB) at pH 7.4. Seawater surface samples (5 m) were collected every 6 hours from the ship���s underway pump. In addition, vertical profiles (6 depths, generally from 5 to 100-150 m) were sampled from 19 CTD casts using a SBE 911 Plus attached to a rosette of 24 12-L PVC Niskin bottles. This dataset presents TEP and CSP from seawater samples collected from the ship���s underway pump and CTDs. Samples were collected around the Southern Ocean on the R/V Akademik Tryoshnikov in the austral summer of 2016/2017, as part of the Antarctic Circumnavigation Expedition (ACE). Dataset contents ace_seawater_csp.csv, data file, comma-separated values ace_seawater_tep.csv, data file, comma-separated values data_file_header_csp.txt, metadata, text data_file_header_tep.txt, metadata, text README.txt, metadata, text Dataset license This TEP and CSP dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/ {"references": ["Passow, U., and Alldredge, A. L.: A dye-binding assay for the spectrophotometric measurement of transparent exopolymer particles (TEP), Limnology and Oceanography, 40, 1326-1335, 1995.", "Cisternas-Novoa, C., Lee, C., and Engel, A.: A semi-quantitative spectrophotometric, dye-binding assay for determination of Coomassie Blue stainable particles, Limnology and Oceanography: Methods, 12, 604-616, 10.4319/lom.2014.12.604, 2014."]} The Antarctic Circumnavigation Expedition was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals. MZ was supported by a FPU predoctoral fellowship (FPU13/04630) from the Spanish Ministry of Education and Culture.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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    Authors: Davis, Gillan;

    Appendix A - Data and QA/QC of certified reference materials of XRF. 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
    Dataset . 2021
    License: CC BY
    Data sources: Mendeley Data
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    Mendeley Data
    Dataset . 2021
    License: CC BY
    Data sources: Mendeley Data
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    Mendeley Data
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    Mendeley Data; NARCIS
    Dataset . 2021
    License: CC BY
    Data sources: Datacite; NARCIS
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    DANS-EASY
    Dataset . 2021
    Data sources: B2FIND
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      Mendeley Data
      Dataset . 2021
      License: CC BY
      Data sources: Mendeley Data
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      Dataset . 2021
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      Data sources: Mendeley Data
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      Mendeley Data
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Mendeley Data; NARCIS
      Dataset . 2021
      License: CC BY
      Data sources: Datacite; NARCIS
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      DANS-EASY
      Dataset . 2021
      Data sources: B2FIND
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  • Authors: Menviel, Laurie;

    Hydrological changes during the penultimate deglaciation and Last interglacial as simulated in a transient experiment performed with LOVECLIM and focusing on North Africa A transient experiment of the penultimate deglaciation and Last interglacial (140-120 ka) is performed with LOVECLIM following the PMIP4 protocol (Menviel et al., 2019) https://gmd.copernicus.org/articles/12/3649/2019/

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    Authors: Zahajská, Petra; Shemesh, Aldo; Conley, Daniel J;

    ¹⁴C data and age-depth models based on ¹⁴C data from two cores sampled from Lake 850 in 1999 and 2019. Radiometric dates were calibrated with IntCal20 radiocarbon calibration dataset (Reimer et al. 2020). For age-depth models calculated using R package Bacon see doi:10.1594/PANGAEA.933325. Lake850-Core3-1999 data are from Shemesh et al., 2001.

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    PANGAEA
    Dataset . 2021
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2021
      Data sources: B2FIND
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    Authors: Scientific Data Curation Team;

    This dataset contains key characteristics about the data described in the Data Descriptor High-resolution, large-scale laboratory measurements of a sandy beach and dynamic cobble berm revetment. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format

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    Dataset . 2021
    License: CC 0
    Data sources: Datacite
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      Dataset . 2021
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    Authors: Menviel, Laurie;

    LIG127k PMIP4 protocol Timeslice experiment of 127ka performed with constant but appropriate orbital parameters, and GHG. Ice-sheets are set to PI extent. Model used is LOVECLIM (Goosse et al., 2010). LIG127k experiment performed with LOVECLIM following the PMIP4 protocol https://pmip4.lsce.ipsl.fr/doku.php/exp_design:lig127

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    https://doi.org/10.26190/5f3dd...
    Dataset . 2020
    License: CC BY ND
    Data sources: Datacite; Sygma
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      https://doi.org/10.26190/5f3dd...
      Dataset . 2020
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    Authors: Anderson, Harris J; Pedro, Joel B; Bostock, Helen C; Chase, Zanna; +1 Authors
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    PANGAEA
    Dataset . 2020
    Data sources: B2FIND
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      Dataset . 2020
      Data sources: B2FIND
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  • Authors: Kerr, Joanna; Rickaby, Rosalind E M; Yu, Jimin; Elderfield, Henry; +1 Authors

    Glacial-interglacial changes in deep Indian and Pacific Ocean carbonate ion concentration ([CO32−]) are mainly driven by two mechanisms that operate on different timescales: 1) a long-term increase during glaciation caused by a reduction in carbonate deposition on shelf areas (i.e, the coral reef hypothesis), and 2) transient carbonate compensation responses to changes in deep ocean carbon storage. To investigate these mechanisms, we use benthic B/Ca to reconstruct deep water [CO32-] in cores from the deep Indian and Equatorial Pacific Oceans during the past five glacial cycles. Based on our reconstructions, we suggest that the redistribution of carbonate deposition from shelf areas to the deep ocean raised deep water [CO32−] on average by 7.3 ± 0.5 (SE) umol/kg during glaciations. Oceanic carbon reorganizations during major climatic transitions caused deep water [CO32−] deviations away from the long-term trend and carbonate compensation processes subsequently acted to restore new steady state conditions. Glacial-interglacial trends in [CO32−] are generally in good agreement with records of sediment carbonate contents (%CaCO3), suggesting that seafloor %CaCO3 is dominated by changes in carbonate preservation in deep water at our studied sites. Supplement to: Kerr, Joanna; Rickaby, Rosalind E M; Yu, Jimin; Elderfield, Henry; Sadekov, Aleksey Y (2017): The effect of ocean alkalinity and carbon transfer on deep-sea carbonate ion concentration during the past five glacial cycles. Earth and Planetary Science Letters, 471, 42-53

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    Authors: Paul, Allanah Joy; Arístegui, Javier; Bach, Lennart Thomas; Hernández-Hernández, Nauzet; +3 Authors

    This data was collected during an short-term incubation experiment in March 2017 that investigated the response of a surface plankton community to upwelling. This experiment was carried in the framework of the SFB754-funded KOSMOS mesocosm study that took place in La Punta, Callao, Peru between February-April 2017. A total of six different treatments were used to disentangle chemical and biological characteristics of deep water that influence surface plankton blooms: 2 different deep water sources with different nutrient concentrations; 3 treatments to distinguish the effects of inorganic nutrients, organic nutrients and deep water microbial populations. Measured variables include inorganic nutrient concentrations, phytoplankton abundances, Chlorophyll a, cDOM, and rates of leucine aminopeptidase activity.

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    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2022
      Data sources: B2FIND
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    Authors: Bailey, Ian; Hemming, Sidney R; Reilly, Brendan T;

    Ar-Ar ages of 58 individual hornblendes and micas picked from a discrete iceberg-rafted layer deposited ~1.2 Ma at IODP U1538. The layer was recovered 310.79–310.82 meters below sea floor in Hole U1538A-36X-3W. All hornblende and mica (mostly biotite) were handpicked from the 250-μm to 1-mm size fraction, with additional mica picked from the 63–250-μm size fraction. Hornblende, biotite and standards were irradiated at the Cd-lined in-core facility (CLICIT) at the Oregon State reactor. 40Ar/39Ar ages were obtained using single-step CO2 laser fusion at the Lamont Doherty Earth Observatory argon geochronology lab (AGES: Argon Geochronology for the Earth Sciences) to release argon, followed by cleanup with Zr-Ar getters heated at 2-amps. Extracted and cleaned gases were measured on a VG5400 noble gas mass spectrometer in peak hopping mode on an analogue multiplier, using the program Massspec. Nuclear interference corrections used values for OSU from Renne et al. (1998), and data were also corrected for background and mass discrimination using measured blanks and air pipettes. J values used to calculate ages were based on co-irradiated Fish Canyon sanidine standard (28.201±0.046 Ma; Kuiper et al. (2008), with decay constants from Min et al. (2000)).

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    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2022
      Data sources: B2FIND
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    Authors: Zamanillo, Marina; Simó, Rafel;

    Dataset abstract TEP are operationally defined as gel particles that are retained on 0.4 ��m polycarbonate filters and stained with the cationic copper phthalocyanine dye Alcian Blue 8GX at pH 2.5. CSP are gel particles retained on 0.4 ��m polycarbonate filters that are stained with a solution of Coomassie Brilliant Blue G (CCB) at pH 7.4. Seawater surface samples (5 m) were collected every 6 hours from the ship���s underway pump. In addition, vertical profiles (6 depths, generally from 5 to 100-150 m) were sampled from 19 CTD casts using a SBE 911 Plus attached to a rosette of 24 12-L PVC Niskin bottles. This dataset presents TEP and CSP from seawater samples collected from the ship���s underway pump and CTDs. Samples were collected around the Southern Ocean on the R/V Akademik Tryoshnikov in the austral summer of 2016/2017, as part of the Antarctic Circumnavigation Expedition (ACE). Dataset contents ace_seawater_csp.csv, data file, comma-separated values ace_seawater_tep.csv, data file, comma-separated values data_file_header_csp.txt, metadata, text data_file_header_tep.txt, metadata, text README.txt, metadata, text Dataset license This TEP and CSP dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/ {"references": ["Passow, U., and Alldredge, A. L.: A dye-binding assay for the spectrophotometric measurement of transparent exopolymer particles (TEP), Limnology and Oceanography, 40, 1326-1335, 1995.", "Cisternas-Novoa, C., Lee, C., and Engel, A.: A semi-quantitative spectrophotometric, dye-binding assay for determination of Coomassie Blue stainable particles, Limnology and Oceanography: Methods, 12, 604-616, 10.4319/lom.2014.12.604, 2014."]} The Antarctic Circumnavigation Expedition was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals. MZ was supported by a FPU predoctoral fellowship (FPU13/04630) from the Spanish Ministry of Education and Culture.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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      Dataset . 2021
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      ZENODO
      Dataset . 2021
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    Authors: Davis, Gillan;

    Appendix A - Data and QA/QC of certified reference materials of XRF. 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
    Dataset . 2021
    License: CC BY
    Data sources: Mendeley Data
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    Mendeley Data
    Dataset . 2021
    License: CC BY
    Data sources: Mendeley Data
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    Mendeley Data
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    Mendeley Data; NARCIS
    Dataset . 2021
    License: CC BY
    Data sources: Datacite; NARCIS
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    DANS-EASY
    Dataset . 2021
    Data sources: B2FIND
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      Dataset . 2021
      License: CC BY
      Data sources: Mendeley Data
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      Mendeley Data
      Dataset . 2021
      License: CC BY
      Data sources: Mendeley Data
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      Mendeley Data
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Mendeley Data; NARCIS
      Dataset . 2021
      License: CC BY
      Data sources: Datacite; NARCIS
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      DANS-EASY
      Dataset . 2021
      Data sources: B2FIND
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  • Authors: Menviel, Laurie;

    Hydrological changes during the penultimate deglaciation and Last interglacial as simulated in a transient experiment performed with LOVECLIM and focusing on North Africa A transient experiment of the penultimate deglaciation and Last interglacial (140-120 ka) is performed with LOVECLIM following the PMIP4 protocol (Menviel et al., 2019) https://gmd.copernicus.org/articles/12/3649/2019/

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    Authors: Zahajská, Petra; Shemesh, Aldo; Conley, Daniel J;

    ¹⁴C data and age-depth models based on ¹⁴C data from two cores sampled from Lake 850 in 1999 and 2019. Radiometric dates were calibrated with IntCal20 radiocarbon calibration dataset (Reimer et al. 2020). For age-depth models calculated using R package Bacon see doi:10.1594/PANGAEA.933325. Lake850-Core3-1999 data are from Shemesh et al., 2001.

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    PANGAEA
    Dataset . 2021
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2021
      Data sources: B2FIND
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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: Scientific Data Curation Team;

    This dataset contains key characteristics about the data described in the Data Descriptor High-resolution, large-scale laboratory measurements of a sandy beach and dynamic cobble berm revetment. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format

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    figshare
    Dataset . 2021
    License: CC 0
    Data sources: Datacite
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      Dataset . 2021
      License: CC 0
      Data sources: Datacite
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    Authors: Menviel, Laurie;

    LIG127k PMIP4 protocol Timeslice experiment of 127ka performed with constant but appropriate orbital parameters, and GHG. Ice-sheets are set to PI extent. Model used is LOVECLIM (Goosse et al., 2010). LIG127k experiment performed with LOVECLIM following the PMIP4 protocol https://pmip4.lsce.ipsl.fr/doku.php/exp_design:lig127

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    https://doi.org/10.26190/5f3dd...
    Dataset . 2020
    License: CC BY ND
    Data sources: Datacite; Sygma
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      https://doi.org/10.26190/5f3dd...
      Dataset . 2020
      License: CC BY ND
      Data sources: Datacite; Sygma
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    Authors: Anderson, Harris J; Pedro, Joel B; Bostock, Helen C; Chase, Zanna; +1 Authors
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    PANGAEA
    Dataset . 2020
    Data sources: B2FIND
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      Dataset . 2020
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