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  • Energy Research
  • 2016-2025
  • 14. Life underwater

  • Authors: Greenland Ecosystem Monitoring;

    Weekly data on flowering phenology the as wells as annual total flower production in permanent Silene acaulis plots. For further details, please refer to the newest BioBasis manual available at the website. Vegetation:Vegetation BioBasis Zackenberg:The BioBasis programme monitors the dynamics of organisms and biological processes in the terrestrial and limnic ecosystems at Zackenberg and Nuuk. The BioBasis programme plays a central role in the development and implementation of the Circumpolar Biodiversity Monitoring Programme (CBMP) http://www.caff.is/monitoring across the Arctic.

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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: Andrew R. Pearson (10215183); Bethany R. S. Fox (4380301); Marcus J. Vandergoes (10215186); Adam Hartland (1461664);

    Lake sediments are the physical remnants of past allochthonous and autochthonous carbon and mineral inputs and therefore have the potential to illuminate both past terrestrial carbon cycling and within-lake biological productivity. However, there are currently no robust, rapid, and inexpensive methods to chemically characterise the organic matter (OM) components in lake sediments, which limits their utility for reconstructing past soil carbon export trends or trophic status. This study explores the use of 3D excitation–emission matrix (EEM) fluorescence spectroscopy of water extractable dissolved organic matter (WEDOM) from lake sediments as a method for reconstructing past soil dissolved organic matter (DOM) export and past lake water quality. Using contemporary lake sediments from 11 New Zealand lakes, we demonstrate that both overall WEDOM fluorescence and protein-like fluorescence intensity are strong functions of trophic status across lakes. We also demonstrate that protein-like fluorescence is a function of sedimentary total nitrogen concentrations in palaeo-sediments from a pristine, high-altitude lake (Adelaide Tarn). This approach has applications in the evaluation of the trophic status of infrequently monitored lakes and in palaeolimnology.

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    figshare
    Dataset . 2021
    License: CC BY NC ND
    Data sources: Datacite
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    figshare
    Dataset . 2021
    License: CC BY NC ND
    Data sources: Datacite
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY NC ND
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      Dataset . 2021
      License: CC BY NC ND
      Data sources: Datacite
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      figshare
      Dataset . 2021
      License: CC BY NC ND
      Data sources: Datacite
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      Smithsonian figshare
      Dataset . 2021
      License: CC BY NC ND
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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: Santos, Catarina; Borges, Francisco; Sampaio, Eduardo; Figueiredo, Cátia; +4 Authors

    The dramatic decline of European eel (Anguilla anguilla) populations over recent decades has attracted considerable attention and concern. Furthermore, little is known concerning the sensitivity of eel’s early stages to projected future environmental change. Here we investigated, for the first time, the potential combined effects of ocean warming (OW; ∆ + 4oC; 18oC) and acidification (OA; ∆ - 0.4 pH units) on the survival and migratory behaviour of A. anguilla glass eels, namely their preference towards riverine cues (freshwater and geosmin). Recently arrived individuals were exposed to isolated and combined OW- and OA–conditions for 100 days, adjusting for the salinity gradients associated with upstream migration. A two-choice test was used to investigate migratory activity and shifts in preference towards freshwater environments. While OW decreased survival and increased migratory activity, OA appears to hinder migratory response, reducing the preference for riverine cues. Our results suggest that future conditions could potentially favor an early settlement of glass eels, reducing the proportion of fully-migratory individuals. Further research into the effects of climate change on eel migration and habitat selection is needed to implement efficient conservation plans for this critically endangered species. Santos&Borges_etal_DataIn this file, the data from our study on the influence of ocean warming and ocean acidification on the riverward migration of glass eels is present. These include survival and behavioural outputs as well as a code sheet for easier table read. The tables are R software ready and can be exported as '.csv' in order to run in the Rscript.BorgesSantos_etal_Data.xlsxSantos&Borges_etal_RscriptThis is the code for the Rscript of the statistical analysis performed in our study.BorgesSantos_etal_Rscript.txt

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    ZENODO
    Dataset . 2019
    License: CC 0
    Data sources: ZENODO
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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
    DRYAD
    Dataset . 2019
    License: CC 0
    Data sources: Datacite
    DRYAD
    Dataset . 2019
    License: CC 0
    Data sources: Datacite
    DRYAD
    Dataset . 2019
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2019
      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 . 2019
      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/
      B2FIND
      Dataset . 2019
      Data sources: B2FIND
      DRYAD
      Dataset . 2019
      License: CC 0
      Data sources: Datacite
      DRYAD
      Dataset . 2019
      License: CC 0
      Data sources: Datacite
      DRYAD
      Dataset . 2019
      License: CC 0
      Data sources: Datacite
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    Authors: Zanna, Laure; Khatiwala, Samar; Gregory, Jonathan; Ison, Jonathan; +1 Authors

    Reconstruction of 1870-2018 ocean heat content (OHC_GF_1870_2018.nc) and thermosteric sea level (ThSL_GF_1870_2018.nc) using Green's functions. The method is described in Zanna et al., PNAS, 2019 This dataset is an update from the original published version with changes described here.

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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: ZENODO
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    BioStudies
    Dataset . 2019
    Data sources: BioStudies
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    Smithsonian figshare
    Dataset . 2019
    License: CC BY
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      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: ZENODO
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      BioStudies
      Dataset . 2019
      Data sources: BioStudies
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      Smithsonian figshare
      Dataset . 2019
      License: CC BY
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  • Authors: Nelson, Eric;

    NREL Modular Ocean Instrumentation System (MOIS) data files for the Azura grid-connected deployment at the 30-meter berth of the US Navy's Wave Energy Test Site (WETS 30m Site) at the Kaneohe Marine Corps Base Hawaii (MCBH) on the windward (northeast) coast of the island of Oahu, HI. See general documentation describing specifics of the data files and formats in a separate NREL submission (linked below).

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    CH4 mole fraction and δ13C data that have been measured by Royal Holloway, University of London (RHUL) from five locations around the UK. The samples were collected at Barra/Vatersay (BAR) in the Outer Hebrides, RHUL in Egham (EGH), Weybourne Atmospheric Observatory (WAO) - University of East Anglia, and the Western Channel Observatory (WCO) at two locations (E1 and L4) in the English Channel - Plymouth Marine Lab (PML). The Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME) was used to calculate the sensitivity of measurements, taken at EGH and WAO, to the surrounding emissions field. The raw NAME output files contain information about the locations of the modelled air particles at each time step. This information is processed to create hourly footprints in units of (mol/mol)(mol/m$^2$/s) for each latitude/longitude grid cell.

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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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  • Authors: Pierrick Penven;

    This realistic ocean simulation was run using the Coastal and Regional Ocean COmmunity model (CROCO), based on the Regional Ocean Modelling System (ROMS), which has 60 terrain-following vertical levels. This output (WOES 0.25) is the largest grid of a triply nested configuration: WOES I, WOES II and WOES III, with horizontal resolutions of ~22.5, 7.5 and 2.5 km respectively. Monthly ouputs of the 0.25 degree GLORYS ocean reanalysis is used to force the boundaries of WOES I. The surface forcing for this model is provided by a bulk formulation using daily ERA-Interim atmospheric reanalysis (with a resolution of ~80 km) and using a relative wind approach. The output is saved as daily averages, in monthly netcdf files spanning January 1993 - December 2014. WOES 0.25 spans 55.7degS to 3.18388 degS and 10degW to 102.25degE and covers most of the Southern Subtropical Indian Ocean and a part of the Southern Atlantic Ocean. Model output includes: averaged free-surface (zeta), averaged vertically integrated u-momentum component (ubar), averaged vertically integrated v-momentum component (vbar), averaged u-momentum component (u), averaged v-momentum component (v), averaged potential temperature (temp), averaged salinity (salt), averaged vertical momentum component (w). Numerical computations were performed on the IDRIS (Institut du Developpement et des Ressources en Informatique Scientifique) IBM "ADA" computer facility (under grant A0020107630)

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    This data was collected during a study on the perceptions of RAS-produced fish in Germany. In the discussion of expanding sustainable aquaculture production in the EU, recirculating aquaculture systems (RAS) adopt an increasingly important role. While capable of mitigating certain environmental externalities commonly found with other forms of aquaculture and enabling the intensive production of safe and healthy aquatic products, RAS are also characterized by higher investment and operating costs which require higher sales prices. Incorporating principles from the theory of planned behavior, multi-attribute attitude models and a taste test, this research investigates consumers’ and fine dining chefs’ perception of RAS-produced fish using the example of pikeperch (Sander lucioperca). While perception and stated purchase intention of RAS-produced pikeperch is generally positive, results reveal a comparably small portion of consumers willing to pay above average prices. Healthiness related aspects are of greatest relevance to both investigated groups and regression analysis shows that personal norms and moral obligation are significant positive predictors of consumers’ purchase intention.

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    Mendeley Data
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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    Authors: Bode, Antonio; Louro, M Ángeles; Rey, Elena;

    Abundance and biomass of mesozooplankton (>200µm) in monthly samples collected in a shelf station off A Coruña (NW Spain) between 1990 and 2018. Zooplankton sampled approximately at monthly intervals between January 1990 and December 2018 at Station E2CO (A Coruña, NW Spain) with double-oblique tows (0-50 m depth) of a 50 cm diameter Juday-Bogorov plankton net with 250 μm (until 1997) or 200 μm (from 1997 onwards) mesh size. The net was equipped with a General Oceanic Flowmeter for the calculation of water filtered and a depth recorder. All samples were collected between 10:00 and 14:00 (local time) and were preserved in 2−4% sodium borate-buffered formaldehyde. Sub-samples were taken to estimate total zooplankton abundance (N m−3) by direct examination using a stereo microscope, and biomass (in mg DW m−3) by weighting dried aliquots (50 °C, 48 h). Species names referenced to the Word Register of Marine Species (last access: June 2019). Zooplankton identification and counts were made by M.T. Álvarez-Ossorio (until 2015), E. Rey and M.A. Louro (from 2016 onwards). These series are part of the long-term observational project RADIALES (Instituto Español de Oceanografía, IEO, Spain). #999 = taxon not considered in a particular record0.0 = taxon considered but not present

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    B2FIND
    Dataset . 2020
    Data sources: B2FIND
    PANGAEA
    Dataset . 2020
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2020
      Data sources: B2FIND
      PANGAEA
      Dataset . 2020
      Data sources: PANGAEA
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    Data and R script related to the third (MPhil) thesis chapter: 'The Vulnerability of World Heritage seagrass habitats to climate change' The data were collected through 2 quantitative surveys targeting seagrass experts and site managers of WH properties. Data includes opinions on exposure and sensitivity of seagrass in 6 bioregions to 19 stressors, cumulative impact type and level of adaptive capacity. Software/equipment used to create/collect the data: Data were collected through 2 online surveys with the software Survey Monkey (Advantage Plan) Software/equipment used to manipulate/analyse the data: Data were analysed with R and RStudio Version:RStudio 2021.09.2+382 "Ghost Orchid" Release (fc9e217980ee9320126e33cdf334d4f4e105dc4f, 2022-01-04) for WindowsMozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) QtWebEngine/5.12.8 Chrome/69.0.3497.128 Safari/537.36

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    https://dx.doi.org/10.25903/84...
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      https://dx.doi.org/10.25903/84...
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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  • Authors: Greenland Ecosystem Monitoring;

    Weekly data on flowering phenology the as wells as annual total flower production in permanent Silene acaulis plots. For further details, please refer to the newest BioBasis manual available at the website. Vegetation:Vegetation BioBasis Zackenberg:The BioBasis programme monitors the dynamics of organisms and biological processes in the terrestrial and limnic ecosystems at Zackenberg and Nuuk. The BioBasis programme plays a central role in the development and implementation of the Circumpolar Biodiversity Monitoring Programme (CBMP) http://www.caff.is/monitoring across the Arctic.

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    Authors: Andrew R. Pearson (10215183); Bethany R. S. Fox (4380301); Marcus J. Vandergoes (10215186); Adam Hartland (1461664);

    Lake sediments are the physical remnants of past allochthonous and autochthonous carbon and mineral inputs and therefore have the potential to illuminate both past terrestrial carbon cycling and within-lake biological productivity. However, there are currently no robust, rapid, and inexpensive methods to chemically characterise the organic matter (OM) components in lake sediments, which limits their utility for reconstructing past soil carbon export trends or trophic status. This study explores the use of 3D excitation–emission matrix (EEM) fluorescence spectroscopy of water extractable dissolved organic matter (WEDOM) from lake sediments as a method for reconstructing past soil dissolved organic matter (DOM) export and past lake water quality. Using contemporary lake sediments from 11 New Zealand lakes, we demonstrate that both overall WEDOM fluorescence and protein-like fluorescence intensity are strong functions of trophic status across lakes. We also demonstrate that protein-like fluorescence is a function of sedimentary total nitrogen concentrations in palaeo-sediments from a pristine, high-altitude lake (Adelaide Tarn). This approach has applications in the evaluation of the trophic status of infrequently monitored lakes and in palaeolimnology.

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    figshare
    Dataset . 2021
    License: CC BY NC ND
    Data sources: Datacite
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    figshare
    Dataset . 2021
    License: CC BY NC ND
    Data sources: Datacite
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY NC ND
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      figshare
      Dataset . 2021
      License: CC BY NC ND
      Data sources: Datacite
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      figshare
      Dataset . 2021
      License: CC BY NC ND
      Data sources: Datacite
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      Smithsonian figshare
      Dataset . 2021
      License: CC BY NC ND
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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: Santos, Catarina; Borges, Francisco; Sampaio, Eduardo; Figueiredo, Cátia; +4 Authors

    The dramatic decline of European eel (Anguilla anguilla) populations over recent decades has attracted considerable attention and concern. Furthermore, little is known concerning the sensitivity of eel’s early stages to projected future environmental change. Here we investigated, for the first time, the potential combined effects of ocean warming (OW; ∆ + 4oC; 18oC) and acidification (OA; ∆ - 0.4 pH units) on the survival and migratory behaviour of A. anguilla glass eels, namely their preference towards riverine cues (freshwater and geosmin). Recently arrived individuals were exposed to isolated and combined OW- and OA–conditions for 100 days, adjusting for the salinity gradients associated with upstream migration. A two-choice test was used to investigate migratory activity and shifts in preference towards freshwater environments. While OW decreased survival and increased migratory activity, OA appears to hinder migratory response, reducing the preference for riverine cues. Our results suggest that future conditions could potentially favor an early settlement of glass eels, reducing the proportion of fully-migratory individuals. Further research into the effects of climate change on eel migration and habitat selection is needed to implement efficient conservation plans for this critically endangered species. Santos&Borges_etal_DataIn this file, the data from our study on the influence of ocean warming and ocean acidification on the riverward migration of glass eels is present. These include survival and behavioural outputs as well as a code sheet for easier table read. The tables are R software ready and can be exported as '.csv' in order to run in the Rscript.BorgesSantos_etal_Data.xlsxSantos&Borges_etal_RscriptThis is the code for the Rscript of the statistical analysis performed in our study.BorgesSantos_etal_Rscript.txt

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    ZENODO
    Dataset . 2019
    License: CC 0
    Data sources: ZENODO
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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
    DRYAD
    Dataset . 2019
    License: CC 0
    Data sources: Datacite
    DRYAD
    Dataset . 2019
    License: CC 0
    Data sources: Datacite
    DRYAD
    Dataset . 2019
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2019
      License: CC 0
      Data sources: ZENODO
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      B2FIND
      Dataset . 2019
      Data sources: B2FIND
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      B2FIND
      Dataset . 2019
      Data sources: B2FIND
      DRYAD
      Dataset . 2019
      License: CC 0
      Data sources: Datacite
      DRYAD
      Dataset . 2019
      License: CC 0
      Data sources: Datacite
      DRYAD
      Dataset . 2019
      License: CC 0
      Data sources: Datacite
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    Authors: Zanna, Laure; Khatiwala, Samar; Gregory, Jonathan; Ison, Jonathan; +1 Authors

    Reconstruction of 1870-2018 ocean heat content (OHC_GF_1870_2018.nc) and thermosteric sea level (ThSL_GF_1870_2018.nc) using Green's functions. The method is described in Zanna et al., PNAS, 2019 This dataset is an update from the original published version with changes described here.

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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: ZENODO
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    BioStudies
    Dataset . 2019
    Data sources: BioStudies
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    Smithsonian figshare
    Dataset . 2019
    License: CC BY
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      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: ZENODO
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      BioStudies
      Dataset . 2019
      Data sources: BioStudies
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      Smithsonian figshare
      Dataset . 2019
      License: CC BY
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  • Authors: Nelson, Eric;

    NREL Modular Ocean Instrumentation System (MOIS) data files for the Azura grid-connected deployment at the 30-meter berth of the US Navy's Wave Energy Test Site (WETS 30m Site) at the Kaneohe Marine Corps Base Hawaii (MCBH) on the windward (northeast) coast of the island of Oahu, HI. See general documentation describing specifics of the data files and formats in a separate NREL submission (linked below).

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    CH4 mole fraction and δ13C data that have been measured by Royal Holloway, University of London (RHUL) from five locations around the UK. The samples were collected at Barra/Vatersay (BAR) in the Outer Hebrides, RHUL in Egham (EGH), Weybourne Atmospheric Observatory (WAO) - University of East Anglia, and the Western Channel Observatory (WCO) at two locations (E1 and L4) in the English Channel - Plymouth Marine Lab (PML). The Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME) was used to calculate the sensitivity of measurements, taken at EGH and WAO, to the surrounding emissions field. The raw NAME output files contain information about the locations of the modelled air particles at each time step. This information is processed to create hourly footprints in units of (mol/mol)(mol/m$^2$/s) for each latitude/longitude grid cell.

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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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  • Authors: Pierrick Penven;

    This realistic ocean simulation was run using the Coastal and Regional Ocean COmmunity model (CROCO), based on the Regional Ocean Modelling System (ROMS), which has 60 terrain-following vertical levels. This output (WOES 0.25) is the largest grid of a triply nested configuration: WOES I, WOES II and WOES III, with horizontal resolutions of ~22.5, 7.5 and 2.5 km respectively. Monthly ouputs of the 0.25 degree GLORYS ocean reanalysis is used to force the boundaries of WOES I. The surface forcing for this model is provided by a bulk formulation using daily ERA-Interim atmospheric reanalysis (with a resolution of ~80 km) and using a relative wind approach. The output is saved as daily averages, in monthly netcdf files spanning January 1993 - December 2014. WOES 0.25 spans 55.7degS to 3.18388 degS and 10degW to 102.25degE and covers most of the Southern Subtropical Indian Ocean and a part of the Southern Atlantic Ocean. Model output includes: averaged free-surface (zeta), averaged vertically integrated u-momentum component (ubar), averaged vertically integrated v-momentum component (vbar), averaged u-momentum component (u), averaged v-momentum component (v), averaged potential temperature (temp), averaged salinity (salt), averaged vertical momentum component (w). Numerical computations were performed on the IDRIS (Institut du Developpement et des Ressources en Informatique Scientifique) IBM "ADA" computer facility (under grant A0020107630)

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    This data was collected during a study on the perceptions of RAS-produced fish in Germany. In the discussion of expanding sustainable aquaculture production in the EU, recirculating aquaculture systems (RAS) adopt an increasingly important role. While capable of mitigating certain environmental externalities commonly found with other forms of aquaculture and enabling the intensive production of safe and healthy aquatic products, RAS are also characterized by higher investment and operating costs which require higher sales prices. Incorporating principles from the theory of planned behavior, multi-attribute attitude models and a taste test, this research investigates consumers’ and fine dining chefs’ perception of RAS-produced fish using the example of pikeperch (Sander lucioperca). While perception and stated purchase intention of RAS-produced pikeperch is generally positive, results reveal a comparably small portion of consumers willing to pay above average prices. Healthiness related aspects are of greatest relevance to both investigated groups and regression analysis shows that personal norms and moral obligation are significant positive predictors of consumers’ purchase intention.

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    Mendeley Data
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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    Authors: Bode, Antonio; Louro, M Ángeles; Rey, Elena;

    Abundance and biomass of mesozooplankton (>200µm) in monthly samples collected in a shelf station off A Coruña (NW Spain) between 1990 and 2018. Zooplankton sampled approximately at monthly intervals between January 1990 and December 2018 at Station E2CO (A Coruña, NW Spain) with double-oblique tows (0-50 m depth) of a 50 cm diameter Juday-Bogorov plankton net with 250 μm (until 1997) or 200 μm (from 1997 onwards) mesh size. The net was equipped with a General Oceanic Flowmeter for the calculation of water filtered and a depth recorder. All samples were collected between 10:00 and 14:00 (local time) and were preserved in 2−4% sodium borate-buffered formaldehyde. Sub-samples were taken to estimate total zooplankton abundance (N m−3) by direct examination using a stereo microscope, and biomass (in mg DW m−3) by weighting dried aliquots (50 °C, 48 h). Species names referenced to the Word Register of Marine Species (last access: June 2019). Zooplankton identification and counts were made by M.T. Álvarez-Ossorio (until 2015), E. Rey and M.A. Louro (from 2016 onwards). These series are part of the long-term observational project RADIALES (Instituto Español de Oceanografía, IEO, Spain). #999 = taxon not considered in a particular record0.0 = taxon considered but not present

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    B2FIND
    Dataset . 2020
    Data sources: B2FIND
    PANGAEA
    Dataset . 2020
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2020
      Data sources: B2FIND
      PANGAEA
      Dataset . 2020
      Data sources: PANGAEA
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    Data and R script related to the third (MPhil) thesis chapter: 'The Vulnerability of World Heritage seagrass habitats to climate change' The data were collected through 2 quantitative surveys targeting seagrass experts and site managers of WH properties. Data includes opinions on exposure and sensitivity of seagrass in 6 bioregions to 19 stressors, cumulative impact type and level of adaptive capacity. Software/equipment used to create/collect the data: Data were collected through 2 online surveys with the software Survey Monkey (Advantage Plan) Software/equipment used to manipulate/analyse the data: Data were analysed with R and RStudio Version:RStudio 2021.09.2+382 "Ghost Orchid" Release (fc9e217980ee9320126e33cdf334d4f4e105dc4f, 2022-01-04) for WindowsMozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) QtWebEngine/5.12.8 Chrome/69.0.3497.128 Safari/537.36

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    https://dx.doi.org/10.25903/84...
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      https://dx.doi.org/10.25903/84...
      Dataset . 2022
      License: CC BY
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