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  • PANGAEA  (8)
  • 2015-2019  (8)
Collection
Keywords
Years
Year
  • 1
    Publication Date: 2023-03-02
    Keywords: Arctic Ocean; Crystal size; Date/Time of event; Event label; ICEM; Ice measurement; LA11-ICE; LA11-ICE_20; LA11-ICE_21; LA11-ICE_22; LA11-ICE_27b; Lance; Latitude of event; Longitude of event; Maximum caliper diameter (dmax); Number; Sample ID; Sample position; Sample type; Standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 49 data points
    Location Call Number Expected Availability
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  • 2
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    PANGAEA
    In:  Supplement to: Bakker, Dorothee C E; Pfeil, Benjamin; Landa, Camilla S; Metzl, Nicolas; O'Brien, Kevin M; Olsen, Are; Smith, Karl; Cosca, Catherine E; Harasawa, Sumiko; Jones, Steve D; Nakaoka, Shin-Ichiro; Nojiri, Yukihiro; Schuster, Ute; Steinhoff, Tobias; Sweeney, Colm; Takahashi, Taro; Tilbrook, Bronte; Wada, Chisato; Wanninkhof, Rik; Alin, Simone R; Balestrini, Carlos F; Barbero, Leticia; Bates, Nicolas R; Bianchi, Alejandro A; Bonou, Frédéric Kpédonou; Boutin, Jacqueline; Bozec, Yann; Burger, Eugene; Cai, Wei-Jun; Castle, Robert D; Chen, Liqi; Chierici, Melissa; Currie, Kim I; Evans, Wiley; Featherstone, Charles; Feely, Richard A; Fransson, Agneta; Goyet, Catherine; Greenwood, Naomi; Gregor, Luke; Hankin, Steven; Hardman-Mountford, Nicolas J; Harlay, Jérôme; Hauck, Judith; Hoppema, Mario; Humphreys, Matthew P; Hunt, Christopher W; Huss, Betty; Ibánhez, J Severino P; Johannessen, Truls; Keeling, Ralph F; Kitidis, Vassilis; Körtzinger, Arne; Kozyr, Alexander; Krasakopoulou, Evangelia; Kuwata, Akira; Landschützer, Peter; Lauvset, Siv K; Lefèvre, Nathalie; Lo Monaco, Claire; Manke, Ansley; Mathis, Jeremy T; Merlivat, Liliane; Millero, Frank J; Monteiro, Pedro M S; Munro, David R; Murata, Akihiko; Newberger, Timothy; Omar, Abdirahman M; Ono, Tsuneo; Paterson, Kristina; Pearce, David J; Pierrot, Denis; Robbins, Lisa L; Saito, Shu; Salisbury, Joe; Schlitzer, Reiner; Schneider, Bernd; Schweitzer, Roland; Sieger, Rainer; Skjelvan, Ingunn; Sullivan, Kevin; Sutherland, Stewart C; Sutton, Adrienne; Tadokoro, Kazuaki; Telszewski, Maciej; Tuma, Matthias; van Heuven, Steven; Vandemark, Doug; Ward, Brian; Watson, Andrew J; Xu, Suqing (2016): A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT). Earth System Science Data, 8(2), 383-413, https://doi.org/10.5194/essd-8-383-2016
    Publication Date: 2024-02-17
    Description: The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.5 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.4 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This living data publication documents changes in the methods and data sets used in this new version of the SOCAT data collection compared with previous publications of this data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014).
    Keywords: SOCAT; Surface Ocean CO2 Atlas Project
    Type: Dataset
    Format: application/zip, 3657 datasets
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  • 3
    Publication Date: 2024-02-17
    Description: The Surface Ocean CO2 Atlas (SOCAT) is a synthesis activity by the international marine carbon research community (〉100 contributors). SOCAT version 6 has 23.4 million quality-controlled, surface ocean fCO2 (fugacity of carbon dioxide) observations from 1957 to 2017 for the global oceans and coastal seas. Calibrated sensor data are also available. Automation allows annual, public releases. SOCAT data is discoverable, accessible and citable. SOCAT enables quantification of the ocean carbon sink and ocean acidification and evaluation of ocean biogeochemical models. SOCAT represents a milestone in biogeochemical and climate research and in informing policy.
    Keywords: SOCAT; Surface Ocean CO2 Atlas Project
    Type: Dataset
    Format: application/zip, 424 datasets
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  • 4
    Publication Date: 2024-02-17
    Keywords: 58LA20150112; 58LA20150112-track; Algorithm; CT; DATE/TIME; Depth, bathymetric, interpolated/gridded; DEPTH, water; Distance; extracted from GLOBALVIEW-CO2; extracted from the 2-Minute Gridded Global Relief Data (ETOPO2); extracted from the NCEP/NCAR 40-Year Reanalysis Project; extracted from the World Ocean Atlas 2005; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Lance; LATITUDE; LONGITUDE; Pressure, atmospheric; Pressure, atmospheric, interpolated; Pressure at equilibration; Quality flag; Recomputed after SOCAT (Pfeil et al., 2013); Salinity; Salinity, interpolated; SOCAT; Surface Ocean CO2 Atlas Project; Temperature, water; Temperature at equilibration; Underway cruise track measurements; xCO2 (air), interpolated; xCO2 (water) at equilibrator temperature (dry air)
    Type: Dataset
    Format: text/tab-separated-values, 508380 data points
    Location Call Number Expected Availability
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  • 5
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    PANGAEA
    In:  Supplement to: Thor, Peter; Bailey, Allison; Halsband, Claudia; Guscelli, Ella; Gorokhova, Elena; Fransson, Agneta (2016): Seawater pH Predicted for the Year 2100 Affects the Metabolic Response to Feeding in Copepodites of the Arctic Copepod Calanus glacialis. PLoS ONE, 11(12), e0168735, https://doi.org/10.1371/journal.pone.0168735
    Publication Date: 2024-03-15
    Description: Widespread ocean acidification (OA) is transforming the chemistry of the global ocean, and the Arctic is recognised as a region where the earliest and strongest impacts of OA are expected. In the present study, metabolic effects of OA and its interaction with food availability was investigated in Calanus glacialis from the Kongsfjord, West Spitsbergen. We measured metabolic rates and RNA/DNA ratios (an indicator of biosynthesis) concurrently in fed and unfed individuals of copepodite stages CII-CIII and CV subjected to two different pH levels representative of present day and the "business as usual" IPCC scenario (RCP8.5) prediction for the year 2100. The copepods responded more strongly to changes in food level than to decreasing pH, both with respect to metabolic rate and RNA/DNA ratio. However, significant interactions between effects of pH and food level showed that effects of pH and food level act in synergy in copepodites of C. glacialis. While metabolic rates in copepodites stage CII-CIII increased by 78% as a response to food under present day conditions (high pH), the increase was 195% in CII-CIIIs kept at low pH-a 2.5 times greater increase. This interaction was absent for RNA/DNA, so the increase in metabolic rates were clearly not a reaction to changing biosynthesis at low pH per se but rather a reaction to increased metabolic costs per unit of biosynthesis. Interestingly, we did not observe this difference in costs of growth in stage CV. A 2.5 times increase in metabolic costs of growth will leave the copepodites with much less energy for growth. This may infer significant changes to the C. glacialis population during future OA.
    Keywords: Alkalinity, total; Alkalinity, total, standard deviation; Animalia; Aragonite saturation state; Arctic; Arthropoda; Bicarbonate ion; Bottles or small containers/Aquaria (〈20 L); Calanus glacialis; Calcite saturation state; Calculated using CO2SYS; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Coast and continental shelf; Coulometric titration; DNA content per individual; EXP; Experiment; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Laboratory experiment; Metabolic rate of carbon per carbon mass; OA-ICC; Ocean Acidification International Coordination Centre; Other; Partial pressure of carbon dioxide, standard deviation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Pelagos; pH; pH, standard deviation; Polar; Potentiometric titration; Registration number of species; Respiration; RNA/DNA ratio; Salinity; Salinity, standard deviation; Single species; Species; Svalbard_OA; Temperature, water; Temperature, water, standard deviation; Treatment; Type; Uniform resource locator/link to reference; Zooplankton
    Type: Dataset
    Format: text/tab-separated-values, 9367 data points
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  • 6
    Publication Date: 2024-03-15
    Description: Our study addresses how environmental variables, such as macronutrients concentrations, snow cover, carbonate chemistry and salinity affect the photophysiology and biomass of Antarctic sea-ice algae. We have measured vertical profiles of inorganic macronutrients (phosphate, nitrite + nitrate and silicic acid) in summer sea ice and photophysiology of ice algal assemblages in the poorly studied Amundsen and Ross Seas sectors of the Southern Ocean. Brine-scaled bacterial abundance, chl a and macronutrient concentrations were often high in the ice and positively correlated with each other. Analysis of photosystem II rapid light curves showed that microalgal cells in samples with high phosphate and nitrite + nitrate concentrations had reduced maximum relative electron transport rate and photosynthetic efficiency. We also observed strong couplings of PSII parameters to snow depth, ice thickness and brine salinity, which highlights a wide range of photoacclimation in Antarctic pack-ice algae. It is likely that the pack ice was in a post-bloom situation during the late sea-ice season, with low photosynthetic efficiency and a high degree of nutrient accumulation occurring in the ice. In order to predict how key biogeochemical processes are affected by future changes in sea ice cover, such as in situ photosynthesis and nutrient cycling, we need to understand how physicochemical properties of sea ice affect the microbial community. Our results support existing hypothesis about sea-ice algal photophysiology, and provide additional observations on high nutrient concentrations in sea ice that could influence the planktonic communities as the ice is retreating.
    Keywords: Alkalinity, total; Antarctic; Aragonite saturation state; Bacteria; Bicarbonate ion; Biomass/Abundance/Elemental composition; Calcite saturation state; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Chlorophyll a; Coast and continental shelf; Core; DEPTH, ice/snow; Electron transport rate efficiency; Entire community; Field observation; Fucoxanthin; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Ice thickness; Identification; Irradiance; LATITUDE; Light saturation; LONGITUDE; Maximal electron transport rate, relative; Maximum photochemical quantum yield of photosystem II; Nitrate and Nitrite; Non photochemical quenching; OA-ICC; Ocean Acidification International Coordination Centre; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Pelagos; pH; Phosphate; Polar; Primary production/Photosynthesis; Salinity; Section; Silicate; Station label; Temperature, water; Type
    Type: Dataset
    Format: text/tab-separated-values, 3286 data points
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  • 7
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    PANGAEA
    In:  Department of Chemistry, University of Gothenburg
    Publication Date: 2024-02-17
    Keywords: 77DN20050720; 77DN20050720-track; Algorithm; CT; DATE/TIME; Depth, bathymetric, interpolated/gridded; DEPTH, water; Distance; extracted from GLOBALVIEW-CO2; extracted from the 2-Minute Gridded Global Relief Data (ETOPO2); extracted from the NCEP/NCAR 40-Year Reanalysis Project; extracted from the World Ocean Atlas 2005; Fugacity of carbon dioxide (water) at equilibrator temperature (wet air); Fugacity of carbon dioxide (water) at sea surface temperature (wet air); LATITUDE; LONGITUDE; Oden; Pressure, atmospheric, interpolated; Quality flag; Recomputed after SOCAT (Pfeil et al., 2013); Salinity; Salinity, interpolated; SOCAT; Surface Ocean CO2 Atlas Project; Temperature, water; Underway cruise track measurements; xCO2 (air), interpolated
    Type: Dataset
    Format: text/tab-separated-values, 120431 data points
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  • 8
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    PANGAEA
    In:  Department of Chemistry, University of Gothenburg
    Publication Date: 2024-02-17
    Keywords: 77DN20061214; 77DN20061214-track; Algorithm; CT; DATE/TIME; Depth, bathymetric, interpolated/gridded; DEPTH, water; Distance; extracted from GLOBALVIEW-CO2; extracted from the 2-Minute Gridded Global Relief Data (ETOPO2); extracted from the NCEP/NCAR 40-Year Reanalysis Project; extracted from the World Ocean Atlas 2005; Fugacity of carbon dioxide (water) at equilibrator temperature (wet air); Fugacity of carbon dioxide (water) at sea surface temperature (wet air); LATITUDE; LONGITUDE; Oden; Pressure, atmospheric, interpolated; Quality flag; Recomputed after SOCAT (Pfeil et al., 2013); Salinity; Salinity, interpolated; SOCAT; Surface Ocean CO2 Atlas Project; Temperature, water; Underway cruise track measurements; xCO2 (air), interpolated
    Type: Dataset
    Format: text/tab-separated-values, 132237 data points
    Location Call Number Expected Availability
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