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  • PANGAEA  (34,085)
  • Oxford University Press
  • 2020-2024  (34,894)
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  • 1
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    Organic-walled dinoflagellate cyst of marine surface sediments and two sediment cores off southwestern Morocco (2020)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Organic-walled dinoflagellate cyst of marine surface sediments and two sediment cores (GeoB8601-3 and GeoB4223-1) off southwestern Morocco.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 3 datasets
    Location Call Number Expected Availability
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  • 2
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    Thermoluminescence (TL) and optically stimulated luminescence (OSL) sensitivities, and IRSL/OSL measurements for core GL-1248 (off Parnaíba River drainage basin, northern northeastern Brazil) (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Marine sediment core GL-1248 was collected from the continental slope off northern northeastern Brazil by Petrobras oil company. Sediment samples (154 in total) were collected with 2 cm wide scoops at every 10 cm from the uppermost 16 m (covering the the last 113 thousand years) of the marine sediment core GL-1248. Samples were oven‐dried at 60°C, precisely weighted to 0.5 g and treated with H2O2 27% and HCl 10% to remove organic matter and calcium carbonate, respectively. The remaining content was diluted in alcohol and three aliquots per sample were mounted on stainless steel discs with four drops of the homogenized solution of alcohol and silt/clay sediments. GL-1248 luminescence measurements were performed on an automated Lexsyg Smart TL/OSL reader equipped with blue and infrared LEDs, Hoya U-340 filters for light detection in the ultraviolet band (270-390 nm) using a photomultiplier and beta radiation sources (90Sr/90Y) with doses rate of 0.116 Gy s-1 at the Luminescence and Gamma Spectrometry Laboratory of the Institute of Geosciences, University of São Paulo, Brazil. The sensitivity representative of the 110°C thermoluminesce (TL) peak of quartz considered the 80–120°C integration range from the TL curve. The 80-120°C TL sensitivity was calculated as a percentage of the total TL emission (0-250°C) and using the background TL curve. The mean of three measured aliquots represents the TL sensitivity of each sample. The OSL sensitivity was calculated by integrating the first second of light emission and the last ten seconds as background. GL-1248 TL sensitivity data were compared to previously published data obtained from marine sediment core GeoB16206-1 (https://doi.org/10.1594/PANGAEA.904357). Marine sediment core GeoB16206-1 was analyzed in a different luminescence reader (i.e. RisØ OSL/TL DA-20 reader) and using different regeneration dose. In order to avoid machine artifacts and the influence of dose size on sensitivity, we normalized the TL data output from both marine sediment cores and produced a composite record. Name of the Campaign: collected by the Petrobras oil company Event Label: GL1248 (GL-1248) Method: quarzt luminescence sensitivity Latitude: -0.920000 Longitude: -43.401667 Elevation: -2,264 m
    Keywords: Luminescence sensitivity; northeastern Brazil; precipitation reconstruction; quartz grains; South America
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 3
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    Pollen, non-pollen palynomorphs, LOI, micro- and macrocharcoal and C14 records from core Razdolye, Kursk region, Russia (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: The dataset represent pollen, non-pollen palynomorphs, LOI, micro- and macrocharcoal and C14 records from core Razdolye, Kursk region, Russia. The core Razdolye was collected in 2009 by Lyudmila Shumilovskikh, Frank Schlütz, Jens Schneeweiß and Oleg Radyush with a Russian corer. Laboratory processing for palynological studies took place in the Dep. Palynology and Climate Dynamics, Georg-August-University of Göttingen in 2009 by Lyudmila Shumilovskikh and 2020 by Monika Schmidt. For each palynological sample, one millilitre of material was treated with hydrochloric acid, potassium hydroxide, hydrofluoric acid, acetolysis mixture, microsieved (6 μm) and stored in glycerol. Before acid, Lycopodium spores were added to calculate pollen influx. Microscopic identification and counting were carried out by Monika Schmidt. Standard microscopical magnification was 400×, for ambiguous objects 1000x with oil immersion. Identification and morphological pollen types follow Beug (2004) and type collections of the Dep. Palynology and Climate Dynamics, Georg-August-University of Göttingen. Non-pollen palynomorphs (NPP) follow Miola (2012) and the Non-Pollen Palynomorphs Image Database (NPP ID, http://non-pollen-palynomorphs.uni-goettingen.de/). New NPP types were described and have been uploaded to the Non-Pollen Palynomorphs Image Database (NPP ID, http://non-pollen-palynomorphs.uni-goettingen.de/). In addition, pieces of burnt plant fragments of 〉 50 µm were counted. Laboratory processing for macrocharcoal took place in the Dep. Palynology and Climate Dynamics, Georg-August-University of Göttingen in 2020 by Monika Schmidt. These samples were treated in the laboratory in Sodium Hexametaphosphate and in bleach, living overnight after each treatment and followed by sieving through 125 µm sieve. Counting of charcoal particles was carried out under a binocular microscope under 10× to 15× magnification. Samples for loss-on-ignition was processed by Monika Schmidt in 2021. Samples (1 ml) were obtained at 2 cm intervals (44 samples). LOI samples were oven-dried for 22 hours at 105 °C, for 4 hours at 550 °C and for 2 hours at 950 °C (Dean 1974; Heiri et al. 2001). LOI records are given as percentages. For an absolute chronology, bulk samples, macroremains and pollen were dated by the radiocarbon laboratories of Poznan (Poland).
    Keywords: charcoal; forest-steppe ecotone; Late Holocene; loss on ignition; macrocharcoal; Microcharcoal; non-pollen palynomorphs; Pollen
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 4
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    Summary of Bayesian onset detection algorithm for abrupt warming transitions in the NGRIP record (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Summary statistics of posterior marginal distribution of the onset of abrupt warming transitions located in the last glacial age of the NGRIP record, based on both the d18O and Ca2+ proxy. Includes both statistics for the onset depth as well as age transition. Onset depth is found by applying a linear ramp function (Erhardt et al. 2019) which is combined with a probabilistic age-depth model to infer the onset age of the transition.
    Keywords: Abrupt Warming; Bayesian; Greenland; Ice core; ICEDRILL; Ice drill; NGRIP; NorthGRIP; onset; Sampling/drilling ice; Summary; TiPES; Tipping Points in the Earth System; transition
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 5
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    Global REVEALS reconstruction of past vegetation cover for taxonomically harmonized pollen data sets (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: This data set presents the reconstructed vegetation cover for 3491 sites based on harmonized pollen data from the data set LegacyPollen 2.0 (https://doi.pangaea.de/10.1594/PANGAEA.965907). 1115 sites are located in North America, 1435 in Europe, 533 in Asia, 173 in South America, 155 in Africa, and 80 in the Indopacific. Sugita's REVEALS model (2007) was applied to all pollen records using REVEALSinR from the DISQOVER package (Theuerkauf et al. 2016). Pollen counts were translated into vegetation cover by accounting for taxon-specific pollen productivity and fall speed. Additionally, relevant source areas of pollen were calculated using the aforementioned taxon-specific parameters and a gaussian plume model for deposition and dispersal. Values for relative pollen productivity and fall speed from the synthesis from Wiezcorek and Herzschuh (2010) were used for the reconstruction of vegetation cover. The average values from all Northern Hemisphere values were used where taxon-specific continental values were not available. This includes records of the Southern Hemisphere. We present tables with reconstructed vegetation cover for all continents with original parameters. As further details we list a table with the taxon-specific parameters used and a list of parameters adjusted in the default version of REVEALSinR.
    Keywords: AWI_Envi; fossil pollen; paleoecology; Polar Terrestrial Environmental Systems @ AWI; REVEALS
    Type: Dataset
    Format: application/zip, 6 datasets
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  • 6
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    Influence of temperature, pCO2, and dissolved nutrients on the oxidative stress response and the carbon metabolism of phytoplankton (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: We conducted a full-factorial lab experiment to study the individual and combined effects of temperature (18°C and 21°C), pCO2 (400 and 1000 ppm), and dissolved N:P ratio (16 and 25 molar) on the antioxidant capacity and carbon metabolism of the phytoplankton Phaeodactylum tricornutum (strain CCAP 1052/1A). The antioxidant response was assessed based on different biomarkers, including the contents of protective carotenoids (ß-Carotene, diadinoxanthin and violaxanthin), and by determination of antioxidant enzyme activities, and Malondialdehyde (MDA) as a biomarker for oxidative stress. We quantified the activity of Managanese Superoxide Dismutase (SOD-Mn), Glutathione S-transferase (GST), Catalase (CAT), Glutathione Peroxidase (GPx). As possible consequence of oxidative stress on metabolic pathways of carbon, we also quantified carbon fluxes by measuring rates of growth, respiration, dissolved organic carbon (DOC) exudation, and cellular organic carbon content and particulate phosphorus (PP). We also quantified the concentration of photosynthetic pigments chlorophyll a (Chl-a) and fucoxanthin.
    Keywords: beta-Carotene per cell; Carbon, organic, dissolved exudation, per cell; Carbon dioxide, partial pressure; carbon metabolism; Carbon per cell; Catalase activity, unit per protein mass; Chlorophyll a per cell; Diadinoxanthin per cell; Diatom; Fucoxanthin per cell; global change; Global change vulnerability of North Sea plankton and associated ecosystem services; Glutathione peroxidase activity, unit per protein mass; Glutathione S-transferase activity, unit per protein mass; Growth rate; High performance liquid chromatography (HPLC), Agilent, Waters Alliance 2695; Malondialdehyde, per wet mass; Nitrogen/Phosphorus ratio; oxidative stress; Phosphorus, organic, particulate, production per cell; PlanktoSERV; Replicate; Respiration rate, carbon; Strain; Superoxide dismutase manganese activity, unit per protein mass; Temperature, water; TOC analyzer, Shimadzu, TOC-L CPH/CPN; Type of study; Violaxanthin per cell
    Type: Dataset
    Format: text/tab-separated-values, 630 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 7
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    REVEALS reconstruction of past vegetation cover with original RPP values for samples in Australia and Oceania (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: This data set presents the reconstructed vegetation cover for 80 Indopacific sites based on harmonized pollen data from the data set LegacyPollen 2.0 (https://doi.pangaea.de/10.1594/PANGAEA.929773). Sugita's REVEALS model (2000) was applied to all pollen records using REVEALSinR from the DISQOVER package (Theuerkauf et al. 2016). Pollen counts were translated into vegetation cover by accounting for taxon-specific pollen productivity and fall speed. Additionally, relevant source areas of pollen were calculated using the aforementioned taxon-specific parameters and a gaussian plume model for deposition and dispersal and forest cover was reconstructed. Values for relative pollen productivity and fall speed from the synthesis from Wiezcorek and Herzschuh (2010) were used for the reconstruction of vegetation cover. The average values from all Northern Hemisphere values were used where taxon-specific continental values were not available. We present tables with reconstructed vegetation cover for all continents with original parameters. As further details we list a table with the taxon-specific parameters used and a list of parameters adjusted in the default version of REVEALSinR.
    Keywords: Acacia, cover; Acanthaceae, cover; Acmena, cover; Acronychia, cover; Aegiceras, cover; Agastachys, cover; Agathis, cover; Aglaia, cover; Aidia, cover; Aizoaceae, cover; Albizia, cover; Alectryon, cover; Aleurites, cover; Allocasuarina, cover; Allophylus, cover; Alnus, cover; Alphitonia, cover; Altingia, cover; ALUAIPUGUA_Pollen; Amaranthaceae, cover; Anacardiaceae, cover; Angophora, cover; Annonaceae, cover; Anodopetalum, cover; Anopterus, cover; ANOUWE2T1_Pollen; Antidesma, cover; Antirhea, cover; Aphananthe, cover; Apiaceae, cover; Apocynaceae, cover; Araceae, cover; Araliaceae, cover; Araucaria, cover; Araucariaceae, cover; Ardisia, cover; Area; Arecaceae, cover; Arenga, cover; Aristotelia, cover; Artemisia, cover; Arytera, cover; Ascarina, cover; Asparagaceae, cover; Asphodelaceae, cover; Asteliaceae, cover; Asteraceae, cover; Astrotricha, cover; Atalaya, cover; Atherosperma, cover; Athrotaxis, cover; Austrobuxus, cover; Avicennia, cover; AWI_Envi; Baccaurea, cover; Baeckea, cover; Balanops, cover; Balsaminaceae, cover; BANDUNG2; Bandung DPDR-II; Banksia, cover; Barringtonia, cover; Basin; Bataceae, cover; Bauhinia, cover; Bedfordia, cover; BEGASWAM; Bega Swamp; Begoniaceae, cover; Beilschmiedia, cover; Beyeria, cover; Bignoniaceae, cover; BIGREEDY_Pollen; Bischofia, cover; BLACKSW_Pollen; BLUELAKE; Blue Lake; Bobea, cover; Bombax, cover; BONATOAB; Bonatoa Bog; Boraginaceae, cover; Bossiaea, cover; Brachychiton, cover; BRASS; Brassicaceae, cover; Brass Tarn; Breynia, cover; Bridelia, cover; Bruguiera, cover; BSP02_Pollen; Buchanania, cover; Buddleja, cover; Bursaria, cover; Cactaceae, cover; Calculated average/mean values; Calendar age, maximum/old; Calendar age, mean; Calendar age, median; Calendar age, minimum/young; Callitris, cover; Calocedrus, cover; Calophyllum, cover; Calytrix, cover; CAMERONS_Pollen; Campanulaceae, cover; Camptostemon, cover; Cannabaceae, cover; Canthium, cover; Capparaceae, cover; Capparis, cover; Caprifoliaceae, cover; Carallia, cover; Carpodetus, cover; Caryophyllaceae, cover; Cassia, cover; Castanopsis, cover; Casuarina, cover; Casuarinaceae, cover; CAVEBAYV78_Pollen; Ceiba, cover; Celastraceae, cover; Celtis, cover; Cenarrhenes, cover; Centrolepidaceae, cover; Cerberiopsis, cover; Charpentiera, cover; Cheirodendron, cover; Chionanthus, cover; Choretrum, cover; Claoxylon, cover; Cleidion, cover; Clerodendrum, cover; CLUBSM_Pollen; COBBCV1_Pollen; Cocos, cover; Codia, cover; Codonocarpus, cover; Colubrina, cover; Combretaceae, cover; Commelinaceae, cover; Commersonia, cover; Connaraceae, cover; Continent; Convolvulaceae, cover; Cordyline, cover; COREDC1; Coriariaceae, cover; Corymbia, cover; Corynocarpus, cover; COTTER_Pollen; Crassulaceae, cover; CRYLGN_Pollen; Cryptandra, cover; Cucurbitaceae, cover; Cunoniaceae, cover; Cupaniopsis, cover; Cupressaceae, cover; Cyclophyllum, cover; Cynometra, cover; Cyperaceae, cover; Dacrycarpus, cover; Dacrydium, cover; Daphniphyllum, cover; DARBY_Pollen; Data ID; Decaspermum, cover; DEPTH, sediment/rock; Diameter; Didymotheca, cover; Dillenia, cover; Dilleniaceae, cover; Dioscoreaceae, cover; Diospyros, cover; Discaria, cover; Distylium, cover; Dodonaea, cover; DOVE; Dove Lake; Dracophyllum, cover; Drimys, cover; DUKES; Dukes Tarn; Dysoxylum, cover; EA200; EA204; Eagle Tarn; EAGLTARN; Ebenaceae, cover; Ehretia, cover; Elaeagnus, cover; Elaeocarpaceae, cover; Elaeocarpus, cover; Elattostachys, cover; ELZ01_Pollen; Endospermum, cover; Engelhardia, cover; Epacridaceae, cover; Eremophila, cover; Ericales, cover; Eriostemon, cover; Erythrina, cover; Escalloniaceae, cover; Eucalyptus, cover; Eucryphia, cover; Eugenia, cover; Euodia, cover; Euphorbiaceae, cover; Event label; EWEBURN_Pollen; Excoecaria, cover; EXN62_Pollen; Exocarpos, cover; Fabaceae, cover; Fagraea, cover; Ficus, cover; Flindersia, cover; Forest, cover; fossil pollen; Frankeniaceae, cover; FRN02_Pollen; FROME_Pollen; Fuchsia, cover; Garcinia, cover; Gardenia, cover; Geniostoma, cover; Gentianaceae, cover; Geraniaceae, cover; Gesneriaceae, cover; Glochidion, cover; GOG; Goodeniaceae, cover; Granta Pools; Grevillea, cover; Griselinia, cover; GRNLGN_Pollen; Guettarda, cover; Guioa, cover; Gunneraceae, cover; Gymnostoma, cover; Gyrostemon, cover; Gyrostemonaceae, cover; Hakea, cover; Halocarpus, cover; HANLON_Pollen; Helicia, cover; Helicteres, cover; Heliotropium, cover; Heritiera, cover; Hernandiaceae, cover; Hibbertia, cover; Hoheria, cover; Homalanthus, cover; Homalium, cover; HORDORLI; HS78_Pollen; Hydrangeaceae, cover; Hypericaceae, cover; Hypoxidaceae, cover; Ijomba; IJOMBA; Ilex, cover; Indeterminable, cover; Indigofera, cover; Indopacific; Iridaceae, cover; Ixerba, cover; Ixora, cover; JACKSONB; Jacksons Bog; Juglandaceae, cover; Juglans, cover; Juncaceae, cover; KEALIA; Kealia Pond; KIRKPAT; Kleinhovia, cover; Knightia, cover; Kohuora_Pollen; Komanimambuno Mire; KOMANLO; Kunzea, cover; Lac Suprin; Lagarostrobos, cover; Lagerstroemia, cover; Lake George; Lake Hordorli; Lake Kirkpatrick; Lake Tagimaucia; Lake Vera; Lambertia, cover; Lamiaceae, cover; Lasiopetalum, cover; LATITUDE; Lauraceae, cover; Laurelia, cover; LC1B_Pollen; Lepidothamnus, cover; Leptecophylla, cover; Leptospermum, cover; Leucopogon, cover; LGEORGE; Libocedrus, cover; Liliaceae, cover; Liliales, cover; Linderniaceae, cover; Litsea, cover; LIZARD_Pollen; LKCARP_Pollen; Location ID; Loganiaceae, cover; Lomatia, cover; Lonchocarpus, cover; LONGITUDE; Lophomyrtus, cover; Loranthaceae, cover; LOWELAK_Pollen; Lumnitzera, cover; LYNCHA; LYNCHA74_Pollen; Lynchs Crater; Lythraceae, cover; Macaranga, cover; Maesa, cover; Mallotus, cover; Malpighiaceae, cover; Malvaceae, cover; Manoao, cover; Median values; Melaleuca, cover; Melastomataceae, cover; Melia, cover; Meliaceae, cover; Melicope, cover; Melicytus, cover; Meliosma, cover; Melochia, cover; Meryta, cover; Metrosideros, cover; Metroxylon, cover; MICALONG_Pollen; Mida, cover; Mimusops, cover; MODEWARRE_Pollen; Montiaceae, cover; Moraceae, cover; Morinda, cover; MP.LGN_Pollen; Myoporaceae, cover; Myoporum, cover; Myrica, cover; Myristica, cover; Myrsinaceae, cover; Myrsine, cover; Myrtaceae, cover; NADRAU; Nadrau Swamp; NATCOMLAG_Pollen; Nauclea, cover; NCE1998_Pollen; Neonauclea, cover; Neopanax, cover; Nestegis, cover; Nitrariaceae, cover; North America; Notelaea, cover; Nothocestrum, cover; Nothofagus, cover; Nyctaginaceae, cover; Octomeles, cover; Olea, cover; Oleaceae, cover; Onagraceae, cover; Opiliaceae, cover; Orchidaceae, cover; Orobanchaceae, cover; Oxalidaceae, cover; PADDYS; Paddys Lake; Palaquium, cover; paleoecology; Pandanaceae, cover; Pandanus, cover; Papuacedrus, cover; Parinari, cover; Passiflora, cover; Pemphis, cover; Pennantia, cover; Persoonia, cover; Pherosphaera, cover; Phrymaceae, cover; Phyllanthaceae, cover; Phyllocladus, cover; Phytolaccaceae, cover; Picea, cover; Picrodendraceae, cover; Pinaceae, cover; Pinus, cover; Piper, cover; Piperaceae, cover; Pipturus, cover; Pisonia, cover; Pittosporaceae, cover; Pittosporum, cover; Planchonia, cover; Plantaginaceae, cover; Plerandra, cover; Plumbaginaceae, cover; Poaceae, cover; Podocarpaceae, cover; Podocarpus, cover; Polar Terrestrial Environmental Systems @ AWI; Pollen, rel influx, median; Pollen, rel influx, standard deviation; Polygalaceae, cover; Polygonaceae, cover; Polyscias, cover; Pomaderris, cover; Pometia, cover; Portulacaceae, cover; Pouteria, cover; Primulaceae, cover; Pritchardia, cover; Prosopis, cover; Proteaceae, cover; Prumnopitys, cover; Prunus, cover; Pseudopanax, cover; Pseudowintera, cover; Psidium, cover; Psychotria, cover; Psydrax, cover; Quercus, cover; Quintinia, cover; Radius; RAIDA4; Rairua marsh; Randia, cover; Ranunculaceae, cover; Rapanea, cover; Reference/source; Restionaceae, cover; REVEALS; Rhamnaceae, cover; Rhizophora, cover; Rhopalostylis, cover; Rhus, cover; Ringarooma River; Ripogonaceae, cover; Rosaceae, cover; Rosales, cover; ROTTEN; Rotten Swamp; RR1; Rubiaceae, cover; Rumex, cover;
    Type: Dataset
    Format: text/tab-separated-values, 8796033 data points
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  • 8
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    Physical oceanography during Alkor cruise AL539 (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: This data set comprises raw CTD data collected during the RV ALKOR cruise AL539 conducted in July 2020 (July 5th to July 18th 2020) in the Western Baltic Sea by the University of Hamburg. The cruise was part of the 5-year MARSYS teaching cruise program of the University of Hamburg GFP20-1_047. The cruises are designed to train students in sampling methods targeting the different compartments of a marine ecosystem.
    Keywords: AL539; AL539_10-2; AL539_11-1; AL539_12-2; AL539_13-1; AL539_14-1; AL539_15-1; AL539_16-2; AL539_17-2; AL539_18-1; AL539_19-1; AL539_20-1; AL539_21-1; AL539_22-1; AL539_23-1; AL539_24-1; AL539_25-1; AL539_26-1; AL539_27-1; AL539_28-1; AL539_29-1; AL539_30-1; AL539_31-2; AL539_32-1; AL539_33-2; AL539_34-1; AL539_35-2; AL539_36-1; AL539_37-2; AL539_38-1; AL539_39-2; AL539_40-1; AL539_41-2; AL539_4-2; AL539_42-1; AL539_43-2; AL539_44-1; AL539_45-2; AL539_46-1; AL539_47-2; AL539_48-1; AL539_49-2; AL539_50-1; AL539_5-1; AL539_51-2; AL539_52-1; AL539_53-2; AL539_54-1; AL539_55-2; AL539_56-1; AL539_57-2; AL539_58-1; AL539_59-2; AL539_60-1; AL539_6-2; AL539_62-1; AL539_63-2; AL539_64-1; AL539_65-1; AL539_66-2; AL539_67-1; AL539_68-2; AL539_69-1; AL539_70-2; AL539_7-1; AL539_71-1; AL539_72-2; AL539_73-1; AL539_74-1; AL539_75-1; AL539_76-1; AL539_77-1; AL539_78-1; AL539_8-2; AL539_9-1; Alkor (1990); Baltic Sea; BONGO; Bongo net; Chlorophyll a; Conductivity; Cruise/expedition; CTD/Rosette; CTD-RO; DATE/TIME; Density, sigma-theta (0); DEPTH, water; Event label; Field measurements; LATITUDE; LONGITUDE; Multiparameter probe (CTD), Sea & Sun Technology, CTD90M [Series II]; coupled with Fluorometer, Turner Designs, Cyclops-7 [for Chlorphyll a]; coupled with Oxygen sensor, AMT Analysenmesstechnik GmbH; Oxygen, dissolved; Oxygen saturation; pH; Pressure, water; RV ALKOR; Salinity; Station label; summer; Teaching cruise; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 1017676 data points
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  • 9
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    Fish biomass data during Alkor cruise AL539 (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: This data set comprises all fish biomass data collected during the RV ALKOR cruise AL539 conducted in July 2020 (July 5th to July 18th 2020) in the Western Baltic Sea by the University of Hamburg. The cruise was part of the 5-year MARSYS teaching cruise program of the University of Hamburg GFP20-1_047. The fish biomass data were collected directly on board. Fish biomass was taken after sorting through a complete fish haul into the single species and weighing them on a scale on board. The amount of Scyphozoa was estimated at 500 kg.
    Keywords: AL539; AL539_16-1; AL539_17-1; AL539_18-2; AL539_19-2; AL539_20-2; AL539_21-2; AL539_22-2; AL539_2-3; AL539_23-2; AL539_24-2; AL539_25-2; AL539_26-2; AL539_4-3; AL539_73-2; AL539_74-2; AL539_75-2; AL539_76-2; AL539_77-2; AL539_78-2; Alkor (1990); Baltic Sea; Biomass, per catch; Cruise/expedition; CTD/Rosette; CTD-RO; DATE/TIME; DEPTH, water; Event label; Field measurements; fish; Gadus morhua; LATITUDE; Life stage; Location; LONGITUDE; RV ALKOR; Species; Station label; summer; Taxon/taxa, unique identification; Taxon/taxa, unique identification (Semantic URI); Taxon/taxa, unique identification (URI); Teaching cruise; Total counts, per catch; TRAWL; Trawl net
    Type: Dataset
    Format: text/tab-separated-values, 580 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 10
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    Seawater carbonate chemistry and photo-physiological fitness, growth and carbon production of the Antarctic cryptophyte Geminigera cryophila (2020)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Ecophysiological studies on Antarctic cryptophytes to assess whether climatic changes such as ocean acidification and enhanced stratification affect their growth in Antarctic coastal waters in the future are lacking so far. This is the first study that investigates the combined effects of the increasing availability of pCO2 (400 and 1000 μatm) and irradiance (20, 200 and 500 μmol photons m-2 s-1) on growth, elemental composition and photo-physiology of the Antarctic cryptophyte Geminigera cryophila. Under ambient pCO2, this species was characterized by a pronounced sensitivity to increasing irradiance with complete growth inhibition at the highest light intensity. Interestingly, when grown under high pCO2 this negative light effect vanished, and it reached the highest rates of growth and particulate organic carbon production at the highest irradiance compared to the other tested experimental conditions. Our results for G. cryophila reveal beneficial effects of ocean acidification in conjunction with enhanced irradiance on growth and photosynthesis. Hence, cryptophytes such as G. cryophila may be potential winners of climate change, potentially thriving better in more stratified and acidic coastal waters and contributing in higher abundance to future phytoplankton assemblages of coastal Antarctic waters.
    Keywords: Alkalinity, total; Aragonite saturation state; Bicarbonate ion; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calcite saturation state; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbon, organic, particulate, per cell; Carbon, organic, particulate, production per cell; Carbon, organic, particulate, standard deviation; Carbon/Nitrogen ratio; Carbon/Nitrogen ratio, standard deviation; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Chromista; Connectivity between photosystem II; Connectivity between photosystem II, standard deviation; Cryptophyta; Electron transport rate, absolute; Electron transport rate, absolute, standard deviation; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Functional absorption cross sections of photosystem II reaction centers; Functional absorption cross sections of photosystem II reaction centers, standard deviation; Functional photosystem II reaction centers, per cell; Functional photosystem II reaction centers, standard deviation; Geminigera cryophila; Growth/Morphology; Growth rate; Growth rate, standard deviation; Irradiance; Laboratory experiment; Laboratory strains; Light; Maximum photochemical quantum yield of photosystem II; Maximum photochemical quantum yield of photosystem II, standard deviation; Nitrogen, organic, particulate, per cell; Nitrogen, organic, particulate, per cell, standard deviation; Non photochemical quenching; Non photochemical quenching, standard deviation; Not applicable; Partial pressure of carbon dioxide, standard deviation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Particulate organic carbon, production, standard deviation; Particulate organic nitrogen production, standard deviation; Pelagos; pH; pH, standard deviation; Phytoplankton; Primary production/Photosynthesis; Production of particulate organic nitrogen; Recovery; Recovery, standard deviation; Registration number of species; Re-oxidation time of the Qa acceptor; Re-oxidation time of the Qa acceptor, standard deviation; Salinity; Single species; Species; Temperature, water; Type; Uniform resource locator/link to reference
    Type: Dataset
    Format: text/tab-separated-values, 2200 data points
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  • 11
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    Results of a 24-hour laboratory experiment sampling cell concentrations, particulate organic carbon (POC), particulate inorganic carbon (PIC) and further cell parameters of the coccolithophore Emiliania huxleyi grown under a 16:8 h light/dark cycle (2020)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Cell division of the coccolithophore Emiliania huxleyi and other phytoplankton typically becomes entrained to diel light/dark cycles under laboratory conditions, with division occurring primarily during dark phases and production occurring during light phases. Under these conditions, the increase in a culture's cell and biomass concentrations deviates from an exponential function on time scales 〈 24 h. We here present a dataset of short-term changes in cell and biomass concentrations of fast dividing, dilute-batch cultures of E. huxleyi grown under a 16:8 h light/dark cycle. This dataset was used to derive linear models describing the diel course in the concentrations of cells, particulate organic carbon (POC) and particulate inorganic carbon (PIC) and for the calculation of daily means of cellular quotas and production rates in Kottmeier et al. (2020). We also present the given seawater carbonate chemistry as well as cellular quotas of particulate organic nitrogen (PON) and chlorophyll a (Chl. a), and the ratios of PIC:POC, POC:PON, POC:cell volume and Chl. a:POC in the course of the 24 h sampling period.
    Keywords: 1; Alkalinity, potentiometric; Alkalinity, total; Alkalinity, total, standard deviation; Calculated using CO2SYS; Carbon, inorganic, dissolved; Carbon, inorganic, particulate, per cell; Carbon, inorganic, particulate, relative concentration; Carbon, organic, particulate; Carbon, organic, particulate, per cell; Carbon, organic, particulate, relative concentration; Carbon, organic, particulate/Nitrogen, organic, particulate ratio; Carbon dioxide, partial pressure; Carbon dioxide, partial pressure, standard deviation; Cell concentration, relative; Chlorophyll a/particulate organic carbon ratio; Chlorophyll a per cell; Colorimetric autoanalysis; Consumption of carbon, inorganic, dissolved, standard deviation; Coulter counter, Beckman Coulter, Multisizer 3; Elemental analyzer, EuroVector, EA 3000; Exponential growth; Fluorometer, Turner Design, TD-700; Growth rate; Growth rate, standard deviation; Hand net; HN; Identification; Irradiance; Light/dark cycles; Light meter; LM; Nitrogen, organic, particulate, per cell; Particulate inorganic carbon/particulate organic carbon ratio; pH; pH, standard deviation; Phase; Phased cell division; PIC production; POC production; Potentiometric; Registration number of species; Salinity; SALINO; Salinometer; SO136; SO136_006-A_HPN; Sonne; Species; Stage; Strain; TASQWA; Temperature, water; Temperature sensor; Time in hours; Treatment: light:dark cycle; Uniform resource locator/link to reference
    Type: Dataset
    Format: text/tab-separated-values, 1983 data points
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  • 12
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    n-alkane carbon and hydrogen stable isotope data from sediment core M125-95-3 (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: In order to assess the response of vegetation from eastern tropical South America to hydroclimate changes during the last ca. 45 kyr, we analyzed marine sediment core M125-95-3 that archived sediments from the São Francisco River drainage basin. We used the stable carbon (δ13C) and hydrogen (δD) isotopes of long-chain n-alkanes (i.e., C29-C31) to reconstruct regional vegetation composition and precipitation dynamics, respectively. The data set contains marine sedimentary records of long-chain n-alkane δ13C and δD, as well as the isotopic difference between homologues (Δδ13C31-29), and locally estimated scatterplot smoothing (LOESS) of indicated data. The δ13Cwax refers to the weighted averages of δ13C29 and δ13C31 values. The δDwax refers to the weighted averages of δD29 and δD31 values.
    Keywords: AGE; DEPTH, sediment/rock; Gas chromatography - Isotope ratio mass spectrometer (GC-IRMS); lipid biomarkers; M125; M125_469-3; M125-95-3; Meteor (1986); n-Alkane, Δδ13C (C31-C29); n-Alkane C29, δ13C; n-Alkane C29, δ13C, standard deviation; n-Alkane C29, δD; n-Alkane C29, δD, standard deviation; n-Alkane C31, δ13C; n-Alkane C31, δ13C, standard deviation; n-Alkane C31, δD; n-Alkane C31, δD, standard deviation; n-alkanes; off eastern South America; PC; Piston corer; SAMBA; São Francisco river; South Atlantic Ocean; Stable carbon and hydrogen isotopes of plant-waxes; stable carbon isotopes δ13C; stable hydrogen isotopes δ2H; δ13C, wax; δ13C, wax, standard deviation; δ Deuterium, wax; δ Deuterium, wax, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 745 data points
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  • 13
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    PALMOD 130k marine palaeoclimate data synthesis V1_0_1 (2020)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Updates since v1.0: no new sites, corrected minor errors and improved standardisation in metadata.
    Keywords: File format; File name; File size; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 12 data points
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  • 14
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    Raw pollen counts and pollen percentages quantified from sediment core MD96-2098 (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Pollen counts and percentages from marine core MD96-2098 (25°36′S, 12°38′E) in southwestern Africa spanning Marine Isotope Stage (MIS) 6 to 2. The core was sampled every 10 cm between 450 and 1940cm (uncorrected depth) for pollen analysis. The uncorrected depth did not take into account artificial gaps created during piston extraction (Bertrand et al., 1996). Depths were corrected to take into account these artificial sediment gaps. An age model was established for the record based on 16 marine isotope events (MIEs) from the Cibicidoides wuellerstorfi δ18O benthic record of MD96-2098 (Bertrand et al., 2002) and 14 accelerator mass spectrometer radiocarbon ages from mixed planktonic foraminifera extracted from MD96-2098 (Urrego et al 2015, Table S2 in the Supplement). Marine sediment samples from MD96-2098 were analysed under the microscope until a sum of at least 100 pollen grains excluding fern spores was reached. The pollen sequence from MD96-2098 covers the period between 24 and 190 thousand years before present and provides an integrated picture of past regional vegetation changes in southwestern Africa.
    Keywords: Acacia; Acanthaceae; AGE; Agulhas Current; Alchornea; Amaranthaceae; Andromischus; Anthospermum; Araceae; Artemisia-type; Asplenium; Asteraceae; Asteraceae-type; Benguela Current; Calculated; CALYPSO; Calypso Corer; Campanulaceae-type; Caryophyllaceae; Chenopodiaceae; Cliffortia; Combretum-type; Coniferaceae; Crassulaceae-type; Cyperaceae; Depth, corrected; Depth, uncorrected; Diodia; Disliptera; Elaphoglossum; Entandrophragma-type; Ericaceae; Euclea; Euphorbia; Ficus; Fynbos; Geraniaceae; Gunnera; IMAGES II; Isoetes; Lamiaceae; Liliaceae; Lüderitz Transect; Lycium; Lycopodium spike; marine; Marion Dufresne (1995); MD105; MD962098; MD96-2098; Megalochlamys/Justicia; Melastomataceae; Moraceae; Myrica; Myrsine; Nama-karoo/fine-leaved savanna; Number of spike added; Olea; Ophioglossum; Passerina; Pentzia-type; Plantago; Pluchea; Plumbaginaceae; Poaceae; Podocarpus; Pollen; Pollen, broken; Pollen, corroded; Pollen, crumpled; Pollen, hidden; Pollen, total; Pollen indeterminata; Polypodiaceae; Polypodium-type; Protea; Ranunculaceae-type; Raw counts; Restionaceae; Rhus-type; Rosaceae; Ruschia; Rutaceae; Sebaea; Solanum; Southern Africa; Spores, monolete psilate; Spores, monolete scabrate; Spores, trilete psilate; Spores, trilete reticulate; Spores indeterminata; Stoebe-type; Tamarix; Total concentration; Trema; Tribulus; Tribulus, pollen; Typha-type; Vernonia; Volume
    Type: Dataset
    Format: text/tab-separated-values, 29175 data points
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  • 15
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    Seawater carbonate chemistry and population-specific responses in physiological rates of Emiliania huxleyi to a broad CO2 range (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Although coccolithophore physiological responses to CO2-induced changes in seawater carbonate chemistry have been widely studied in the past, there is limited knowledge on the variability of physiological responses between populations from different areas. In the present study, we investigated the specific responses of growth, particulate organic (POC) and inorganic carbon (PIC) production rates of three populations of the coccolithophore Emiliania huxleyi from three regions in the North Atlantic Ocean (Azores: six strains, Canary Islands: five strains, and Norwegian coast near Bergen: six strains) to a CO2 partial pressure (pCO2) range from 120 to 2630 µatm. Physiological rates of each population and individual strain increased with rising pCO2 levels, reached a maximum and declined thereafter. Optimal pCO2 for growth, POC production rates, and tolerance to low pH (i.e., high proton concentration) was significantly higher in an E. huxleyi population isolated from the Norwegian coast than in those isolated near the Azores and Canary Islands. This may be due to the large environmental variability including large pCO2 and pH fluctuations in coastal waters off Bergen compared to the rather stable oceanic conditions at the other two sites. Maximum growth and POC production rates of the Azores and Bergen populations were similar and significantly higher than that of the Canary Islands population. This pattern could be driven by temperature–CO2 interactions where the chosen incubation temperature (16 °C) was slightly below what strains isolated near the Canary Islands normally experience. Our results indicate adaptation of E. huxleyi to their local environmental conditions and the existence of distinct E. huxleyi populations. Within each population, different growth, POC, and PIC production rates at different pCO2 levels indicated strain-specific phenotypic plasticity. Accounting for this variability is important to understand how or whether E. huxleyi might adapt to rising CO2 levels.
    Keywords: Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Azores_OA; Bicarbonate ion; Bicarbonate ion, standard deviation; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calcification/Dissolution; Calcite saturation state; Calcite saturation state, standard deviation; Calculated using CO2SYS; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbon, inorganic, particulate; Carbon, inorganic, particulate, per cell; Carbon, inorganic, particulate, production per cell; Carbon, organic, particulate; Carbon, organic, particulate, per cell; Carbon, organic, particulate, production per cell; Carbon, organic, particulate, standard deviation; Carbonate ion; Carbonate ion, standard deviation; Carbonate system computation flag; Carbon dioxide; Carbon dioxide, standard deviation; Chromista; Coast and continental shelf; Emiliania huxleyi; Event label; EXP; Experiment; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Gran_Canaria; Growth; Growth/Morphology; Growth rate; Growth rate, standard deviation; Haptophyta; Laboratory experiment; North Atlantic; OA-ICC; Ocean Acidification International Coordination Centre; Partial pressure of carbon dioxide, standard deviation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Particulate inorganic carbon, production, standard deviation; Particulate inorganic carbon/particulate organic carbon ratio; Particulate inorganic carbon/particulate organic carbon ratio, standard deviation; Particulate inorganic carbon per cell, standard deviation; Particulate organic carbon, production, standard deviation; Pelagos; pH; pH, standard deviation; Phytoplankton; Potentiometric; Potentiometric titration; Primary production/Photosynthesis; Raunefjord_OA; Salinity; Single species; Site; Species, unique identification; Species, unique identification (Semantic URI); Species, unique identification (URI); Strain; Temperate; Temperature, water; Type of study
    Type: Dataset
    Format: text/tab-separated-values, 9080 data points
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  • 16
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    Seawater carbonate chemistry and Phaeocystis pouchetii's responses to temperature (2 vs. 6 °C), light (55 vs. 160 µmol photons m-2 s-1) and pCO2 (400 vs. 1000 µatm) (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: We assessed the responses of solitary cells of Arctic Phaeocystis pouchetii (Strain PS78) grown under a matrix of temperature (2°C vs. 6°C), light intensity (55 vs. 160 μmol photons m-2 s-1) and CO2 partial pressures (pCO2; 400 vs. 1000 μatm). Before the experiments, the strain (isolated during Polarstern cruise PS78 in 2011) was kept as stock culture at 1° in 0.2 µm sterile-filtered Arctic seawater (Salinity 33), enriched with vitamins and trace metals according to F/2 medium (Guillard & Ryther, 1962). Nitrate and phosphate were added in concentrations of 100 and 6 µmol L-1, respectively. Experiments were conducted between May 2016 and September 2017 at the Alfred-Wegener-Institute, using standardized media and continuous light exposition. Next to acclimation parameters (growth rates, particulate and dissolved organic carbon and nitrogen, chlorophyll a content), we measured physiological processes in-vivo (electron transport rates and net photosynthesis) using fast-repetition rate fluorometry and membrane-inlet mass spectrometry. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2022) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2024-01-20.
    Keywords: Alkalinity, total; Aragonite saturation state; Arctic; Bicarbonate ion; Biomass/Abundance/Elemental composition; Bottle incubation; Bottles or small containers/Aquaria (〈20 L); Calcite saturation state; calculated from carbonate chemistry using the CO2Sys Excel sheet (Pierrot, Lewis & Wallace, 2006); calculated from chlorophyll a (chl a) and particulate organic carbon (POC) quota; calculated from growth rate and particulate organic carbon (POC) quota; calculated from growth rate and particulate organic nitrogen (PON) quota; calculated from particulate organic carbon (POC) and particulate organic nitrogen (PON) quota; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, organic, particulate, per cell; Carbon, organic, particulate, production per cell; Carbon, organic, particulate/Nitrogen, organic, particulate ratio; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Chlorophyll a/particulate organic carbon ratio; Chlorophyll a per cell; Chromista; Colorimetric detection, TRAACs continuous flow autoanalyzer, according to the method of Stoll et al. (2001); Coulter counter, Beckman Coulter, Multisizer 3; Date/time end; Date/time start; Electron transport rate, relative; Elemental analyzer, EuroVector, EuroEA; EXP; Experiment; Experimental treatment; Fitted parameter using the photosynthesis vs. Irradiance equation from Rokitta & Rost (2012), raw data obtained using a membrane-inlet mass spectrometer (MIMS) as described in Kottmeier, Rokitta & Rost (2016); Fitted parameter using the photosynthesis vs. Irradiance equation from Rokitta & Rost (2012); raw data obtained using a fast-repetition rate fluoremeter (FRRF), FastOcean PTX with FastAct Laboratory system, Chelsea Technologies after Oxborough et al. (201; Fluorometer, Turner Designs, TD-700, using acidification method (Knap et al., 1996); Fram Strait; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Growth rate; Haptophyta; Initial slope of the photosynthesis-irradiance curve, relative electron transfer rate per unit light; Laboratory experiment; Light; Light acclimation index; Maximum photosynthesis rate, oxygen, per chlorophyll a; Nitrogen, organic, particulate, per cell; OA-ICC; Ocean Acidification International Coordination Centre; Open ocean; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); pCO2 mixed from CO2-free air and pure CO2 with a custom built gas mixing system; Pelagos; pH; pH 826 mobile handheld device, with Aquatrode Plus, Metrohm; Phaeocystis_pouchetii_PS78; Phaeocystis pouchetii; Phytoplankton; Polar; Primary production/Photosynthesis; Production of particulate organic nitrogen; Replicate; Single species; Species, unique identification; Species, unique identification (Semantic URI); Species, unique identification (URI); Strain; Temperature; Temperature, water; Thermometer, internal, Aquatrode Plus, Metrohm; Treatment: light intensity; Treatment: partial pressure of carbon dioxide; Treatment: temperature; Type of study; Universal light meter & data logger, WALZ, ULM-500, with 4Pi sensor, LI-COR
    Type: Dataset
    Format: text/tab-separated-values, 1580 data points
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  • 17
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    Organic carbon stocks and accumulation rates on the Norwegian continental margin (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: The dataset contains digital maps of organic carbon stocks (kg m⁻²) relating to the upper ten centimetres of the sediment column and ²¹⁰Pb-based organic carbon accumulation rates (g m⁻² yr⁻¹) of sediments on the Norwegian continental margin including the North, Norwegian, and Barents Seas. The results are presented as geo-referenced floating-point TIFF-files with a spatial resolution of 4 km and Lambert Azimuthal Equal-Area projection as spatial reference. Stocks were calculated based on spatially predicted organic carbon content and dry bulk density. Accumulation rates were calculated based on spatially predicted organic carbon content, dry bulk density and sediment accumulation rates. All three spatial models also derived prediction uncertainties and areas of applicability of the model (Meyer & Pebesma, 2021). Uncertainties were propagated by taking the square root of the sum of squared relative uncertainties. Areas of applicability of the organic carbon stocks and accumulation rates were calculated by multiplying individual areas of applicability.
    Keywords: Barents Sea; Continental Margin; File content; Modeled; Model output, GeoTIFF format; Model output, GeoTIFF format (File Size); North Sea; Norwegian Margin; Norwegian Sea; OC_Norwegian_margin; Organic carbon (OC) burial; Organic carbon stock
    Type: Dataset
    Format: text/tab-separated-values, 12 data points
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  • 18
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    Seawater carbonate chemistry and growth and carbon fixation of Antarctic cryptophyte (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: We conducted a multiple-stressor experiment to evaluate the response of the still poorly studied key Antarctic cryptophyte species Geminigera cryophila (CCMP 2564, isolated from the Southern Ocean and obtained from Matt Johnson's Laboratory of Protistan Ecology at the Woods Hole Oceanography Institute, United States) to warming in combination with ocean acidification and high irradiance. Based on the thermal growth response of G. cryophila, we grew the cryptophyte at suboptimal (2°C) and optimal (4°C) temperatures in combination with two light intensities (medium light: 100 μmol photons/m**2/s and high light [HL]: 500 μmol photons/m**2/s) under ambient (400 μatm pCO2) and high pCO2 (1000 μatm pCO2) conditions.
    Keywords: Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Bicarbonate ion; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calculated using CO2SYS; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbon, organic, particulate, per cell; Carbon, organic, particulate, production per cell; Carbon, organic, particulate, standard deviation; Carbon/Nitrogen ratio; Carbon/Nitrogen ratio, standard deviation; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Carbon nitrogen elemental analyzer, EURO EA-CN Elemental Analyzer, HEKAtech GmbH; Chlorophyll a, standard deviation; Chlorophyll a per cell; Chlorophyll c2, standard deviation; Chlorophyll c2 per cell; Chromista; Cryptophyta; Electron transport rate, absolute; Electron transport rate, absolute, standard deviation; Fast Repetition Rate fluorometer (FRRF), FastOcean PTX; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Functional photosystem II reaction centers, per cell; Functional photosystem II reaction centers, standard deviation; Geminigera cryophila; Growth/Morphology; Growth rate; Growth rate, standard deviation; Irradiance; Laboratory experiment; Laboratory strains; Light; Maximum photochemical quantum yield of photosystem II; Maximum photochemical quantum yield of photosystem II, standard deviation; Not applicable; OA-ICC; Ocean Acidification International Coordination Centre; Partial pressure of carbon dioxide, standard deviation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Particulate organic carbon, production, standard deviation; Pelagos; pH; pH, standard deviation; Phosphate; Phytoplankton; Potentiometric; Potentiometric titration; Primary production/Photosynthesis; Re-oxidation time of the Qa acceptor; Re-oxidation time of the Qa acceptor, standard deviation; Reverse phase high performance liquid chromatography (HPLC), VWR-Hitachi International GmbH; Salinity; Silicate; Single species; Species, unique identification; Species, unique identification (Semantic URI); Species, unique identification (URI); Temperature; Temperature, water; Time in weeks; Treatment: light intensity; Treatment: partial pressure of carbon dioxide; Treatment: temperature; Type of study
    Type: Dataset
    Format: text/tab-separated-values, 3288 data points
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  • 19
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    Physical oceanography during Alkor cruise AL540 (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: This data set comprises raw CTD data collected during the RV ALKOR cruise AL540 conducted in July 2020 (July 21st to July 31st 2020) in the Western Baltic Sea by the University of Hamburg. The cruise was part of the 5-year MARSYS teaching cruise program of the University of Hamburg GFP20-1_047. The cruises are designed to train students in sampling methods targeting the different compartments of a marine ecosystem.
    Keywords: AL540; AL540_10-1; AL540_1-1; AL540_11-2; AL540_12-1; AL540_13-1; AL540_14-2; AL540_15-1; AL540_16-1; AL540_17-2; AL540_18-1; AL540_19-2; AL540_20-1; AL540_21-2; AL540_2-2; AL540_22-1; AL540_23-2; AL540_24-1; AL540_25-2; AL540_26-1; AL540_27-1; AL540_28-2; AL540_29-1; AL540_30-2; AL540_3-1; AL540_31-1; AL540_32-1; AL540_34-2; AL540_35-1; AL540_36-2; AL540_37-1; AL540_38-1; AL540_39-1; AL540_40-1; AL540_40-2; AL540_42-2; AL540_43-1; AL540_5-2; AL540_6-1; AL540_7-5; AL540_8-1; AL540_9-2; Alkor (1990); Baltic Sea; Chlorophyll a; Conductivity; Cruise/expedition; CTD/Rosette; CTD-RO; DATE/TIME; Density, sigma-theta (0); DEPTH, water; Event label; Field measurements; GPF 19-2_026; LATITUDE; LONGITUDE; MSN; Multiparameter probe (CTD), Sea & Sun Technology, CTD90M [Series II]; coupled with Fluorometer, Turner Designs, Cyclops-7 [for Chlorphyll a]; coupled with Oxygen sensor, AMT Analysenmesstechnik GmbH; Multiple opening/closing net; Oxygen, dissolved; Oxygen saturation; pH; Pressure, water; RV ALKOR; Salinity; Station label; summer; Teaching cruise; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 380523 data points
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  • 20
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    Organic-walled dinoflagellate cyst of sediment core GeoB4223-1 (2020)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: Agadir Canyon; Age; AGE; Ataxiodinium choane; Bitectatodinium tepikiense; Brigantedinium spp.; Center for Marine Environmental Sciences; Counting, palynology; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Dinoflagellate cyst; Dinoflagellate cyst indeterminata; Dubridinium spp.; Echinidinium aculeatum; Echinidinium delicatum; Echinidinium granulatum; Echinidinium spp.; Echinidinium transparantum; Echinidinium zonneveldiae; GeoB4223-1; Gymnodinium nolleri; Impagidinium aculeatum; Impagidinium paradoxum; Impagidinium patulum; Impagidinium plicatum; Impagidinium sphaericum; Impagidinium spp.; Impagidinium strialatum; Impagidinium variaseptum; Lejeunecysta oliva; Lejeunecysta paratenella; Lejeunecysta sabrina; Lejeunecysta spp.; Lingulodinium machaerophorum; M37/1; Marker, added; Marker, found; MARUM; Mass; Meteor (1986); MUC; MultiCorer; Nematosphaeropsis labyrinthus; Operculodinium centrocarpum; Operculodinium israelianum; Pentapharsodinium dalei; Polykrikos kofoidii; Polykrikos schwartzii; Polysphaeridium zoharyi; Protoperidinium americanum; Protoperidinium monospinum; Quinquecuspis concreta; Selenopemphix nephroides; Selenopemphix quanta; Selenopemphix sp.; Spiniferites bentori; Spiniferites elongatus; Spiniferites hyperacanthus; Spiniferites membranaceus; Spiniferites mirabilis; Spiniferites ramosus; Spiniferites spp.; Stelladinium robustum; Trinovantedinium applanatum; Votadinium calvum; Votadinium spinosum; Xandarodinium xanthum
    Type: Dataset
    Format: text/tab-separated-values, 1320 data points
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  • 21
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    Thermoluminescence of marine sediment core GL-1248 (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: DEPTH, sediment/rock; GL1248; GL-1248; Luminescence sensitivity; northeastern Brazil; precipitation reconstruction; quartz grains; South America; Thermoluminescence
    Type: Dataset
    Format: text/tab-separated-values, 153 data points
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  • 22
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    Brazil Current sea surface temperature compilation since the Last Glacial Maximum (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: AGE; Age, 14C calibrated, CALIB 8.2 and Marine20 calibration curve; Age, 14C calibrated, CALIB 8.2 and Marine20 calibration curve plus regional reservoir error; Age, standard deviation; AMOC; Brazil Current; interpolated; last deglaciation; North Brazil Current; Sea surface temperature, anomaly; Sea surface temperature, anomaly, standard deviation; South Atlantic
    Type: Dataset
    Format: text/tab-separated-values, 1440 data points
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  • 23
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    Sea surface temperature stack for the Brazilian margin from the Last Glacial Maximum to the Holocene (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: The number of sea surface temperature reconstructions from the Brazilian margin has grown through the last years, but with the surge of new records it has been turn difficult to explain individual data variability. In order to overcome this difficult and understant the evolution of surface temperature across the entire Brazilian margin from the Last Glacial Maximum to the Holocene, we propose a SST-stack based on Mg/Ca of surface-dwelling planktic foraminifera. The data display the temperature reduction during the LGM and the amplitude and timing of major SST increase across the last deglaciation. Interesting insights also emerge from the Holocene, with a SST decline from the late Holocene towards the present likely related to global volcanic activity. Published Mg/Ca-derived sea surface temperature for the Brazilian Margin were compiled. The age models from different studies were all transferred to Marine20 radiocarbon calibration and final probabilistic age model for each core was provided by Bacon. The Mg/Ca calibration from different studies were all transferred to the recent calibration of Gray and Evans (2019; doi:10.1029/2018PA003517). The new sea surface temperature (anomalies) and ages for each record were interpolated to a resolution of 0.4 ka and the data was grouped. Finally, a 1000-year window bootstrap smoothing with the robust LOWESS method and 2000 Monte Carlo simulations using the Acycle software to remove high-frequency variabilities.
    Keywords: AMOC; Brazil Current; last deglaciation; North Brazil Current; South Atlantic
    Type: Dataset
    Format: application/zip, 5 datasets
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  • 24
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    Carbon compounds, methane concentration and nutritional composition of water samples along the Elbe to the North Sea (German Bight) during the MOSES projects' Sternfahrt 9 in 2022 (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: The "Sternfahrt 9" cruise was conducted from the 30th of May to the 2nd of June 2022, covering a late spring situation in the German Bight. The three participating vessels (Littorina, Uthörn and Ludwig Prandtl) covered a wide range from 7.6°E to 8.9°E and from 53.5°N to 54.8°N, following similar tracks and sampling stations like those of the "Sternfahrt 5" in September 2020. Objective of this cruise was to get new insights on the chemical transformation of Chlorophyll-a and dissolved organic matter from the Elbe, Tide-Elbe and North Sea. Therefore, each ship was continuously measuring different hydrographic parameters and greenhouse gases along their tracks (not included in the present dataset, please see article(s) 'related to'). Additionally, each day eight stations were run by the crews along their respective track (for a more detailed description see 'file description'). Thus, delivering discrete water samples for later analyses of DIC, TA, DOC, methane, nutrients and explosive metals. Due to partly bad weather not always all stations could be realized. While the vessel Littorina covered the south eastern part of the German Bight, the Ludwig Prandtl went further North until the small island Amrum. The Uthörn instead sampled on one side in the north of Heligoland and on the other side in the south and south-west towards Cuxhaven (see map in 'additional metadata'). For more detailed information about the MOSEShx campaign and the cruise Sternfahrt 9, see article cited in references.
    Keywords: 2022_MOSES_Elbe-NorthSea; 2022_MOSES_Elbe-NorthSea_KON1; 2022_MOSES_Elbe-NorthSea_L1; 2022_MOSES_Elbe-NorthSea_UT1; Alfred-Wegener-Institute; Alkalinity, total; Ammonium; Carbon, organic, dissolved; Carbon, organic, particulate; Carbon cycle; Chlorophyll a; chlorophyll-a; DATE/TIME; DEPTH, water; DOC; Elbe; Event label; Geomar; German Bight; Helgoland; Hereon; KON_stern_9_P-1; KON_stern_9_P-10; KON_stern_9_P-11; KON_stern_9_P-12; KON_stern_9_P-13; KON_stern_9_P-14; KON_stern_9_P-15; KON_stern_9_P-16; KON_stern_9_P-17; KON_stern_9_P-18; KON_stern_9_P-19; KON_stern_9_P-2; KON_stern_9_P-20; KON_stern_9_P-21; KON_stern_9_P-22; KON_stern_9_P-23; KON_stern_9_P-24; KON_stern_9_P-25; KON_stern_9_P-26; KON_stern_9_P-27; KON_stern_9_P-3; KON_stern_9_P-4; KON_stern_9_P-5; KON_stern_9_P-6; KON_stern_9_P-7; KON_stern_9_P-8; KON_stern_9_P-9; L-01; L-02; L-03; L-04; L-05; L-06; L-07; L-08; L-09; L-10; L-11; L-12; L-13; L-14; L-15; L-16; L-17; L-18; L-19; L-20; L-21; L-22; L22_stern_9_L-01; L22_stern_9_L-02; L22_stern_9_L-03; L22_stern_9_L-04; L22_stern_9_L-05; L22_stern_9_L-06; L22_stern_9_L-07; L22_stern_9_L-08; L22_stern_9_L-09; L22_stern_9_L-10; L22_stern_9_L-11; L22_stern_9_L-12; L22_stern_9_L-13; L22_stern_9_L-14; L22_stern_9_L-15; L22_stern_9_L-16; L22_stern_9_L-17; L22_stern_9_L-18; L22_stern_9_L-19; L22_stern_9_L-20; L22_stern_9_L-21; L22_stern_9_L-22; L22_stern_9_L-23; L22_stern_9_L-24; L-23; L-24; LATITUDE; Littorina; LONGITUDE; Ludwig Prandtl; Methane; Modular Observation Solutions for Earth Systems; MOSES; Name; Nitrate; Nitrite; Nitrogen, organic, total; Nitrogen, total dissolved; Nitrogen oxide; North Sea; nutrients; P-1; P-10; P-11; P-12; P-13; P-14; P-15; P-16; P-17; P-18; P-19; P-2; P-20; P-21; P-22; P-23; P-24; P-25; P-26; P-27; P-3; P-4; P-5; P-6; P-7; P-8; P-9; Phosphate; POC; Principal investigator; Silicate; Station label; TA alkalinity; Tide Elbe; U1; U10; U11; U12; U13; U14; U15; U16; U17; U18; U19; U2; U20; U21; U22; U23; U24; U25; U26; U27; U28; U29; U3; U4; U5; U6; U7; U8; U9; UT2022_stern_9_U-1; UT2022_stern_9_U-10; UT2022_stern_9_U-11; UT2022_stern_9_U-12; UT2022_stern_9_U-13; UT2022_stern_9_U-14; UT2022_stern_9_U-15; UT2022_stern_9_U-16; UT2022_stern_9_U-17; UT2022_stern_9_U-18; UT2022_stern_9_U-19; UT2022_stern_9_U-2; UT2022_stern_9_U-20; UT2022_stern_9_U-21; UT2022_stern_9_U-22; UT2022_stern_9_U-23; UT2022_stern_9_U-24; UT2022_stern_9_U-25; UT2022_stern_9_U-26; UT2022_stern_9_U-27; UT2022_stern_9_U-28; UT2022_stern_9_U-29; UT2022_stern_9_U-3; UT2022_stern_9_U-4; UT2022_stern_9_U-5; UT2022_stern_9_U-6; UT2022_stern_9_U-7; UT2022_stern_9_U-8; UT2022_stern_9_U-9; Uthörn; Water sample; Water samples; WS
    Type: Dataset
    Format: text/tab-separated-values, 1127 data points
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  • 25
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    Quartz thermoluminescence sensitivity, optically stimulated luminescence sensitivity, and infrared stimulated luminescence/optically stimulated luminescence measurements from marine sediment core GL-1248 (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: AGE; DEPTH, sediment/rock; GL1248; GL-1248; Infrared stimulation light/Optically stimulated luminescence ratio; Infrared stimulation light/Optically stimulated luminescence ratio, standard deviation; Luminescence sensitivity; northeastern Brazil; Optically stimulated luminescence; Optically stimulated luminescence, standard deviation; precipitation reconstruction; quartz grains; South America; Thermoluminescence; Thermoluminescence, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 922 data points
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  • 26
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    Normalized quartz thermoluminescence (TL80–120) sensitivity of the 110°C peak from sediment cores GeoB16206-1/GL-1248 composite record (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: 057-1; AGE; AMADEUS; Continental Slope Northeast Brazil; GeoB16206-1; GL1248; GL-1248; Gravity corer (Kiel type); Luminescence sensitivity; Maria S. Merian; MSM20/3; northeastern Brazil; precipitation reconstruction; quartz grains; SL; South America; Thermoluminescence, normalized; Thermoluminescence, normalized, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 452 data points
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  • 27
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    Raw SST data for the full BR SST stack (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: 053-2; 087-1; AGE; Age, 14C calibrated, CALIB 8.2 and Marine20 calibration curve; AMADEUS; AMOC; Argentine Basin; Brazil Current; Cabo Frio Upwelling, Southwest Atlantic; Calculated after Gray and Evans, 2019; CF10-01B; Continental Slope Northeast Brazil; Core; CORE; DEPTH, sediment/rock; Event label; French Guiana; GC; GeoB16202-2; GeoB16224-1; GeoB3129-1; GeoB3911-1; GeoB6211-1; GeoB6211-2; GGC; Giant gravity corer; GL1090; GL-1090; GL1180; GL-1180; GL1248; GL-1248; Gravity corer; Gravity corer (Kiel type); JOPSII-6; JPC17; KN159-5; Knorr; KNR159-5; KNR159-5-36GGC; last deglaciation; Latitude of event; Longitude of event; M125; M125_428-3; M125_445-7; M125_469-3; M125-35-3; M125-55-7; M125-95-3; M34/4; M46/2; Maria S. Merian; Meteor (1986); MSM20/3; MUC; MultiCorer; NE-Brazilian continental margin; North Brazil Current; Northeast Brasilian Margin; Paleoprod; PC; PC-7610; PC-7616; Piston corer; Prof W Besnard; SAMBA; Sea surface temperature; Sea surface temperature, standard deviation; SL; South Atlantic; South Atlantic Ocean; South Brazil Bight, Santos Basin; Victor Hensen; western South Atlantic; western tropical Atlantic
    Type: Dataset
    Format: text/tab-separated-values, 5690 data points
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  • 28
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    Summary of Bayesian onset detection algorithm for abrupt warming transitions in the NGRIP record: depth (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Summary statistics of posterior marginal distribution of the onset of abrupt warming transitions located in the last glacial age of the NGRIP record, based on both the d18O and Ca2+ proxy. Includes both statistics for the onset depth as well as age transition. Onset depth is found by applying a linear ramp function (Erhardt et al. 2019) which is combined with a probabilistic age-depth model to infer the onset age of the transition.
    Keywords: Abrupt Warming; Bayesian; DEPTH, ice/snow; Greenland; Ice core; ICEDRILL; Ice drill; NGRIP; NorthGRIP; onset; Sample ID; Sampling/drilling ice; Summary; TiPES; Tipping Points in the Earth System; transition
    Type: Dataset
    Format: text/tab-separated-values, 29 data points
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  • 29
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    Summary of Bayesian onset detection algorithm for abrupt warming transitions in the NGRIP record: age (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Summary statistics of posterior marginal distribution of the onset of abrupt warming transitions located in the last glacial age of the NGRIP record, based on both the d18O and Ca2+ proxy. Includes both statistics for the onset depth as well as age transition. Onset depth is found by applying a linear ramp function (Erhardt et al. 2019) which is combined with a probabilistic age-depth model to infer the onset age of the transition.
    Keywords: Abrupt Warming; Age; Bayesian; Greenland; Ice core; ICEDRILL; Ice drill; NGRIP; NorthGRIP; onset; Sample ID; Sampling/drilling ice; Summary; TiPES; Tipping Points in the Earth System; transition
    Type: Dataset
    Format: text/tab-separated-values, 203 data points
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  • 30
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    Seawater carbonate chemistry and physiology and functional gene expression of the coccolithophore Emiliania huxleyi (2020)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Here, we examined two-way and multiple driver effects of ocean acidification and other key environmental drivers - nitrate, phosphate, irradiance, and temperature - on the growth, photosynthetic and calcification rates, and the elemental composition of E. huxleyi. In addition, changes in functional gene expression were examined to understand the molecular mechanisms underpinning the physiological responses. The single driver manipulation experiments sugguest decreased nitrate supply being the most important driver regulating E. huxleyi physiology, by significantly reducing the growth, photosynthetic and calcification rates. In addition, the interaction of ocean acidification and decreased nitrate supply (projected for year 2100) had more negative synergistic effects on E. huxleyi physiology than all other two-way factorial manipulations, suggesting a linkage between the single dominant driver (nitrate) effects and interactive effects with other drivers. Simultaneous manipulation of all five environmental drivers to the projected year 2100 conditions had the largest negative effects on most of the physiological metrics. Furthermore, functional genes associated with inorganic carbon acquisition (RubisCO, AEL1 and delta CA) and calcification (CAX3, AEL1, PATP and NhaA2) were most down-regulated by the multiple driver manipulation, revealing linkages between responses of functional gene expression and associated physiological metrics.
    Keywords: Alkalinity, total; Aragonite saturation state; Bicarbonate ion; Biomass/Abundance/Elemental composition; Bottle number; Bottles or small containers/Aquaria (〈20 L); Calcification/Dissolution; Calcification rate of carbon per cell; Calcite saturation state; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, particulate, per cell; Carbon, organic, particulate, per cell; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Chlorophyll a per cell; Chromista; Emiliania huxleyi; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Gene expression, fold change, relative; Gene expression, fold change, relative, standard deviation; Gene expression (incl. proteomics); Growth/Morphology; Growth rate; Haptophyta; Laboratory experiment; Laboratory strains; Light; Macro-nutrients; Net photosynthesis rate, per cell; Nitrogen, organic, particulate, per cell; Not applicable; OA-ICC; Ocean Acidification International Coordination Centre; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Pelagos; pH; Phosphorus, organic, particulate, per cell; Phytoplankton; Primary production/Photosynthesis; Ratio; Registration number of species; Salinity; Single species; Species; Temperature; Temperature, water; Treatment; Type; Uniform resource locator/link to reference
    Type: Dataset
    Format: text/tab-separated-values, 776 data points
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  • 31
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    Seawater carbonate chemistry and growth and particulate organic nitrogen production of diatom Thalassiosira pseudonana (2020)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Phytoplankton in the upper oceans are exposed to changing light levels due to mixing, diurnal solar cycles and weather conditions. Consequently, effects of ocean acidification are superimposed upon responses to variable light levels. We therefore grew a model diatom Thalassiosira pseudonana under either constant or variable light but at the same daily photon dose, with current low (400 μatm, LC) and future high CO2 (1000 μatm, HC) treatments. Variable light, compared with the constant light regime, decreased the growth rate, Chl a, Chl c, and carotenoid contents under both LC and HC conditions. Cells grown under variable light appeared more tolerant of high light as indicated by higher maximum relative electron transport rate and saturation light. Light variation interacted with high CO2/lowered pH to decrease the carbon fixation rate, but increased particulate organic carbon (POC) and particularly nitrogen (PON) per cell, which drove a decrease in C/N ratio, reflecting changes in the efficiency of energy transfer from photo-chemistry to net biomass production. Our results imply that elevated pCO2 under varying light conditions can lead to less primary productivity but more PON per biomass of the diatom, which might improve the food quality of diatoms and thereby influence biogeochemical nitrogen cycles.
    Keywords: Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Aragonite saturation state, standard deviation; Bicarbonate ion; Bicarbonate ion, standard deviation; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calcite saturation state; Calcite saturation state, standard deviation; Calculated using CO2SYS; Calculated using seacarb after Nisumaa et al. (2010); Calculated using seacarb after Orr et al. (2018); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbon, organic, particulate; Carbon, organic, particulate, per cell; Carbon, organic, particulate, production per cell; Carbon, organic, particulate, standard deviation; Carbon/Nitrogen ratio; Carbon/Nitrogen ratio, standard deviation; Carbonate ion; Carbonate ion, standard deviation; Carbonate system computation flag; Carbon dioxide; Carbon dioxide, standard deviation; Carbon fixation rate; Carbon fixation rate, standard deviation; Carotenoids, intracellular; Carotenoids, standard deviation; Carotenoids/Chlorophyll a ratio; Carotenoids/Chlorophyll a ratio, standard deviation; Carotenoids per cell; Cell size; Cell size, standard deviation; Chlorophyll a, intracellular; Chlorophyll a, standard deviation; Chlorophyll a per cell; Chlorophyll c, intracellular; Chlorophyll c, standard deviation; Chlorophyll c per cell; Chromista; Effective quantum yield; Effective quantum yield, standard deviation; Electron transport rate, relative; Electron transport rate, relative, standard deviation; Electron transport rate efficiency; Electron transport rate efficiency, standard deviation; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Fugacity of carbon dioxide in seawater, standard deviation; Growth/Morphology; Growth rate; Growth rate, standard deviation; Irradiance; Laboratory experiment; Laboratory strains; Light; Light saturation point; Light saturation point, standard deviation; Maximal electron transport rate, relative; Maximal electron transport rate, relative, standard deviation; Nitrogen, organic, particulate; Nitrogen, organic, particulate, per cell; Not applicable; OA-ICC; Ocean Acidification International Coordination Centre; Ochrophyta; Partial pressure of carbon dioxide, standard deviation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Particulate organic carbon, production, standard deviation; Particulate organic nitrogen, standard deviation; Particulate organic nitrogen production, standard deviation; pH; pH, standard deviation; Phytoplankton; Primary production/Photosynthesis; Production of particulate organic carbon; Production of particulate organic nitrogen; Registration number of species; Salinity; Single species; Species; Temperature, water; Thalassiosira pseudonana; Time of day; Total carbon fixation per cell per hour; Treatment; Type; Uniform resource locator/link to reference
    Type: Dataset
    Format: text/tab-separated-values, 2936 data points
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  • 32
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    Seawater carbonate chemistry and growth rates, carbon utilization and the internal pH regulation at the site of calcification in Emiliania huxleyi, Calcidiscus leptoporus and Pleurochrysis (2021)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Ocean acidification (OA) appears to have diverse impacts on calcareous coccolithophores, but the cellular processes underlying these responses are not well understood. Here we use stable boron and carbon isotopes, B/Ca ratios, as well as inorganic and organic carbon production rates to investigate the carbon utilization and the internal pH regulation at the site of calcification in Emiliania huxleyi, Pleurochrysis carterae and Calcidiscus leptoporus cultured over a wide pCO2 range (180 to 1000 μatm). Despite large variability, the geochemistry data indicate species-specific modes of pH control and differences in the utilization of inorganic carbon. Boron isotope data suggest that all three species generally upregulate the pH of the calcification fluid (pHCF) compared to surrounding seawater, which coincides with relatively constant growth rates and cellular ratios of inorganic to organic carbon. Furthermore, species exhibit different strategies in regulating their pHCF, i.e., two species maintain homeostasis (pHCF = ∼ 8.7), while one species shows a constant offset to the surrounding seawater (ΔpH = ∼0.6 units) over the entire tested pCO2 range. In addition to these different strategies, carbon isotope data suggests that high plasticity in the utilization of dissolved inorganic carbon might be an explanation for species-specific differences in coccolithophore responses to OA.
    Keywords: Acid-base regulation; Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Bicarbonate ion; Biomass/Abundance/Elemental composition; Boron/Calcium ratio; Boron/Calcium ratio, standard deviation; Bottles or small containers/Aquaria (〈20 L); Calcidiscus leptoporus; Calcification/Dissolution; Calcifying fluid, pH; Calcifying fluid, pH, standard deviation; Calcite saturation state; Calculated using CO2SYS; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbon, inorganic, particulate, per cell; Carbon, inorganic, particulate, production per cell; Carbon, organic, particulate, per cell; Carbon, organic, particulate, production per cell; Carbon, organic, particulate, standard deviation; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Chromista; Difference δ13C, particulate inorganic carbon and dissolved inorganic carbon; Difference δ13C, particulate inorganic carbon and dissolved inorganic carbon, standard deviation; Difference δ13C, particulate organic carbon and dissolved inorganic carbon; Difference δ13C, particulate organic carbon and dissolved inorganic carbon, standard deviation; Emiliania huxleyi; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Growth/Morphology; Growth rate; Growth rate, standard deviation; Haptophyta; Identification; Iron/Calcium ratio; Iron/Calcium ratio, standard deviation; Laboratory experiment; Laboratory strains; Magnesium/Calcium ratio; Magnesium/Calcium ratio, standard deviation; Not applicable; OA-ICC; Ocean Acidification International Coordination Centre; Other studied parameter or process; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Particulate inorganic carbon/particulate organic carbon ratio; Particulate inorganic carbon/particulate organic carbon ratio, standard deviation; Particulate inorganic carbon per cell, standard deviation; Pelagos; pH; pH, difference; pH, difference, standard deviation; pH, standard deviation; Phytoplankton; Pleurochrysis carterae; Potentiometric; Potentiometric titration; Primary production/Photosynthesis; Registration number of species; Salinity; Single species; Species; Temperature, water; Temperature, water, standard deviation; Type; Uniform resource locator/link to reference; δ11B; δ11B, standard deviation; δ13C, dissolved inorganic carbon; δ13C, dissolved inorganic carbon, standard deviation; δ13C, particulate inorganic carbon; δ13C, particulate inorganic carbon, standard deviation; δ13C, particulate organic carbon; δ13C, particulate organic carbon, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 1945 data points
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  • 33
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    Seawater carbonate chemistry and physiological parameters of Thalassiosira sp. and Nitzschia closterium f.minutissima (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Marine diatoms are one of the marine phytoplankton functional groups, with high species diversity, playing important roles in the marine food web and carbon sequestration. In order to evaluate the species-specific responses of coastal diatoms to the combined effects of future ocean acidification (OA) and warming on the coastal diatoms, we conducted a semi-continuous incubation on the large centric diatom Thalassiosira sp. (~30 μm) and small pennate diatom Nitzschia closterium f.minutissima (~15 μm). A full factorial combination of two temperature levels (15 and 20°C) and pCO2 (400 and 1,000 ppm) was examined. The results suggest that changes in temperature played a more important role in regulating the physiology of Thalassiosira sp. and N. closterium f.minutissima than CO2. For Thalassiosira sp., elevated temperature significantly reduced the cellular particulate organic carbon (POC), particulate organic nitrogen (PON), particulate organic phosphate (POP), biogenic silica (BSi), chlorophyll a (Chl a), and protein contents, and the C:N ratio. CO2 only had significant effects on the growth rate and the protein content. However, for the smaller pennate diatom N. closterium f.minutissima, the growth rate, POC production rate, and the C:P ratio significantly increased with an elevated temperature, whereas the cellular POP and BSi contents significantly decreased. CO2 had significant effects on the POC production rate, cellular BSi, POC, and PON contents, the C:P, Si:C, N:P, and Si:P ratios, and sinking rate. The interaction between OA and warming showed mostly antagonistic effects on the physiology of both species. Overall, by comparison between the two species, CO2 played a more significant role in regulating the growth rate and sinking rate of the large centric diatom Thalassiosira sp., whereas had more significant effects on the elemental compositions of the smaller pennate diatom N. closterium f.minutissima. These results suggest differential sensitivities of different diatom species with different sizes and morphology to the changes in CO2/temperature regimes and their interactions.
    Keywords: Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Beidou; Bicarbonate ion; Bicarbonate ion, standard deviation; Biogenic silica, per cell; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calcite saturation state; Calculated using seacarb after Nisumaa et al. (2010); Carbohydrates, per cell; Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbon, organic, dissolved; Carbon, organic, particulate, per cell; Carbon, organic, particulate, production per cell; Carbon/Nitrogen ratio; Carbon/Phosphorus ratio; Carbon/Silicon ratio; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Cell size; Chlorophyll a per cell; Chromista; Coast and continental shelf; EXP; Experiment; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Growth/Morphology; Growth rate; Laboratory experiment; Nitrogen, organic, particulate, per cell; Nitrogen/Phosphorus ratio; Nitzschia closterium f.minutissima; North Pacific; OA-ICC; Ocean Acidification International Coordination Centre; Ochrophyta; Other studied parameter or process; Partial pressure of carbon dioxide, standard deviation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Pelagos; pH; pH, standard deviation; Phosphorus, organic, particulate, per cell; Phytoplankton; Protein per cell; Salinity; Silicon/Phosphorus ratio; Single species; Sinking velocity; Species; Temperate; Temperature; Temperature, water; Thalassiosira sp.; Treatment; Type
    Type: Dataset
    Format: text/tab-separated-values, 983 data points
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  • 34
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    Seawater carbonate chemistry and lipid content, particulate organic carbon/nitrogen, growth rate, and morphology of Emiliania huxleyi (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Coccolithophores are a calcifying unicellular phytoplankton group that are at the base of the marine food web, and their lipid content provides a source of energy to consumers. Coccolithophores are vulnerable to ocean acidification and warming, therefore it is critical to establish the effects of climate change on these significant marine primary producers, and determine potential consequences that these changes can have on their consumers. Here, we quantified the impact of changes in pH and temperature on the nutritional condition (lipid content, particulate organic carbon/nitrogen), growth rate, and morphology of the most abundant living coccolithophore species, Emiliania huxleyi. We used a regression type approach with nine pH levels (ranging from 7.66 to 8.44) and two temperatures (15°C and 20°C). Lipid production was greater under reduced pH, and growth rates were distinctly lower at 15°C than at 20°C. The production potential of lipids, which estimates the availability of lipids to consumers, increased under 20°C, but decreased under low pH. The results indicate that, while consumers will benefit energetically under ocean warming, this benefit will be mitigated by ocean acidification. The carbon to nitrogen ratio was higher at 20°C and low pH, indicating that the nutritional quality of coccolithophores for consumers will decline under climate change. The impact of low pH on the structural integrity of the coccosphere may also mean that coccolithophores are easier to digest for consumers. Many responses suggest cellular stress, indicating that increases in temperature and reductions in pH may have a negative impact on the ecophysiology of coccolithophores.
    Keywords: Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Bicarbonate ion; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calcification/Dissolution; Calcite saturation state; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, particulate, per cell; Carbon, inorganic, particulate, production per cell; Carbon, inorganic, particulate, standard deviation; Carbon, organic, particulate, per cell; Carbon, organic, particulate, production per cell; Carbon, organic, particulate, standard deviation; Carbon, organic, particulate/Nitrogen, particulate ratio; Carbon, organic, particulate/Nitrogen, particulate ratio, standard deviation; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Cellular lipid quota/cellular particulate organic carbon quota; Cellular lipid quota/cellular particulate organic carbon quota, standard deviation; Chlorophyll a, production, standard deviation; Chlorophyll a, standard deviation; Chlorophyll a per cell; Chlorophyll a production per cell; Chromista; Coccosphere, diameter; Coccosphere, diameter, standard deviation; Coccospheres; Diameter; Diameter, standard deviation; Distal shield, length; Distal shield, length, standard deviation; Distal shield, width; Distal shield, width, standard deviation; Emiliania huxleyi; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Growth/Morphology; Growth rate; Growth rate, standard deviation; Haptophyta; Laboratory experiment; Laboratory strains; Lipid production per cell; Lipid production per cell, standard deviation; Lipids, standard deviation; Lipids per cell; Not applicable; OA-ICC; Ocean Acidification International Coordination Centre; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Particulate inorganic carbon, production, standard deviation; Particulate inorganic carbon/particulate organic carbon ratio; Particulate inorganic carbon/particulate organic carbon ratio, standard deviation; Particulate inorganic carbon/total particulate nitrogen ratio; Particulate inorganic carbon/total particulate nitrogen ratio, standard deviation; Particulate organic carbon, production, standard deviation; Pelagos; pH; Phytoplankton; Primary production/Photosynthesis; Salinity; Single species; Species, unique identification; Species, unique identification (Semantic URI); Species, unique identification (URI); Temperature; Temperature, water; Type; Width; Width, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 979 data points
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  • 35
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    Seawater carbonate chemistry and growth, elemental composition,biomass production, respiration and carbon acquisition of diatoms Thalassiosira hyalina and Melosira arctica (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Sea ice retreat, changing stratification, and ocean acidification are fundamentally changing the light availability and physico-chemical conditions for primary producers in the Arctic Ocean. However, detailed studies on ecophysiological strategies and performance of key species in the pelagic and ice-associated habitat remain scarce. Therefore, we investigated the acclimated responses of the diatoms Thalassiosira hyalina and Melosira arctica toward elevated irradiance and CO2 partial pressures (pCO2). Next to growth, elemental composition, and biomass production, we assessed detailed photophysiological responses through fluorometry and gas-flux measurements, including respiration and carbon acquisition. In the pelagic T. hyalina, growth rates remained high in all treatments and biomass production increased strongly with light. Even under low irradiances cells maintained a high-light acclimated state, allowing them to opportunistically utilize high irradiances by means of a highly plastic photosynthetic machinery and carbon uptake. The ice-associated M. arctica proved to be less plastic and more specialized on low-light. Its acclimation to high irradiances was characterized by minimizing photon harvest and photosynthetic efficiency, which led to lowered growth. Comparably low growth rates and strong silification advocate a strategy of persistence rather than of fast proliferation, which is also in line with the observed formation of resting stages under low-light conditions. In both species, responses to elevated pCO2 were comparably minor. Although both diatom species persisted under the applied conditions, their competitive abilities and strategies differ strongly. With the anticipated extension of Arctic pelagic habitats, flexible high-light specialists like T. hyalina seem to face a brighter future.
    Keywords: Alkalinity, total; Alkalinity, total, standard deviation; Antenna size; Aragonite saturation state; Arctic; Bicarbonate ion; Biogenic silica, per cell; Biogenic silica/Carbon, organic, particulate; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calcite saturation state; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbon, organic, particulate, per cell; Carbon, organic, particulate, production per cell; Carbon/Nitrogen ratio; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Central_Arctic_ocean; Chlorophyll a/particulate organic carbon ratio; Chlorophyll a per cell; Chromista; Connectivity between photosystem II; Electron transport rate, relative; Electron transport rate, relative, maximum velocity; Event label; EXP; Experiment; Fluorometry; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Gas-flux measurement; Growth/Morphology; Growth rate; Identification; Irradiance; KongsfjordenOA; Laboratory experiment; Light; Light saturation point; Maximum light use efficiency; Maximum photochemical quantum yield of photosystem II; Melosira arctica; Net photosynthesis rate, carbon dioxide, per chlorophyll a; Net photosynthesis rate, oxygen, per chlorophyll a; Net photosynthesis rate, oxygen, per particulate organic carbon; Non photochemical quenching; OA-ICC; Ocean Acidification International Coordination Centre; Ochrophyta; Open ocean; Partial pressure of carbon dioxide, standard deviation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Particulate organic carbon production, per chlorophyll a; Particulate organic carbon production, per particulate organic carbon; Pelagos; Percentage; pH; pH, standard deviation; Photosynthetic efficiency, carbon production; Photosynthetic quotient; Phytoplankton; Polar; Primary production/Photosynthesis; Ratio; Reopening rate; Respiration; Respiration rate, oxygen, per chlorophyll a; Salinity; Single species; Species, unique identification; Species, unique identification (Semantic URI); Species, unique identification (URI); Temperature, water; Temperature, water, standard deviation; Thalassiosira hyalina; Treatment: partial pressure of carbon dioxide; Type
    Type: Dataset
    Format: text/tab-separated-values, 4737 data points
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  • 36
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    Physiological response of E. huxleyi ecotype A, strain SO5.14 to changing carbonate chemistry under nutrient-replete conditions (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Future oceanic conditions induced by anthropogenic greenhouse gas emissions include warming, acidification and reduced nutrient supply due to increased stratification. Some parts of the Southern Ocean are expected to show rapid changes, especially for carbonate mineral saturation. Here we compare the physiological response of the model coccolithophore Emiliania huxleyi (strain EHSO 5.14, originating from 50S, 149E) with pH/CO2 gradients (mimicking ocean acidification ranging from 1 to 4 × current pCO2 levels) under nutrient-limited (nitrogen and phosphorus) and -replete conditions. Both nutrient limitations decreased per cell photosynthesis (particulate organic carbon (POC) production) and calcification (particulate inorganic carbon (PIC) production) rates for all pCO2 levels, with more than 50% reductions under nitrogen limitation. These impacts, however, became indistinguishable from nutrient-replete conditions when normalized to cell volume. Calcification decreased three-fold and linearly with increasing pCO2 under all nutrient conditions, and was accompanied by a smaller ~30% nonlinear reduction in POC production, manifested mainly above 3 × current pCO2. Our results suggest that normalization to cell volume allows the major impacts of nutrient limitation (changed cell sizes and reduced PIC and POC production rates) to be treated independently of the major impacts of increasing pCO2 and, additionally, stresses the importance of including cell volume measurements to the toolbox of standard physiological analysis of coccolithophores in field and laboratory studies.
    Keywords: Alkalinity, total; Aragonite saturation state; Bicarbonate ion; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calcification/Dissolution; Calcite saturation state; Calculated using CO2SYS; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, particulate, per cell; Carbon, organic, particulate, per cell; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Cell biovolume; Chromista; Coccoliths, volume; Coulometric titration; Emiliania huxleyi; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Growth/Morphology; Haptophyta; Laboratory experiment; Laboratory strains; Macro-nutrients; Nitrogen, organic, particulate, per cell; Not applicable; OA-ICC; Ocean Acidification International Coordination Centre; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); pH; Phytoplankton; Potentiometric titration; Primary production/Photosynthesis; Salinity; Single species; Species, unique identification; Species, unique identification (Semantic URI); Species, unique identification (URI); Temperature, water; Treatment; Type of study; Volume
    Type: Dataset
    Format: text/tab-separated-values, 223 data points
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  • 37
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    Temperature effects on the physiology of photosynthesis and respiration in Phaeodactylum tricornutum (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: Phaeodactylum tricornutum strain CCAP 1052/1A was cultivated at 6°C and 15°C under controlled conditions (32 salinity, F/2 medium, 400 µatm pCO2, 100 µmol photons m-2 s-2 light intentsity 16:8 light:dark cycle) in semi-continous batch cultures. We assessed the carbonate chemistry (pH, total alkalinity, dissolved inorganic carbon), growth rates, particulate organic carbon and nitrogen (POC and PON), chlorophyll a quota (Chl a), POC:PON ratios, Chl a:POC ratios as well as production rates at both acclimation temperatures. Additionally, we performed biological invivo assays to measure rates of gross photosynthetic oxygen release, gross photosynthetic carbon uptake, respiratory oxygen uptake and respiratory carbon release using membrane-inlet mass-spectrometry. Assays were performed in photosynthesis-irradiance-(PI-)curves of increasing light intensity (0, 50, 150, 250, 400 µmol photons m-2 s-2). First rates were measured under acclimation temperature (6°C and 15°C), directly afterwards, the assay temperature was abruptly shifted to 15°C or 6°C, respectively, and the PI-curve measurement was repeated, so that 6°C acclimated cells were measured at 15°C and 15°C acclimated cells were measured at 6°C. Q10 factors were calculated from acclimated cells und the respective temperature shift. Photosynthetic and respiratory quotients were calculated for acclimated cells as well as after the abrupt temperature shift. PI-parameters, i.e. maximum photosynthesis rate, light use efficiency and light saturation index were calculated. All experiments were performed in laboratories at the Alfred-Wegener-Institute Bremerhaven.
    Keywords: Alkalinity, total; Calculated; Calculation according to Rehder et al. (2023); Calculation according to Rokitta & Rost (2012); Carbon, inorganic, dissolved; Carbon, organic, particulate, per cell; Carbon, organic, particulate, production per cell; Carbon, organic, particulate/Nitrogen, organic, particulate ratio; Chlorophyll a/particulate organic carbon ratio; Chlorophyll a per cell; Coulter Counter (Beckman Coulter); Date/time end, experiment; Date/time start, experiment; Diatom; Elemental analyzer, EuroVector, EA 3000; Experiment; Factor quantifying temperature dependent change of rates of processes; Generation; Gross photosynthetic carbon uptake rate, per chlorophyll a; Gross photosynthetic oxygen release rate, per chlorophyll a; Growth rate; Laboratory; Laboratory experiment; Laboratory fluorometer, Turner, Trilogy; Light saturation index; Light use efficiency; Maximum photosynthetic carbon uptake rate, per chlorophyll a; Maximum photosynthetic oxygen release rate, per chlorophyll a; Measured with colorimetric assay on QuAAtro continuous segmented flow analyzer (Seal Analytical); Medium; Membrane inlet mass spectrometer (MIMS), GV Instruments, Isoprime; Nitrogen, organic, particulate, per cell; pH; Phaeodactylum tricornutum; Photosynthesis; Photosynthetic quotient; Physiological performance; Phytoplankton; Respiration; Respiratory carbon release rate, per chlorophyll a; Respiratory oxygen uptake rate, per chlorophyll a; Respiratory quotient; Salinity; Sample ID; Sampling date/time, experiment; Species; Species, unique identification; Species, unique identification (Semantic URI); Species, unique identification (URI); Strain; Temperature; Titration analyzer, Schott Instruments, TitroLine alpha plus; Treatment: light:dark cycle; Treatment: light intensity; Treatment: temperature; Type of study
    Type: Dataset
    Format: text/tab-separated-values, 736 data points
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  • 38
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    Western tropical South Atlantic sea surface temperature over the last 300 kyr based on Mg/Ca in shells of Globigerinoides ruber (white) from sediment core GL1180 (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: We investigate long-term SST variability of the western tropical South Atlantic (WTSA) using a 300 kyr-long SST record derived from Mg/Ca ratios in shells of Globigerinoides ruber (white). The foraminifera shells were derived from sediment core GL-1180, which was retrieved from 1037 m water depth at the northeastern continental margin of Brazil (8° 27'18 S, 33° 32'53 W) by the Brazilian oil company Petrobras. Measurements of Mg/Ca ratios were performed using an inductively coupled plasma optical emission spectrometer (ICP-OES) at MARUM-Center for Marine Environmental Sciences, University of Bremen. Additionally, Fe, Mn, and Al were measured to monitor contaminants.
    Keywords: AGE; Calculated; Core; CORE; DEPTH, sediment/rock; GL1180; GL-1180; Glacial cycles; Globigerinoides ruber; Globigerinoides ruber white, Aluminium/Calcium ratio; Globigerinoides ruber white, Iron/Calcium ratio; Globigerinoides ruber white, Magnesium/Calcium ratio; Globigerinoides ruber white, Manganese/Calcium ratio; ICP-OES; Mg/Ca; Sea surface temperature; Sea surface temperature, standard deviation; SST from Mg/Ca ratios; western tropical Atlantic; western tropical South Atlantic
    Type: Dataset
    Format: text/tab-separated-values, 3270 data points
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  • 39
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    Mid- Holocene stable isotope records (ẟ18O and ẟ13C) of speleothem VEAJ from Alfredo Jahn Cave, northern Venezuela (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: The stable isotope records for mid- and late- Holocene are based on two stalagmites, VEAJ collected in Alfredo Jahn cave and VECA collected in Caripe Cave, respectively. Both caves are located in northern Venezuela, adjacent to Cariaco Basin. The ẟ18O record was interpreted as a proxy for the proximity of the Intertropical Convergence Zone (ITCZ) to our study sites, and the ẟ13C record as a proxy for vegetation changes, as discussed in the paper 'Atlantic ITCZ variability during the Holocene based on high-resolution speleothem isotope records from northern Venezuela' (Medina et al., 2023). The ẟ18O and ẟ13C analyses were performed at the Stable Isotope Laboratory at the Institute of Geoscience of the University of São Paulo (Brazil) using a Thermo-Finnigan Delta Plus Advantage mass spectrometer. ẟ-notation in per mil units (‰) was used to express the sample isotopic ratios deviation from the Vienna Pee Dee Belemnite (VPDB) standard. Approximately 200 μg of CaCO3-powder subsamples for ẟ18O and ẟ13C stable isotopic analyses were collected using a manually controlled Sherline 5400 milling at a resolution of 0.4 mm for VEAJ and 0.5 mm for VECA. The ẟ18O and ẟ13C isotopic profiles of VEAJ-base, VEAJ-top left and VEAJ-top right are based on 530, 310 and 250 samples, respectively. VECA isotopic profiles consist of 670 samples. Since VEAJ-top left overlaps with some sections of the -top right record, we merged them through normalization (i.e., by subtracting the mean and dividing by the standard deviation) of the data inside the overlapping period, averaging both series and then reconstructing the shorter time series with the mean and standard deviation of the longer one. The geochronology was established by means of the U/Th dating method, using a multicollector inductively-coupled plasma mass spectrometers (MC-ICP-MS-Thermo-Finnigan NEPTUNE) at the Institute of Global Environmental Change, Xi'an Jiaotong University (China). The sampling for the U/Th dating was performed by extracting ~0.100 g of powdered carbonate with a handheld drill of the least porous and colored, most traceable layers along or at the side of each speleothem growth axis. A total of 42 U/Th ages were used to construct the age model for VEAJ and 25 for VECA, yielding an mean temporal stable isotope sampling resolutions of 3 and 23 years for VEAJ-base & top-composite, respectively, and 1.5 years for VECA. Some age reversals along the stalagmites were flagged as outliers using Bayesian statistics, and consequently removed from the age models. For other age inversions, an iterative procedure was applied to increase the range of uncertainty in order to fulfill the monotonicity criterion (Scholz and Hoffmann, 2011).
    Keywords: AGE; Age, dated; Age, dated standard error; Age, Uranium-Thorium; Alfredo Jahn cave; Cariaco Basin; Caribbean; d13C; d18O; DISTANCE; Holocene climate; Intertropical Convergence Zone (ITCZ); Mass spectrometer Thermo Finnigan DELTA plus Advantage; paleoenvironment; Profile; Speleothems; Speleothem sample; SPS; stable isotope data; VEAJ; Venezuela; δ13C, carbonate; δ18O, carbonate
    Type: Dataset
    Format: text/tab-separated-values, 2562 data points
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  • 40
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    Seawater carbonate chemistry and characterization of oyster growth and calcification on constructed oyster reefs (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: This study, therefore, sought to (1) characterize the baseline pH/DO variability as well as the associated drivers of the carbonate system in constructed reefs to (2) determine the reefs' influence on the biogeochemistry of the overlying waters and (3) evaluate the impacts, if any, on resident oysters, particularly in environments already prone to coastal acidification. To do this, we conducted a 4-year study (2018–2021) of multiple constructed subtidal oyster reefs in Shinnecock Bay, NY USA. We monitored the growth of three oyster reefs over four consecutive years and established high frequency time series of pHNBS, DO, and other relevant environmental parameters in both regional ambient seawater and reef-modified seawater during the summer months (when coastal acidification is most prevalent and oyster growth is maximal) over two of the four years. During one year, these data were paired with weekly surveys characterizing habitat macroalgae abundance and with biweekly sampling of reef and control seawater for discrete measurements of DIC, TA, and chlorophyll a. Finally, two in situ oyster experiments were conducted during the summers of two separate years to evaluate the impact of reef-modified seawater conditions versus ambient seawater conditions on juvenile oyster growth and survival. This dataset is included in the OA-ICC data compilation maintained in the framework of the IAEA Ocean Acidification International Coordination Centre (see https://oa-icc.ipsl.fr). Original data were downloaded from Dryad (see Source) by the OA-ICC data curator. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2024) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2024-04-28.
    Keywords: Abundance per area; Age; Alkalinity, total; Animalia; Aragonite saturation state; Benthic animals; Benthos; Bicarbonate ion; Biomass/Abundance/Elemental composition; Calcification/Dissolution; Calcification rate; Calcite saturation state; Calcium carbonate, mass; 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; Coverage; Crassostrea virginica; Date; Date/time end; Date/time start; Entire community; Field experiment; Field observation; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Growth/Morphology; Growth rate; Height; Identification; Mollusca; North Atlantic; OA-ICC; Ocean Acidification International Coordination Centre; Oxygen, apparent utilization; Oxygen, dissolved; Oxygen saturation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); pH; Rocky-shore community; Salinity; Shell, mass; Shell growth; Shell height; Single species; Site; Temperate; Temperature, water; Type of study; Year of sampling
    Type: Dataset
    Format: text/tab-separated-values, 15571 data points
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  • 41
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    Fish length data during Alkor cruise AL539 (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Description: This data set comprises all fish length data collected during the RV ALKOR cruise AL539 conducted in July 2020 (July 5th to July 18th 2020) in the Western Baltic Sea by the University of Hamburg. The cruise was part of the 5-year MARSYS teaching cruise program of the University of Hamburg GFP20-1_047. The fish length data were collected directly on board.
    Keywords: AL539; AL539_16-1; AL539_17-1; AL539_18-2; AL539_19-2; AL539_20-2; AL539_21-2; AL539_22-2; AL539_2-3; AL539_23-2; AL539_24-2; AL539_25-2; AL539_26-2; AL539_4-3; AL539_73-2; AL539_74-2; AL539_75-2; AL539_76-2; AL539_77-2; AL539_78-2; Alkor (1990); Baltic Sea; Cruise/expedition; CTD/Rosette; CTD-RO; DATE/TIME; DEPTH, water; Event label; Field measurements; fish; Fish measuring board; Gadus morhua; LATITUDE; Length; Life stage; Location; LONGITUDE; Number of individuals; RV ALKOR; Species, unique identification; Species, unique identification (Semantic URI); Species, unique identification (URI); Station label; summer; Teaching cruise; TRAWL; Trawl net
    Type: Dataset
    Format: text/tab-separated-values, 2997 data points
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  • 42
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    Organic-walled dinoflagellate cyst of sediment core GeoB8601-3 (2020)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: 261; Age; AGE; Ataxiodinium choane; Brigantedinium spp.; Center for Marine Environmental Sciences; Counting, palynology; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Dinoflagellate cyst; Dinoflagellate cyst indeterminata; Dubridinium spp.; Echinidinium aculeatum; Echinidinium delicatum; Echinidinium granulatum; Echinidinium spp.; Echinidinium transparantum; Echinidinium zonneveldiae; GeoB8601-3; Gravity corer (Kiel type); Gymnodinium nolleri; Impagidinium aculeatum; Impagidinium paradoxum; Impagidinium patulum; Impagidinium plicatum; Impagidinium sphaericum; Impagidinium spp.; Impagidinium strialatum; Impagidinium variaseptum; Lejeunecysta oliva; Lejeunecysta paratenella; Lejeunecysta sabrina; Lejeunecysta spp.; Lingulodinium machaerophorum; M58/2; Marker, added; Marker, found; MARUM; Mass; Meteor (1986); Nematosphaeropsis labyrinthus; off Northwest Africa; Operculodinium centrocarpum; Operculodinium israelianum; Pentapharsodinium dalei; Polykrikos kofoidii; Polykrikos schwartzii; Polysphaeridium zoharyi; Protoperidinium americanum; Protoperidinium monospinum; Quinquecuspis concreta; Selenopemphix nephroides; Selenopemphix quanta; Selenopemphix sp.; SL; Spiniferites bentori; Spiniferites elongatus; Spiniferites hyperacanthus; Spiniferites membranaceus; Spiniferites mirabilis; Spiniferites ramosus; Spiniferites spp.; Stelladinium robustum; Trinovantedinium applanatum; Votadinium calvum; Votadinium spinosum; Xandarodinium xanthum
    Type: Dataset
    Format: text/tab-separated-values, 2515 data points
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  • 43
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    LOI record from sediment core Razdolye, Kursk region, Russia (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: charcoal; DEPTH, sediment/rock; forest-steppe ecotone; Late Holocene; loss on ignition; Loss on ignition; macrocharcoal; Microcharcoal; non-pollen palynomorphs; Oven-dried; Pollen; Razdolye
    Type: Dataset
    Format: text/tab-separated-values, 96 data points
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  • 44
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    Globorotalia truncatulinoides carbon isotopic composition (δ13C) from northwestern South Atlantic sediment core M125-95-3 (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: AGE; AWI_INSPIRES; DEPTH, sediment/rock; Globorotalia inflata; Globorotalia truncatulinoides; Globorotalia truncatulinoides, δ13C; iAtlantic; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; International Science Program for Integrative Research in Earth Systems; Isotope ratio mass spectrometry; M125; M125_469-3; M125-95-3; Meteor (1986); Mg/Ca-based sea surface temperature; PC; Piston corer; SACW; SAMBA; South Atlantic; South Atlantic Ocean; Thermodynamic isotopic air-sea equilibration
    Type: Dataset
    Format: text/tab-separated-values, 258 data points
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  • 45
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    Globigerinoides ruber Mg/Ca-based sea surface temperature (°C) from northwestern South Atlantic sediment core M125-95-3 (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: AGE; AWI_INSPIRES; DEPTH, sediment/rock; Globorotalia inflata; Globorotalia truncatulinoides; iAtlantic; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; International Science Program for Integrative Research in Earth Systems; M125; M125_469-3; M125-95-3; Meteor (1986); Mg/Ca-based sea surface temperature; PC; Piston corer; SACW; SAMBA; Sea surface temperature, annual mean; South Atlantic; South Atlantic Ocean; SST from Mg/Ca ratios; Thermodynamic isotopic air-sea equilibration
    Type: Dataset
    Format: text/tab-separated-values, 85 data points
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  • 46
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    Full Brazilian margin (Brazil Current and North Brazil Current) sea surface temperature compilation since the Last Glacial Maximum (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: 053-2; 087-1; AGE; Age, 14C calibrated, CALIB 8.2 and Marine20 calibration curve; Age, 14C calibrated, CALIB 8.2 and Marine20 calibration curve plus regional reservoir error; Age, standard deviation; AMADEUS; AMOC; Argentine Basin; Brazil Current; Cabo Frio Upwelling, Southwest Atlantic; CF10-01B; Continental Slope Northeast Brazil; Core; CORE; Event label; French Guiana; GC; GeoB16202-2; GeoB16224-1; GeoB3129-1; GeoB3911-1; GeoB6211-1; GeoB6211-2; GGC; Giant gravity corer; GL1090; GL-1090; GL1180; GL-1180; GL1248; GL-1248; Gravity corer; Gravity corer (Kiel type); interpolated; JOPSII-6; JPC17; KN159-5; Knorr; KNR159-5; KNR159-5-36GGC; last deglaciation; Latitude of event; Longitude of event; M125; M125_428-3; M125_445-7; M125_469-3; M125-35-3; M125-55-7; M125-95-3; M34/4; M46/2; Maria S. Merian; Meteor (1986); MSM20/3; MUC; MultiCorer; NE-Brazilian continental margin; North Brazil Current; Northeast Brasilian Margin; Paleoprod; PC; PC-7610; PC-7616; Piston corer; Prof W Besnard; SAMBA; Sea surface temperature, anomaly; Sea surface temperature, anomaly, standard deviation; SL; South Atlantic; South Atlantic Ocean; South Brazil Bight, Santos Basin; Victor Hensen; western South Atlantic; western tropical Atlantic
    Type: Dataset
    Format: text/tab-separated-values, 2810 data points
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  • 47
    facet.materialart.
    Unknown
    Pollen, non-pollen palynomorphs record from sediment core Razdolye, Kursk region, Russia (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: Abies; Adoxaceae; Alnus; Amphitrema flavum; Anthoceros crispulus-type; Apiaceae; Arcella cf. discoides; Arcella cf. megastoma; Artemisia; Assulina muscorum; Astragalus-type; Betula pubescens-type; Brassicaceae; Bullinularia indica; Cannabinaceae; Cantocamptus spermatophora; Carpinus betulus; Caryophyllaceae; Castanea; Centaurea cyanus; Centaurea jacea-type; Centaurea scabiosa-type; Centropyxis aculeata; Cercophora sp.; Cerealia-type; cf. Avena-type; cf. Hordeum-type; cf. Triticum-type; charcoal; Charcoal; Chenopodiaceae; Cichorioideae; Cirsium; Convolvulus arvensis-type; Corylus; Counting pollen with microscope; Crustacea, fragment; Cuscuta europaea-type; Cyperaceae; Daphne; DEPTH, sediment/rock; Dianthus; Dianthus caryophylleus; Dianthus neglectus; Difflugia indeterminata; Difflugia pulex; Digitalis; Empetrum/Ledum-type; Endophragmiella; Epilobium; Equisetum; Fabaceae; Fagopyrum; Fallopia; Filinia longiseta-type; Filipendula; forest-steppe ecotone; Fraxinus excelsior-type; Fungi; Gelasinospora; Gentiana pneuneonanthe-type; Gieysztoria virgulifera; Glomeromycota indeterminata; Glomus sp.; Gyratrix hermaphroditus; Herniaria/Paronychia; Indeterminata; Insect, fragments; Juniperus; Late Holocene; Lemnaceae; loss on ignition; Lycopodium (added); Lycopodium (counted); Lycopodium annotinum; Lycopodium tablets; Lysimachia vulgaris-type; macrocharcoal; Matricaria-type; Medicago sativa-type; Microcharcoal; Mougeotia; Myriophyllum spicatum; Nadinella sp.; Neorhabdocoela Oocyte; Neorhabdocoela operculum; non-pollen palynomorphs; Odontites-type; Oxalis stricta-type; Palynomorpha; Papaver argemone; Persicaria maculosa-type; Picea; Pinus diploxylon-type; Plantago lanceolata-type; Plantago major-media-type; Pleospora sp.; Pleurospermum-type; Poaceae; Podospora anserina-type; Podospora decipiens-type; Pollen; Polygonum aviculare-type; Populus; Pseudoschizaea; Pteridium; Quercus robur/pubescence-type; Ranunculus acris-type; Razdolye; Riccia; Riccia tetrade; Rosa; Rubus; Rumex; Rumex acetosa-type; Saggitaria saggitifolia; Salix; Sambucus nigra-type; Sample volume; Saxifraga hirculus-type; Scheuchzeria palustris; Scorzonera humilis-type; Secale; Senecio-type; Silene-type; Sorbus-group; Sordaria sp.; Sparganium-type; Spergularia-type; Spirogyra sp.; Spores, monolete; Spores, trilete; Stuartella sp.; Testate amoeba indet; Thalictrum; Thecaphora sp.; Tilia; Trachelomonas cf. hispida; Trichocerca; Triglochin; Typha latifolia-type; Ulmus; Urticaceae; Valeriana officinalis-type; Veronica-type; Viburnum opulus-type; Viscum album; Xanthium strumarium-type; Zea mays; Zygnemataceae
    Type: Dataset
    Format: text/tab-separated-values, 4316 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 48
    facet.materialart.
    Unknown
    Globorotalia truncatulinoides carbon isotopic composition (δ13C) from southwestern South Atlantic sediment core GeoB2107-3 (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: AGE; AWI_INSPIRES; Brazil Basin; DEPTH, sediment/rock; GeoB2107-3; Globorotalia inflata; Globorotalia truncatulinoides; Globorotalia truncatulinoides, δ13C; Gravity corer (Kiel type); iAtlantic; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; International Science Program for Integrative Research in Earth Systems; Isotope ratio mass spectrometry; M23/2; Meteor (1986); Mg/Ca-based sea surface temperature; SACW; SL; South Atlantic; Thermodynamic isotopic air-sea equilibration
    Type: Dataset
    Format: text/tab-separated-values, 421 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 49
    facet.materialart.
    Unknown
    Stacked Artemisia record from the Iberian Peninsula and Morocco (last 5000 years BP) (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: AANSSER; ADAJA; Africa; AGE; AJO; Al-Andalus; Albufera Alcudia, Spain; ALCUDIA; ALGENDAR; Algendar, Spain; Almenara de Adaja, Spain; ALSA; Alsa, Spain; ANTAS; Antas, Spain; ARBARRAIN; AREO; ARMENA; Arroyo de las Cárcavas; Arroyo de Navalacarreta; Arroyo de Valdeconejos; Artemisia; Artemisia, normalized; Atxuri, Spain; ATXURI01; Ayo de Vidriales; AYOO; BAB_EL_KARN; BANA_C; BANA_D; BANYOLES; Banyoles, Spain; BARBAROX; BASAMORA; BASSA_NERA; BAZA; BELATE01; Beliche-Guadiana; BESOS; Bosc dels Estanyons, Andorra; BOSCESTA; BOTIJA; BREZOSO; Cala Galdana, Spain; Calan Porter, Spain; Calculated, 15-point moving average; Calculated, 45-point moving average; CANADACR; CANDIEIR; CARCAVAS; CARRIZAL; CHAFARIZ; Charco da Candieira, Portugal; CLAREZA; COES; COMPR1_J; Core1; Core2; Core3; Core6; CoreB1; CPORTER; CREIXELL; CRUZ; CuadramónI; CUAI; CULAZON; Culazón; DACH; Dachnowski corer; DAYET; DRILL; Drilling/drill rig; Eijkelkamp Kammerbohrer; EKB; El Maíllo mire; ELPAYO; El Payo, Spain; ELX; ESPINOSA; ESTACAS; ESTANY; Europe; FAVAS; GADOR; GALDANA; GRAU; GUALLAR; HACHLAF1; HONDERA; Hort Timoner, Spain; HTIMONER; Iberian Peninsula; INDC; Industrial corer; LABRADIL; Labradillos mire; LAGMESAG; LAGNEGRA; Lagoa Travessa I, Portugal; Laguna de la Roya, Spain; Laguna Mesagosa; Laguna Negra; Lake_Sidi_Ali; La Molina mire, Spain; LANZAHIT; Lanzahíta, Spain; LAROYA; Les Palanques; LIVB; LIVC; Livingstone borer; Livingstone corer; Livingstone piston corer; LLIGAT; LPC; MAI; MARBORE; MEDINA; Middle Atlas, Morocco; MITJANA; MOLINAES; Monte Areo mire, Spain; Montes do Buio Cuadramón, Spain; Morocco; MOURISCO; NAVALACA; Navarres; Padul-15-05; PALANQUE; PARDILLAS; PATATERO; Patateros bog; PCUWI; PEATC; Peat corer; Pedrido_Bog; PENANEGR; Peña Negra, Spain; Pico del Sertal, Spain; Piston corer, UWITEC; Poço do Barbaroxa de Cima, Portugal; Pollen; Posidonia Lligat, Spain; PRAILLOS; PRATVILA; PRD4; PRD-4, Spain; Puerto de Belate, Spain; Puerto de las Estaces de Trueba, Spain; Puerto de Los Tornos, Spain; Puerto de Serranillos, Spain; QUINTA01; Quintanar de la Sierra, Spain; Ras_El_Ma; RCD; Rio_Seco; ROQUETAS; Roquetas de Mar, Spain; Rotary core drilling; RPB; RPS; RUSC; Russian corer; Russian peat borer; Russian peat sampler; SABINAR; Salada_Chiprana; Salada_Pequena; SALDROPO; Saldropo, Spain; SALGAD; SALINES; San_Rafael_EPD; SANABRIA; Sanabria Marsh, Spain; Sediment sample; Serra Mitjana fen; SERRANIL; SERTAL; SES; Sierra Nevada, Spain; SILES; SONBOU; Son Bou, Spain; SOTOMBO; Spain; Square-rod piston corer; SRPC; Stack; TIGAL; Tigalmamine, Morocco; TORNOS01; TRAVESS1; TUB_EPD; Tubilla del Lago; VALDECON; VALDEYER; Valdeyernos bog; VERDEOSP; VINUELAS; Visigothic Kingdom; Xan de Llamas; Xerophytes; XL; ZALAMA; ZONAR
    Type: Dataset
    Format: text/tab-separated-values, 12526 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 50
    facet.materialart.
    Unknown
    Stacked Artemisia and xerophyte records from the Iberian Peninsula and Morocco (last 5000 years BP) - Sites and data sources (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-27
    Keywords: AANSSER; ADAJA; Africa; AJO; Al-Andalus; Albufera Alcudia, Spain; ALCUDIA; ALGENDAR; Algendar, Spain; Almenara de Adaja, Spain; ALSA; Alsa, Spain; ANTAS; Antas, Spain; ARBARRAIN; AREO; ARMENA; Arroyo de las Cárcavas; Arroyo de Navalacarreta; Arroyo de Valdeconejos; Artemisia; Atxuri, Spain; ATXURI01; Ayo de Vidriales; AYOO; BAB_EL_KARN; BANA_C; BANA_D; BANYOLES; Banyoles, Spain; BARBAROX; BASAMORA; BASSA_NERA; BAZA; BELATE01; Beliche-Guadiana; BESOS; Bosc dels Estanyons, Andorra; BOSCESTA; BOTIJA; BREZOSO; Cala Galdana, Spain; Calan Porter, Spain; CANADACR; CANDIEIR; CARCAVAS; CARRIZAL; CHAFARIZ; Charco da Candieira, Portugal; CLAREZA; COES; COMPR1_J; Core1; Core2; Core3; Core6; CoreB1; CPORTER; CREIXELL; CRUZ; CuadramónI; CUAI; CULAZON; Culazón; DACH; Dachnowski corer; DAYET; DRILL; Drilling/drill rig; Eijkelkamp Kammerbohrer; EKB; ELEVATION; El Maíllo mire; ELPAYO; El Payo, Spain; ELX; ESPINOSA; ESTACAS; ESTANY; Europe; Event label; FAVAS; GADOR; GALDANA; GRAU; GUALLAR; HACHLAF1; HONDERA; Hort Timoner, Spain; HTIMONER; Iberian Peninsula; Identification; INDC; Industrial corer; LABRADIL; Labradillos mire; LAGMESAG; LAGNEGRA; Lagoa Travessa I, Portugal; Laguna de la Roya, Spain; Laguna Mesagosa; Laguna Negra; Lake_Sidi_Ali; La Molina mire, Spain; LANZAHIT; Lanzahíta, Spain; LAROYA; LATITUDE; Les Palanques; LIVB; LIVC; Livingstone borer; Livingstone corer; Livingstone piston corer; LLIGAT; LONGITUDE; LPC; MAI; MARBORE; MEDINA; Method comment; Middle Atlas, Morocco; MITJANA; MOLINAES; Monte Areo mire, Spain; Montes do Buio Cuadramón, Spain; Morocco; MOURISCO; NAVALACA; Navarres; Padul-15-05; PALANQUE; PARDILLAS; PATATERO; Patateros bog; PCUWI; PEATC; Peat corer; Pedrido_Bog; PENANEGR; Peña Negra, Spain; Pico del Sertal, Spain; Piston corer, UWITEC; Poço do Barbaroxa de Cima, Portugal; Pollen; Posidonia Lligat, Spain; PRAILLOS; PRATVILA; PRD4; PRD-4, Spain; Puerto de Belate, Spain; Puerto de las Estaces de Trueba, Spain; Puerto de Los Tornos, Spain; Puerto de Serranillos, Spain; QUINTA01; Quintanar de la Sierra, Spain; Ras_El_Ma; RCD; Reference/source; Reference of data; Rio_Seco; ROQUETAS; Roquetas de Mar, Spain; Rotary core drilling; RPB; RPS; RUSC; Russian corer; Russian peat borer; Russian peat sampler; SABINAR; Salada_Chiprana; Salada_Pequena; SALDROPO; Saldropo, Spain; SALGAD; SALINES; San_Rafael_EPD; SANABRIA; Sanabria Marsh, Spain; Sediment sample; Serra Mitjana fen; SERRANIL; SERTAL; SES; Sierra Nevada, Spain; SILES; Site; SONBOU; Son Bou, Spain; SOTOMBO; Spain; Square-rod piston corer; SRPC; Stack; TIGAL; Tigalmamine, Morocco; TORNOS01; TRAVESS1; TUB_EPD; Tubilla del Lago; Uniform resource locator/link to source data file; VALDECON; VALDEYER; Valdeyernos bog; VERDEOSP; VINUELAS; Visigothic Kingdom; Xan de Llamas; Xerophytes; XL; ZALAMA; ZONAR
    Type: Dataset
    Format: text/tab-separated-values, 728 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
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