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  • 2020-2024  (166,290)
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  • 1
    Publication Date: 2024-05-26
    Description: Abstract
    Description: This collection contains 10500 computationally generated, randomised 2D microstructures, their geometrical and electrical properties, and the Matlab software package used to calculate these properties. The two-phase microstructures (mineral matrix, pore space) represent three different pore space types (microfracture networks, intergranular pore space, oomoldic pore space) and are organised into 35 ensembles - with common modelling parameters - of 100 individual microstructure realisations each. For all realisations, several geometrical properties (percolation, total porosity, connected porosity, isolated porosity, surface area, fractal dimension) and physical properties (formation factor from electrical resistivity, electrical tortuosity) are given. The collection also includes a Matlab-based finite element simulation package derived from the FEMALY library, which can be used to compute the properties of any given 2D raster microstructure.
    Keywords: petrophysics ; microstructure ; finite element method ; permeability and porosity ; statistical methods ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 SEDIMENTARY ROCKS 〉 SEDIMENTARY ROCK PHYSICAL/OPTICAL PROPERTIES ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 SEDIMENTARY ROCKS 〉 SEDIMENTARY ROCK PHYSICAL/OPTICAL PROPERTIES 〉 ELECTRICAL ; science 〉 natural science 〉 earth science 〉 geophysics
    Type: Collection , Collection
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  • 2
    Publication Date: 2024-05-26
    Keywords: A Palaeoreanalysis To Understand Decadal Climate Variability; DATE/TIME; Description; ELEVATION; File name; GlobCover; Identification; LATITUDE; LONGITUDE; PALAEO-RA; Station label; Temperature, air, monthly mean; Uniform resource locator/link to source data file
    Type: Dataset
    Format: text/tab-separated-values, 3365786 data points
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  • 3
    Publication Date: 2024-05-26
    Keywords: A Palaeoreanalysis To Understand Decadal Climate Variability; Binary Object; DATE/TIME; ELEVATION; GlobCover; Identification; LATITUDE; LONGITUDE; PALAEO-RA; Station label; Uniform resource locator/link to source data file; Variable
    Type: Dataset
    Format: text/tab-separated-values, 17586 data points
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  • 4
    Publication Date: 2024-05-26
    Description: Multibeam bathymetry raw data was recorded in the North Atlantic during cruise SO276 MerMet 17-6 that took place between 2020-06-22 and 2020-07-26. The data was collected using the ship's own Kongsberg EM 122. Sound velocity profiles (SVP) were applied on the data for calibration. Please see environmental data (zip file) and the cruise report for details. The bathymetric data acquisition was carried out within the IceAge project which aims to investigate the North Atlantic ecosystem. Working areas have been selected to offer a variability of environments (e.g., variability of water depth, and geological setting (shelf, mid-ocean ridge, deep basin)). The bathymetric data were used to plan ROV dives and sampling stations as well as background for habitat mapping studies.
    Keywords: Binary Object; Binary Object (File Size); Binary Object (Media Type); Comment; Data file recording distance; Data file recording duration; DATE/TIME; ELEVATION; Event label; File content; iAtlantic; IceAge; Icelandic marine Animals: Genetics and Ecology; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; KEM122; Kongsberg datagram raw file name; KONGSBERG EM122; LATITUDE; LONGITUDE; MerMet 17-6; Norwegian Sea, Arctic Ocean; Number of pings; Ship speed; SO276; SO276_0_Underway-1; Sonne_2; Start of data file, depth; Start of data file, heading; Start of data file recording, date/time; Start of data file recording, latitude; Start of data file recording, longitude; Stop of data file, depth; Stop of data file, heading; Stop of data file recording, date/time; Stop of data file recording, latitude; Stop of data file recording, longitude
    Type: Dataset
    Format: text/tab-separated-values, 4002 data points
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  • 5
    Publication Date: 2024-05-26
    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; Particulate inorganic carbon/particulate organic carbon ratio; Particulate organic nitrogen per cell; 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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  • 6
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    Instituto de Investigaciones Marinas y Costeras "José Benito Vives de Andréis" | Santa Marta, Colombia
    Publication Date: 2024-05-25
    Description: En el inhóspito, Agreste y poco conocido Pacífico colombiano, se destaca un lugar especial por haberse constituido en el transcurso de las últimas dos décadas en epicentro de la investigación en biodiversidad marina: Isla Gorgona. Su condición insular y de Parque Nacional Natural hacen de ella, aunque poco accesible, un escenario ideal para la observación contemplativa y minuciosa de las muchas expresiones que la naturaleza ha sabido reunir allí, tanto en tierra como en las aguas que la circundan. Es lugar de paso obligado para grandes cetáceos y aves migratorias, posee formaciones coralinas que albergan una característica diversidad de peces e invertebrados, además de playas, acantilados, fondos de arena de roca que propician la coexistencia de variadas y contrastantes comunidades bióticas que han cautivado la atención de biólogos y estudiantes, lo que le ha valido el calificativo de "isla ciencia". Este libro da a conocer sus atributos naturales.
    Description: Published
    Description: Refereed
    Keywords: Peces marinos ; ASFA_2015::C::Coral reefs ; ASFA_2015::CComunidades coralinas ; ASFA_2015::AArrecifes coralinos ; ASFA_2015::E::Ecology
    Repository Name: AquaDocs
    Type: Book/Monograph/Conference Proceedings
    Format: 160pp.
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  • 7
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    Naturalis Biodiversity Center
    In:  Blumea: Biodiversity, Evolution and Biogeography of Plants vol. 65 no. 3, pp. 179-187
    Publication Date: 2024-05-25
    Description: During the preparation of the accounts of Artabotrys (Annonaceae) and Magnolia (Magnoliaceae) for the Flora of Singapore, the types of all relevant names were evaluated. New lectotypes are designated for A. suaveolens and M. maingayi and a second-step lectotypification is performed for M. elegans. The citation of a lectotype locality is corrected for A. costatus and the citation of an isolectotype is improved for A. maingayi. We also clarify the previous use of the term ‘type’ to designate specimens that are in fact lectotypes for several names in Magnolia.
    Keywords: Plant Science ; Ecology ; Evolution ; Behavior and Systematics ; Annonaceae ; Artabotrys ; lectotypification ; Magnoliaceae ; nomenclature ; Singapore
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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  • 8
    Publication Date: 2024-05-25
    Description: Palmitic acid (PA) is ubiquitous in the biosphere and its hydrogen isotopic composition (δ2HPA) was proposed as a potential paleoenvironmental proxy for salinity, with δ2HPA values increasing with salinity. In this study, we analyzed 40 surface sediment samples from Baffin Bay and the Labrador Sea to examine the isotopic composition of PA in relation to local environmental variables, including salinity. In contrast to expectations, our results show a negative relationship between the δ2HPA and sea-surface salinity, raising questions about its pertinence/usefulness as a salinity proxy. Instead, our results suggest that the relative abundance of distinct organisms that employ different metabolisms is key in determining the hydrogen isotopic fractionations in PA. Whereas we show that PA is mostly produced through photoautotrophic metabolisms by diatoms and dinoflagellates, varying contributions from heterotrophic metabolisms may obscure the stable isotope composition of PA. Surprisingly, we found no correlation between the stable carbon isotopic composition of the sedimentary organic matter (δ13Corg) and palmitic acid (δ13CPA), implying major differences in either the dominant organisms producing sedimentary PA or in carbon isotope fractionation during lipid biosynthesis. We also found that the presence of extended sea-ice cover leads to enriched carbon and hydrogen isotopic compositions in PA. These enriched values suggest heterotrophic biodegradation in the water column and/or in the sediment as well as an increase in grazing activities. We propose that sea-ice cover and surface water oxygenation modulate the relative impact of phototrophic and heterotrophic metabolisms, and therefore the isotopic composition of marine sedimentary PA.
    Keywords: Average chain length; Baffin Bay; BC; Bottom water salinity, annual mean; Bottom water temperature; Box corer; Carbon; Carbon, inorganic, total; Carbon, organic; Carbon isotopes; Carbon organic/Nitrogen, molar ratio; Carbon Preference Index; Davis Strait; DB3.02; DB3.08; DB3.10; DB3.14; DB3.31; DB3.32; DB3.34; DB3.35; DB6.02; DB6.04; DB6.05; DB6.07; DB6.08; DB6.09; DEPTH, sediment/rock; Dinoflagellate cyst, heterotrophic; Dinoflagellate cyst, per unit sediment mass; Dinoflagellate cyst, phototrophic; Event label; FB1.02; FB1.07; GeoB22315-3; GeoB22318-1; GeoB22319-1; GeoB22344-2; GeoB22350-2; GeoB22353-2; GeoB22356-2; GeoB22358-2; Grab; GRAB; HB2.04; Hexadecanoic acid, δ13C; Hexadecanoic acid, δ13C, standard deviation; Hudson Strait; Hydrogen isotopes; Labrador Sea; lipid biomarkers; Maria S. Merian; MSM45; MSM45_002-4; MSM45_009-3; MSM45_030-3; MSM45_401-4; MSM45_408-3; MSM45_417-3; MSM45_424-3; MSM45_430-3; MSM45-018-3; MSM45-024-3; MSM46; MSM46_11-5; MSM46_14-2; MSM46_25-1; MSM46_28-3; MSM66; MSM66/15-3; MSM66/18-1; MSM66/19-1; MSM66/44-2; MSM66/50-2; MSM66/53-2; MSM66/56-2; MSM66/58-2; MUC; MultiCorer; n-fatty acid C16, per unit mass total organic carbon; n-fatty acid C16, per unit sediment mass; n-fatty acid C16:1, per unit mass total organic carbon; n-fatty acid C16:1, per unit sediment mass; n-fatty acid C18, per unit mass total organic carbon; n-fatty acid C18, per unit sediment mass; n-fatty acid C18:1, per unit mass total organic carbon; n-fatty acid C18:1, per unit sediment mass; n-fatty acid C18:2, per unit mass total organic carbon; n-fatty acid C18:2, per unit sediment mass; Nitrate; Nitrogen; Oxygen, apparent utilization; Oxygen saturation; Paamiut; Paamiut2014; Palmitic acid; Palynomorpha, reworked per unit sediment mass; Phosphate; Pollen, per unit sediment mass; Primary production of carbon per area, yearly; Q7.03; Q7.04; Ratio; Saturated fatty acids, per unit mass total organic carbon; Saturated fatty acids, per unit sediment mass; Sea ice cover duration; Sea surface salinity, annual mean; Sea surface salinity, summer; Sea surface salinity, winter; Sea surface temperature, annual mean; Sea surface temperature, summer; Sea surface temperature, winter; Silicate; Site; Spores per unit sediment mass; U5.04; U5.10; U5.14; V4.03; δ13C, organic carbon; δ18O, water; δ Deuterium, palmitic acid; δ Deuterium, palmitic acid, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 2194 data points
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  • 9
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    PANGAEA
    In:  GEOMAR - Helmholtz Centre for Ocean Research Kiel
    Publication Date: 2024-05-25
    Description: Raw data acquired by position sensors on board RV MERIAN during expedition MSM123 were processed to receive a validated master track which can be used as reference of further expedition data. During MSM123 the motion reference unit Kongsberg SeaTex AS MRU-5 combined with Kongsberg SeaTex AS Seapath 320 and the GPS receivers Trimble SPS855 and SAAB R4 were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.bsh.de) with a resolution of 1 sec. Processing and evaluation of the data is outlined in the data processing report. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
    Keywords: 1 sec resolution; BELS; CT; DAM_Underway; DAM Underway Research Data; Maria S. Merian; MSM123; MSM123-track; Underway cruise track measurements
    Type: Dataset
    Format: application/zip, 121.8 MBytes
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  • 10
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    PANGAEA
    In:  GEOMAR - Helmholtz Centre for Ocean Research Kiel
    Publication Date: 2024-05-25
    Description: Raw data acquired by position sensors on board RV METEOR during expedition M198 were processed to receive a validated master track which can be used as reference of further expedition data. During M198 the motion reference unit Kongsberg SeaTex AS MRU-5 combined with Kongsberg SeaTex AS Seapath 320 and two C and C Technologies GPS receivers C-NAV3050 were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.bsh.de) with a resolution of 1 sec. Processing and evaluation of the data is outlined in the data processing report. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
    Keywords: Calculated; Course; CT; DAM_Underway; DAM Underway Research Data; DATE/TIME; LATITUDE; LONGITUDE; M198; M198-track; Meteor (1986); MIDES; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 3742 data points
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  • 11
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    PANGAEA
    In:  Max Planck Institute for Marine Microbiology
    Publication Date: 2024-05-25
    Description: Raw data acquired by position sensors on board RV MERIAN during expedition MSM125 were processed to receive a validated master track which can be used as reference of further expedition data. During MSM125 the motion reference unit Kongsberg SeaTex AS MRU-5 combined with Kongsberg SeaTex AS Seapath 320 and the GPS receivers Trimble SPS855 and SAAB R4 were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.bsh.de) with a resolution of 1 sec. Processing and evaluation of the data is outlined in the data processing report. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
    Keywords: 1 sec resolution; CT; DAM_Underway; DAM Underway Research Data; EqTestGOC; Maria S. Merian; MSM125; MSM125-track; Underway cruise track measurements
    Type: Dataset
    Format: application/zip, 25.8 MBytes
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  • 12
    Publication Date: 2024-05-25
    Description: The dataset presents the greenhouse gas production (CO2 and CH4) from sediment of a terrestrial permafrost outcrop (Byk14-A-1; 71.85175°N, 129.350883°E), the thermokarst lake Goltsovoye (PG2412 (TKL), 71.74515°N, 129.30217°E), the nearly-closed Polar Fox Lagoon (PG2411 (LAG1), 71.743056°N, 129.337778°E) and the semi-open Uomullyakh Lagoon (PG2410-1 (LAG1), 71.730833°N, 129.2725°E). We incubated the samples anaerobically at 4 °C under fresh (c=0 g/L), brackish (c=13g/L) and marine (36g/L) conditions for one year and measured carbon dioxide (CO2) and methane (CH4) concentrations regularly in a 250 µL subsample using gas chromatography with an Agilent GC 7890A equipped with an Agilent HP-PLOT Q column. Cumulative CO2 and CH4 concentrations and production rates per day are given over time for all samples with three replicates each per gram of dry weight and normalised to gram of soil organic carbon (SOC).
    Keywords: Anaerobic incubation; Arctic permafrost coasts; AWI Arctic Land Expedition; Bykovsky_2017_spring; Carbon dioxide, production, anaerobic, per mass soil organic carbon; Carbon dioxide, production, anaerobic, per soil dry mass; Carbon dioxide, production rate, per mass soil organic carbon; Carbon dioxide, production rate, per soil dry mass; carbon dioxide production; Core; Date; Day of experiment; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Event label; EXPO; Exposure; Goltsovoye Lake, Siberia, Russia; Laboratory experiment; Lena_Delta_Sobo-Byk_2014; Methane, production, anaerobic, per mass soil organic carbon; Methane, production, anaerobic, per soil dry mass; Methane, production rate, per mass soil organic carbon; Methane, production rate, per soil dry mass; methane production; Mobile drilling rig, Geotechnika, URB-4T; PETA-CARB; PG2410-1; PG2411-1; PG2412-1; PG-BYK14-1-A; Polar Fox Lagoon; Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool; Replicate; RU-Land_2014_Lena_Sobo-Byk; RU-Land_2017_Lena_Bykovsky; Sample ID; Sediment type; thermokarst lagoon formation; thermokarst lakes; Treatment; Type of study; Uomullyakh Lagoon
    Type: Dataset
    Format: text/tab-separated-values, 18900 data points
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  • 13
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    PANGAEA
    In:  GEOMAR - Helmholtz Centre for Ocean Research Kiel
    Publication Date: 2024-05-25
    Description: Raw data acquired by position sensors on board RV METEOR during expedition M198 were processed to receive a validated master track which can be used as reference of further expedition data. During M198 the motion reference unit Kongsberg SeaTex AS MRU-5 combined with Kongsberg SeaTex AS Seapath 320 and two C and C Technologies GPS receivers C-NAV3050 were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.bsh.de) with a resolution of 1 sec. Processing and evaluation of the data is outlined in the data processing report. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
    Keywords: 1 sec resolution; CT; DAM_Underway; DAM Underway Research Data; M198; M198-track; Meteor (1986); MIDES; Underway cruise track measurements
    Type: Dataset
    Format: application/zip, 47.1 MBytes
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  • 14
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    PANGAEA
    In:  GEOMAR - Helmholtz Centre for Ocean Research Kiel
    Publication Date: 2024-05-25
    Description: Raw data acquired by position sensors on board RV MERIAN during expedition MSM123 were processed to receive a validated master track which can be used as reference of further expedition data. During MSM123 the motion reference unit Kongsberg SeaTex AS MRU-5 combined with Kongsberg SeaTex AS Seapath 320 and the GPS receivers Trimble SPS855 and SAAB R4 were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.bsh.de) with a resolution of 1 sec. Processing and evaluation of the data is outlined in the data processing report. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
    Keywords: BELS; Calculated; Course; CT; DAM_Underway; DAM Underway Research Data; DATE/TIME; LATITUDE; LONGITUDE; Maria S. Merian; MSM123; MSM123-track; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 9432 data points
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  • 15
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    PANGAEA
    In:  Max Planck Institute for Marine Microbiology
    Publication Date: 2024-05-25
    Description: Raw data acquired by position sensors on board RV MERIAN during expedition MSM125 were processed to receive a validated master track which can be used as reference of further expedition data. During MSM125 the motion reference unit Kongsberg SeaTex AS MRU-5 combined with Kongsberg SeaTex AS Seapath 320 and the GPS receivers Trimble SPS855 and SAAB R4 were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.bsh.de) with a resolution of 1 sec. Processing and evaluation of the data is outlined in the data processing report. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
    Keywords: Calculated; Course; CT; DAM_Underway; DAM Underway Research Data; DATE/TIME; EqTestGOC; LATITUDE; LONGITUDE; Maria S. Merian; MSM125; MSM125-track; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 2032 data points
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  • 16
    Publication Date: 2024-05-25
    Keywords: 2,6,10,14-Tetramethyl-7-(3-methylpent-4-enyl)pentadecane, per unit mass total organic carbon; 24-Methylcholesta-5,22E-dien-3beta-ol, per unit mass total organic carbon; 4alpha,23,24-Trimethyl-5alpha-cholest-22E-en-3beta-ol, per unit mass total organic carbon; AMD14; AMD14_101; AMD14_115; AMD14_200; Arctic Ocean; ARK-XXIX/2.1; ARK-XXVIII/4 ALEX2014; ARK-XXXI/4; Baffin Bay; BC; Box corer; Carbon, organic, total; CCGS Amundsen; Core; CORE; CORIBAR; Davis Strait; DB3.02; DB3.08; DB3.10; DB3.11; DB3.12; DB3.13; DB3.14; DB3.15; DB3.16; DB3.20; DB3.23; DB3.24; DB3.25; DB3.26; DB3.27; DB3.30; DB3.31; DB3.32; DB3.33; DB3.34; DB3.35; DB3.36; DB3.37; DB3.39; DB3.42; DB6.01; DB6.02; DB6.05; DB6.06; DB6.07; DB6.08; DB6.09; EGS-1; Event label; FB1.02; FB1.04; FB1.05; FB1.07; FB1.12; FRAM-2014/15_ice_drift; FRAM2014/15-08-06; FRAM2014/15-11-09; FRAM2014/15-13-11; FRAM2014/15-15-13; FRAM2014/15-15-14; FRAM2014/15-15-15; FRAM2014/15-15-16; FRAM2014/15-15-17; FRAM2014/15-15-18; G. O. Sars (2003); GC; GeoB17601-2; GeoB17602-1; GeoB17603-1; GeoB17604-1; GeoB17605-1; GeoB17606-1; GeoB17607-1; GeoB17608-1; GeoB17609-1; GeoB17609-3; GeoB17610-1; GeoB17611-2; GeoB17612-1; GeoB17613-1; GeoB17614-1; GeoB17615-1; GeoB17616-1; GeoB17617-1; GeoB17618-1; GeoB17619-1; GeoB17620-1; GeoB17621-1; GeoB17622-1; GeoB17623-1; GeoB19904-1; GeoB19905-2; GeoB19916-5; GeoB19920-4; GeoB19927-2; GeoB19931-2; GeoB19933-2; GeoB19940-3; GeoB19946-3; GeoB19948-2; GeoB19953-5; GeoB19959-3; GeoB19961-2; GeoB19963-2; GeoB19969-2; GeoB19973-3; GeoB22304-4; GeoB22305-2; GeoB22306-2; GeoB22315-3; GeoB22316-1; GeoB22317-1; GeoB22318-1; GeoB22319-1; GeoB22320-1; GeoB22321-1; GeoB22329-3; GeoB22331-2; GeoB22333-3; GeoB22334-1; GeoB22336-2; GeoB22344-2; GeoB22346-2; GeoB22348-2; GeoB22350-2; GeoB22351-2; GeoB22353-2; GeoB22356-2; GeoB22357-2; GeoB22358-2; GeoB22359-2; Giant box corer; GKG; Gravity corer; Greenland Sea; GS15-198-36; GS15-198-37; GS15-198-38; GS15-198-39; GS15-198-40; GS15-198-41; GS15-198-42; GS15-198-43; GS15-198-44; GS15-198-45; GS15-198-46; GS15-198-47; GS15-198-48; GS15-198-49; GS15-198-50; GS15-198-51; GS15-198-52; GS15-198-53; GS15-198-54; GS15-198-55; GS15-198-56; GS15-198-58; GS15-198-59; GS15-198-60; GS15-198-61; GS15-198-62; GS15-198-63; GS16-204-19; GS16-204-21; GS16-204-22; GS16-204-23; GS16-204-24; GS2015-198; GS2016-204; HB2.01; HB2.02; HB2.03; HB2.04; HB2.06; Heat-Flow probe; HF; Highly branched isoprenoids, diunsatured, per unit mass total organic carbon; Highly branched isoprenoids (E), triunsatured, per unit mass total organic carbon; Highly branched isoprenoids (Z), triunsatured, per unit mass total organic carbon; HUD2008/29; HUD2008/29_14; HUD2008/29_47; HUD2008/29_55; HUD2008/29_66; HUD2013/29; HUD2013/29_51; HUD2013/29_52; HUD2013/29_54; HUD2013/29_68; HUD2013/29_78; HUD2013/29_79; Hudson; Labrador Sea; LATITUDE; LONGITUDE; Maria S. Merian; MOOR; Mooring; MSM12/2; MSM12/2_642-2; MSM12/2_643-2; MSM12/2_645-3; MSM12/2_646-2; MSM12/2_647-1; MSM12/2_649-4; MSM12/2_650-2; MSM12/2_651-2; MSM12/2_653-3; MSM12/2_654-1; MSM12/2_656-2; MSM12/2-01-02; MSM12/2-02-02; MSM12/2-03-02; MSM12/2-04-02; MSM12/2-05-01; MSM12/2-06-03; MSM12/2-07-01; MSM12/2-08-02; MSM12/2-09-02; MSM12/2-10-01; MSM12/2-12-02; MSM30; MSM30_463-2; MSM30_466-1; MSM30_467-1; MSM30_469-1; MSM30_471-1; MSM30_472-1; MSM30_474-1; MSM30_476-1; MSM30_477-1; MSM30_477-3; MSM30_479-1; MSM30_480-2; MSM30_482-1; MSM30_483-1; MSM30_485-1; MSM30_486-1; MSM30_488-1; MSM30_490-2; MSM30_493-1; MSM30_499-1; MSM30_500-1; MSM30_501-1; MSM30_502-1; MSM30_503-1; MSM31; MSM31_550-5; MSM31_557-2; MSM31_561-2; MSM31_575-3; MSM31_585-4; MSM44; MSM44_330-1; MSM44_331-2; MSM44_342-5; MSM44_346-4; MSM44_353-2; MSM44_357-2; MSM44_359-2; MSM44_366-3; MSM44_372-3; MSM44_374-2; MSM44_379-5; MSM44_385-3; MSM44_387-2; MSM44_389-2; MSM44_395-2; MSM44_399-3; MSM46; MSM46_10-8; MSM46_12-5; MSM46_14-2; MSM46_16-6; MSM46_19-3; MSM46_20-3; MSM46_22-2; MSM46_25-1; MSM46_28-3; MSM46_3-5; MSM46_4-5; MSM46_5-8; MSM46_6-4; MSM46_7-10; MSM66; MSM66/05-2; MSM66/15-3; MSM66/16-1; MSM66/17-1; MSM66/18-1; MSM66/19-1; MSM66/20-1; MSM66/21-1; MSM66/29-3; MSM66/31-2; MSM66/33-3; MSM66/34-1; MSM66/36-2; MSM66/4-4; MSM66/44-2; MSM66/46-2; MSM66/48-2; MSM66/50-2; MSM66/51-2; MSM66/53-2; MSM66/56-2; MSM66/57-2; MSM66/58-2; MSM66/59-2; MSM66/6-2; MUC; MultiCorer; Multicorer with television; North Greenland Sea; Norwegian Sea; Paamiut; Paamiut2014; Polarstern; PS109; PS109_105-1; PS109_115-2; PS109_125-1; PS109_129-1; PS109_139-1; PS109_19-2; PS109_36-2; PS109_46-2; PS109_76-1; PS109_85-1; PS109_93-2; PS115/1; PS115/1_10-1; PS115/1_17-2; PS115/1_18-1; PS115/1_19-2; PS115/1_21-1; PS115/1_22-2; PS115/1_26-1; PS115/1_4-2; PS115/1_47-1; PS115/1_48-1; PS115/1_50-1; PS115/1_51-1; PS115/1_52-2; PS115/1_6-1; PS115/1_7-1; PS115/1_9-4; PS87; PS87/029-3; PS87/030-3; PS87/035-3; PS87/040-3; PS87/067-3; PS87/068-3; PS87/070-3; PS87/074-2; PS87/076-3; PS87/079-3; PS87/086-2; PS87/099-4; PS93/011-4; PS93/016-5; PS93/017-5; PS93/018-4; PS93/020-5; PS93/023-4; PS93/024-6; PS93/030-4; PS93/031-1; PS93/039-7; PS93/041-2; PS93/046-4; PS93.1; Q7.01; Q7.03; Q7.04; Q7.07; Sabvabba; South Atlantic Ocean; Station label; TVMUC; U5.04; U5.05; U5.08; U5.09; U5.10; U5.14; U5.15; V4.01; V4.02; V4.03; V4.04
    Type: Dataset
    Format: text/tab-separated-values, 2046 data points
    Location Call Number Expected Availability
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  • 17
    Publication Date: 2024-05-25
    Keywords: (9E)-2,6,10,14-Tetramethyl-7-(3-methylpent-4-enyliden)pentadeca-9-ene per unit sediment mass; (9Z)-2,6,10,14-Tetramethyl-7-(3-methylpent-4-enyliden)pentadeca-9-ene per unit sediment mass; 2,10,14-Trimethyl-6-enyl-7-(3-methylpent-1-enyl)pentadecene/2,6,10,14-Tetramethyl-7-(3-methylpent-4-enyl)pentadecane ratio; 2,10,14-Trimethyl-6-enyl-7-(3-methylpent-1-enyl)pentadecene per unit sediment mass; 2,6,10,14-Tetramethyl-7-(3-methylpent-4-enyl)pentadecane per unit sediment mass; 24-Methylcholesta-5,22E-dien-3beta-ol per unit sediment mass; 4alpha,23,24-Trimethyl-5alpha-cholest-22E-en-3beta-ol per unit sediment mass; AMD14; AMD14_101; AMD14_115; AMD14_200; Arctic Ocean; ARK-XXIX/2.1; ARK-XXVIII/4 ALEX2014; ARK-XXXI/4; Baffin Bay; BC; Box corer; CCGS Amundsen; Core; CORE; CORIBAR; Davis Strait; DB3.02; DB3.08; DB3.10; DB3.11; DB3.12; DB3.13; DB3.14; DB3.15; DB3.16; DB3.20; DB3.23; DB3.24; DB3.25; DB3.26; DB3.27; DB3.30; DB3.31; DB3.32; DB3.33; DB3.34; DB3.35; DB3.36; DB3.37; DB3.39; DB3.42; DB6.01; DB6.02; DB6.05; DB6.06; DB6.07; DB6.08; DB6.09; EGS-1; Event label; FB1.02; FB1.04; FB1.05; FB1.07; FB1.12; FRAM-2014/15_ice_drift; FRAM2014/15-08-06; FRAM2014/15-11-09; FRAM2014/15-13-11; FRAM2014/15-15-13; FRAM2014/15-15-14; FRAM2014/15-15-15; FRAM2014/15-15-16; FRAM2014/15-15-17; FRAM2014/15-15-18; G. O. Sars (2003); GC; GeoB17601-2; GeoB17602-1; GeoB17603-1; GeoB17604-1; GeoB17605-1; GeoB17606-1; GeoB17607-1; GeoB17608-1; GeoB17609-1; GeoB17609-3; GeoB17610-1; GeoB17611-2; GeoB17612-1; GeoB17613-1; GeoB17614-1; GeoB17615-1; GeoB17616-1; GeoB17617-1; GeoB17618-1; GeoB17619-1; GeoB17620-1; GeoB17621-1; GeoB17622-1; GeoB17623-1; GeoB19904-1; GeoB19905-2; GeoB19916-5; GeoB19920-4; GeoB19927-2; GeoB19931-2; GeoB19933-2; GeoB19940-3; GeoB19946-3; GeoB19948-2; GeoB19953-5; GeoB19959-3; GeoB19961-2; GeoB19963-2; GeoB19969-2; GeoB19973-3; GeoB22304-4; GeoB22305-2; GeoB22306-2; GeoB22315-3; GeoB22316-1; GeoB22317-1; GeoB22318-1; GeoB22319-1; GeoB22320-1; GeoB22321-1; GeoB22329-3; GeoB22331-2; GeoB22333-3; GeoB22334-1; GeoB22336-2; GeoB22344-2; GeoB22346-2; GeoB22348-2; GeoB22350-2; GeoB22351-2; GeoB22353-2; GeoB22356-2; GeoB22357-2; GeoB22358-2; GeoB22359-2; Giant box corer; GKG; Gravity corer; Greenland Sea; GS15-198-36; GS15-198-37; GS15-198-38; GS15-198-39; GS15-198-40; GS15-198-41; GS15-198-42; GS15-198-43; GS15-198-44; GS15-198-45; GS15-198-46; GS15-198-47; GS15-198-48; GS15-198-49; GS15-198-50; GS15-198-51; GS15-198-52; GS15-198-53; GS15-198-54; GS15-198-55; GS15-198-56; GS15-198-58; GS15-198-59; GS15-198-60; GS15-198-61; GS15-198-62; GS15-198-63; GS16-204-19; GS16-204-21; GS16-204-22; GS16-204-23; GS16-204-24; GS2015-198; GS2016-204; HB2.01; HB2.02; HB2.03; HB2.04; HB2.06; Heat-Flow probe; HF; HUD2008/29; HUD2008/29_14; HUD2008/29_47; HUD2008/29_55; HUD2008/29_66; HUD2013/29; HUD2013/29_51; HUD2013/29_52; HUD2013/29_54; HUD2013/29_68; HUD2013/29_78; HUD2013/29_79; Hudson; Labrador Sea; LATITUDE; LONGITUDE; Maria S. Merian; MOOR; Mooring; MSM12/2; MSM12/2_642-2; MSM12/2_643-2; MSM12/2_645-3; MSM12/2_646-2; MSM12/2_647-1; MSM12/2_649-4; MSM12/2_650-2; MSM12/2_651-2; MSM12/2_653-3; MSM12/2_654-1; MSM12/2_656-2; MSM12/2-01-02; MSM12/2-02-02; MSM12/2-03-02; MSM12/2-04-02; MSM12/2-05-01; MSM12/2-06-03; MSM12/2-07-01; MSM12/2-08-02; MSM12/2-09-02; MSM12/2-10-01; MSM12/2-12-02; MSM30; MSM30_463-2; MSM30_466-1; MSM30_467-1; MSM30_469-1; MSM30_471-1; MSM30_472-1; MSM30_474-1; MSM30_476-1; MSM30_477-1; MSM30_477-3; MSM30_479-1; MSM30_480-2; MSM30_482-1; MSM30_483-1; MSM30_485-1; MSM30_486-1; MSM30_488-1; MSM30_490-2; MSM30_493-1; MSM30_499-1; MSM30_500-1; MSM30_501-1; MSM30_502-1; MSM30_503-1; MSM31; MSM31_550-5; MSM31_557-2; MSM31_561-2; MSM31_575-3; MSM31_585-4; MSM44; MSM44_330-1; MSM44_331-2; MSM44_342-5; MSM44_346-4; MSM44_353-2; MSM44_357-2; MSM44_359-2; MSM44_366-3; MSM44_372-3; MSM44_374-2; MSM44_379-5; MSM44_385-3; MSM44_387-2; MSM44_389-2; MSM44_395-2; MSM44_399-3; MSM46; MSM46_10-8; MSM46_12-5; MSM46_14-2; MSM46_16-6; MSM46_19-3; MSM46_20-3; MSM46_22-2; MSM46_25-1; MSM46_28-3; MSM46_3-5; MSM46_4-5; MSM46_5-8; MSM46_6-4; MSM46_7-10; MSM66; MSM66/05-2; MSM66/15-3; MSM66/16-1; MSM66/17-1; MSM66/18-1; MSM66/19-1; MSM66/20-1; MSM66/21-1; MSM66/29-3; MSM66/31-2; MSM66/33-3; MSM66/34-1; MSM66/36-2; MSM66/4-4; MSM66/44-2; MSM66/46-2; MSM66/48-2; MSM66/50-2; MSM66/51-2; MSM66/53-2; MSM66/56-2; MSM66/57-2; MSM66/58-2; MSM66/59-2; MSM66/6-2; MUC; MultiCorer; Multicorer with television; North Greenland Sea; Norwegian Sea; Paamiut; Paamiut2014; Phytoplankton biomarker Brassicasterol IP25 index; Phytoplankton biomarker C25 HBI (Z) triene IP25 index; Phytoplankton biomarker Dinosterol IP25 index; Phytoplankton biomarker HBI TR25 index; Polarstern; PS109; PS109_105-1; PS109_115-2; PS109_125-1; PS109_129-1; PS109_139-1; PS109_19-2; PS109_36-2; PS109_46-2; PS109_76-1; PS109_85-1; PS109_93-2; PS115/1; PS115/1_10-1; PS115/1_17-2; PS115/1_18-1; PS115/1_19-2; PS115/1_21-1; PS115/1_22-2; PS115/1_26-1; PS115/1_4-2; PS115/1_47-1; PS115/1_48-1; PS115/1_50-1; PS115/1_51-1; PS115/1_52-2; PS115/1_6-1; PS115/1_7-1; PS115/1_9-4; PS87; PS87/029-3; PS87/030-3; PS87/035-3; PS87/040-3; PS87/067-3; PS87/068-3; PS87/070-3; PS87/074-2; PS87/076-3; PS87/079-3; PS87/086-2; PS87/099-4; PS93/011-4; PS93/016-5; PS93/017-5; PS93/018-4; PS93/020-5; PS93/023-4; PS93/024-6; PS93/030-4; PS93/031-1; PS93/039-7; PS93/041-2; PS93/046-4; PS93.1; Q7.01; Q7.03; Q7.04; Q7.07; Sabvabba; South Atlantic Ocean; Station label; TVMUC; U5.04; U5.05; U5.08; U5.09; U5.10; U5.14; U5.15; V4.01; V4.02; V4.03; V4.04
    Type: Dataset
    Format: text/tab-separated-values, 2993 data points
    Location Call Number Expected Availability
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  • 18
    Publication Date: 2024-05-25
    Keywords: Akademik Boris Petrov; AMD14; AMD14_101; AMD14_115; AMD14_200; ARA2B; ARA2B-11_BOX-01; ARA2B-15; ARA2B-16a_BOX-01; ARA2B-16B; ARA2B-18A; ARA2B-18B; ARA2B-1A; ARA2B-1B; ARA2B-2; ARA2B-3A; ARA2B-3B; ARA2B-8_BOX-01; ARA2B-9_BOX-01; ARA3B; ARA3B_01; ARA3B_08MUC-02; ARA3B_09MUC-02; ARA3B_10MUC-02; ARA3B_11MUC-02; ARA3B_12; ARA3B_13MUC-01; ARA3B_14MUC-01; ARA3B_15b; ARA3B_16MUC-01; ARA3B_18MUC-01; ARA3B_19MUC-02; ARA3B_26; ARA3B_27; ARA3B_28; ARA3B_29MUC-02; ARA3B_30MUC-01; ARA3B_38aMUC-01; ARA3B_41MUC-03; Araon; ARC/ASP13_Tyro-5; ARC/ASP13_YS163; ARC/ASP14_Tyro-8; ARC/ASP14_YS3.14; ARC/IGN15_SD60; ARC/IGN15_Tyro-100; ARC/IGN15_YS3.18; ARC/IGN15_YSD; ARC/IGN15_Z60; ARC-1; ARC-2; ARC-3; ARC-4; ARC-5; ARC-6; ARC-7; ARC-8; ArcticNet2005; ArcticNet2005_ARC-1; ArcticNet2005_ARC-2; ArcticNet2005_ARC-3; ArcticNet2005_ARC-4; ArcticNet2005_ARC-5; ArcticNet2005_ARC-6; ArcticNet2005_ARC-7; ArcticNet2005_ARC-8; Arctic Ocean; ARK-VIII/2; ARK-X/2; ARK-XI/1; ARK-XIV/1a; ARK-XIX/4a; ARK-XV/2; ARK-XVI/1; ARK-XVI/2; ARK-XVII/1; ARK-XVII/2; ARK-XVIII/1; ARK-XXIX/2.1; ARK-XXVI/3; ARK-XXVII/3; ARK-XXVIII/4 ALEX2014; ARK-XXXI/4; Baffin Bay; Barents_625; Barents_627; Barents_629; Barents_631; Barents_633; Barents_635; Barents_639; Barents_643; Barents_645; Barents_647; Barents_649; Barents_651; Barents_653; Barents_655; Barents_657; Barents_659; Barents_661; Barents_663; Barents_665; Barents_667; Barents_669; Barents_671; Barents_673; Barents_675; Barents_677; Barents_679; Barents_681; Barents_690; Barents_692; Barents_St02; Barents_St03; Barents_St04; Barents_St06; Barents_St07; Barents_St09; Barents_St11; Barents_St12; Barents_St13; Barents_St14; Barents_St15; Barents_St17; Barents_St18; Barents_St19; Barents_St20; Barents_St21; Barents_St22; Barents_St23; Barents_St24; Barents_St25; Barents_St26; Barents_St27; Barents_St29; Barents_St30; Barents_St31; Barents_St32; Barents_St34; Barents_St35; Barents_St36; Barents_St37; Barents_St38; Barents_St39; Barents_St40; Barents_St41; Barents_St43; Barents_St44; Barents_St45; Barents Sea; BC; Bering Sea; Box corer; BP00; BP00-02; BP00-04; BP00-05; BP00-07; BP00-08; BP00-09; BP00-13; BP00-14; BP00-15; BP00-16; BP00-17; BP00-22; BP00-23; BP00-26; BP00-27; BP00-28; BP00-29; BP00-30; BP00-31; BP00-35; BP00-36; BP00-38; BP01; BP01-38; BP01-43; BP01-64; BP01-67; BP01-73a; BP01-74; BP01-75; BP01-76; BP01-78; BP01-79; BP02; BP02-01B; BP02-02B; BP02-03/01; BP02-05/01; BUCKET; Bucket water sampling; CCGS Amundsen; Core; CORE; CORIBAR; CTD/Rosette; CTD-RO; Davis Strait; DB3.02; DB3.08; DB3.10; DB3.11; DB3.12; DB3.13; DB3.14; DB3.15; DB3.16; DB3.20; DB3.23; DB3.24; DB3.25; DB3.26; DB3.27; DB3.30; DB3.31; DB3.32; DB3.33; DB3.34; DB3.35; DB3.36; DB3.37; DB3.39; DB3.42; DB6.01; DB6.02; DB6.05; DB6.06; DB6.07; DB6.08; DB6.09; DEPTH, water; Dredge; DRG; East Greenland Sea; East Siberian Sea; EGS-1; Event label; FB1.02; FB1.04; FB1.05; FB1.07; FB1.12; FRAM-2014/15_ice_drift; FRAM2014/15-08-06; FRAM2014/15-11-09; FRAM2014/15-13-11; FRAM2014/15-15-13; FRAM2014/15-15-14; FRAM2014/15-15-15; FRAM2014/15-15-16; FRAM2014/15-15-17; FRAM2014/15-15-18; G. O. Sars (2003); GC; GeoB17601-2; GeoB17602-1; GeoB17603-1; GeoB17604-1; GeoB17605-1; GeoB17606-1; GeoB17607-1; GeoB17608-1; GeoB17609-1; GeoB17609-3; GeoB17610-1; GeoB17611-2; GeoB17612-1; GeoB17613-1; GeoB17614-1; GeoB17615-1; GeoB17616-1; GeoB17617-1; GeoB17618-1; GeoB17619-1; GeoB17620-1; GeoB17621-1; GeoB17622-1; GeoB17623-1; GeoB19904-1; GeoB19905-2; GeoB19916-5; GeoB19920-4; GeoB19927-2; GeoB19931-2; GeoB19933-2; GeoB19940-3; GeoB19946-3; GeoB19948-2; GeoB19953-5; GeoB19959-3; GeoB19961-2; GeoB19963-2; GeoB19969-2; GeoB19973-3; GeoB22304-4; GeoB22305-2; GeoB22306-2; GeoB22315-3; GeoB22316-1; GeoB22317-1; GeoB22318-1; GeoB22319-1; GeoB22320-1; GeoB22321-1; GeoB22329-3; GeoB22331-2; GeoB22333-3; GeoB22334-1; GeoB22336-2; GeoB22344-2; GeoB22346-2; GeoB22348-2; GeoB22350-2; GeoB22351-2; GeoB22353-2; GeoB22356-2; GeoB22357-2; GeoB22358-2; GeoB22359-2; Giant box corer; GKG; Gravity corer; Gravity corer (Kiel type); Greenland Sea; GS15-198-36; GS15-198-37; GS15-198-38; GS15-198-39; GS15-198-40; GS15-198-41; GS15-198-42; GS15-198-43; GS15-198-44; GS15-198-45; GS15-198-46; GS15-198-47; GS15-198-48; GS15-198-49; GS15-198-50; GS15-198-51; GS15-198-52; GS15-198-53; GS15-198-54; GS15-198-55; GS15-198-56; GS15-198-58; GS15-198-59; GS15-198-60; GS15-198-61; GS15-198-62; GS15-198-63; GS16-204-19; GS16-204-21; GS16-204-22; GS16-204-23; GS16-204-24; GS2015-198; GS2016-204; HB2.01; HB2.02; HB2.03; HB2.04; HB2.06; HE153; HE153/1239-2; HE153/1241-1; HE153/1251-2; HE153/1254-2; HE153/1255-2; HE153/1261-2; HE153/1262-2; HE153/1263-2; HE153/1265-2; HE153/1269-2; HE153/1270-2; HE153/1273-2; HE153/1286-2; HE153/1287-2; HE153/1288-2; HE153/1289-2; HE153/1290-2; Heincke; Helmer Hanssen; HG_I; HG_II; HG_IV; HG_IX; HH11; HH11-133GC; HH11-134BC; HH11-135GC; HH11-136BC; HH11-137BC; HH11-138GC; HH11-140BC; HH13-19; HH13-21; HH13-23E; HH13-25F; HH2011; HH2013; HUD2008/29; HUD2008/29_14; HUD2008/29_47; HUD2008/29_55; HUD2008/29_66; HUD2013/29; HUD2013/29_51; HUD2013/29_52; HUD2013/29_54; HUD2013/29_68; HUD2013/29_78; HUD2013/29_79; Hudson; Hudson Bay; Hurry Inlet, East Greenland; Iceland Sea; INOPEX; Investigator; James Clark Ross; JR142; JR142-GC10; JR142-GC11; JR142-GC12; JR142-GC13; JR142-GC14; JR142-GC15; JR142-GC17; JR142-GC19; JR142-GC20; JR142-GC21; JR142-GC22; JR142-GC23; JR142-GC4; JR142-GC5; JR142-GC6; JR142-GC7; JR142-GC8; JR142-GC9; JR20060728; JR20080823; JR211; JR211-04GC; JR211-10BC; JR211-12GC; JR211-13GC; JR211-15GC; JR211-26GC; JR211-28GC; JR211-33GC; KAL; Kapitan Dranitsyn; Kara Sea; Kasten corer; KD9523-8; KD9529-12; KD9533-11; KD9541-13; KD9548-13; KD9565-12; KD9568-8; KD9572-1; Kempe Fjord, East Greenland; Labrador Sea; Laptev Sea; LATITUDE; LONGITUDE; Maria S. Merian; MOOR; Mooring; MSM12/2; MSM12/2_642-2; MSM12/2_643-2; MSM12/2_645-3; MSM12/2_646-2; MSM12/2_647-1; MSM12/2_649-4; MSM12/2_650-2; MSM12/2_651-2; MSM12/2_653-3; MSM12/2_654-1; MSM12/2_656-2; MSM12/2-01-02; MSM12/2-02-02; MSM12/2-03-02; MSM12/2-04-02; MSM12/2-05-01; MSM12/2-06-03; MSM12/2-07-01; MSM12/2-08-02; MSM12/2-09-02; MSM12/2-10-01; MSM12/2-12-02; MSM30; MSM30_463-2; MSM30_466-1; MSM30_467-1; MSM30_469-1; MSM30_471-1; MSM30_472-1; MSM30_474-1; MSM30_476-1; MSM30_477-1; MSM30_477-3; MSM30_479-1; MSM30_480-2; MSM30_482-1; MSM30_483-1; MSM30_485-1; MSM30_486-1; MSM30_488-1; MSM30_490-2; MSM30_493-1; MSM30_499-1; MSM30_500-1; MSM30_501-1; MSM30_502-1; MSM30_503-1; MSM31; MSM31_550-5; MSM31_557-2; MSM31_561-2; MSM31_575-3; MSM31_585-4; MSM44; MSM44_330-1; MSM44_331-2; MSM44_342-5; MSM44_346-4; MSM44_353-2; MSM44_357-2; MSM44_359-2; MSM44_366-3; MSM44_372-3; MSM44_374-2; MSM44_379-5; MSM44_385-3; MSM44_387-2; MSM44_389-2; MSM44_395-2; MSM44_399-3; MSM46; MSM46_10-8; MSM46_12-5; MSM46_14-2; MSM46_16-6; MSM46_19-3; MSM46_20-3; MSM46_22-2; MSM46_25-1; MSM46_28-3; MSM46_3-5; MSM46_4-5; MSM46_5-8; MSM46_6-4; MSM46_7-10; MSM66; MSM66/05-2; MSM66/15-3; MSM66/16-1; MSM66/17-1; MSM66/18-1; MSM66/19-1; MSM66/20-1; MSM66/21-1; MSM66/29-3; MSM66/31-2; MSM66/33-3; MSM66/34-1; MSM66/36-2; MSM66/4-4; MSM66/44-2; MSM66/46-2; MSM66/48-2; MSM66/50-2; MSM66/51-2; MSM66/53-2; MSM66/56-2; MSM66/57-2; MSM66/58-2; MSM66/59-2; MSM66/6-2; MSN; MUC; MULT; MultiCorer; Multicorer with television; Multiple investigations; Multiple opening/closing net; Nitrate; North Greenland Sea; North Pacific Ocean; Northwestern Passages; Norwegian Sea; NOW-1; NOW-2; NOW-3; NOW-4; NOW-5; Number; OBS; OBS314; Ocean bottom seismometer; Paamiut; Paamiut2014; Phosphate; Polarstern; Primary production of carbon; PS109; PS109_105-1; PS109_115-2; PS109_125-1; PS109_129-1; PS109_139-1; PS109_19-2; PS109_36-2; PS109_46-2; PS109_76-1; PS109_85-1; PS109_93-2; PS19/040; PS19/045; PS19/078; PS19/080; PS19/082; PS19/102; PS19/116; PS19/119; PS19/126; PS19/132; PS19/134; PS19/136; PS19/143; PS19 EPOS II; PS2111-2; PS2113-1; PS2117-1; PS2119-2; PS2121-1; PS2131-1; PS2142-3; PS2144-3; PS2148-1; PS2149-1; PS2150-
    Type: Dataset
    Format: text/tab-separated-values, 15755 data points
    Location Call Number Expected Availability
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  • 19
    Publication Date: 2024-05-25
    Description: Shallow sediment cores were collected with gravity cores from sites in the Japan Trench during cruise SO219A with R/V SONNE. In order to determine ex-situ concentrations of methane dissolved in pore water, sediment samples were taken from the sediment cores with cut-off syringes and transferred into glass vials. Methane concentrations in the headspace gas were used to calculate concentrations of methane dissolved in pore water (uncorrected for sediment porosity and Bunsen coefficient).
    Keywords: 27; Center for Marine Environmental Sciences; DEPTH, sediment/rock; GC; GeoB16423-1; Gravity corer; MARUM; Methane, porewater; SO219A/2; Sonne
    Type: Dataset
    Format: text/tab-separated-values, 10 data points
    Location Call Number Expected Availability
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  • 20
    Publication Date: 2024-05-25
    Description: The Deep-sea Sponge Microbiome Project is a large-scale study, integrating 16S amplicon sequencing data of seawater, sediment, and sponges, with a large set of ecological and physical metadata. The present dataset includes NCBI-accession numbers, sample collection details, and diverse measurements, adding up to 50 entries for each of the 1546 covered samples.
    Keywords: Accession number, genetics; Ada Rebikoff; Agassiz Trawl; AGT; Alkalinity, total; Anchor dredge; Angeles Alvarino; ANT-XXXI/2 FROSN; Arctic Ocean; Area/locality; ARK-XXVII/2; ARK-XXX/3; ARK-XXXI/2; Azores2018; Bay of Biscay; BC; BEAM; Beam trawl; Bleiksdjupet; Bottle, Niskin; Bottom trawl; Box corer; BT; Campaign; Carbon, inorganic, particulate; Carbon, organic, dissolved; Carbon, organic, particulate; Carbon dioxide, total; Celtic Voyager; Class; Conductivity; CTD; CTD/Rosette; CTD1; CTD10; CTD11; CTD12; CTD13; CTD14; CTD15; CTD2; CTD3; CTD4; CTD5; CTD6; CTD7; CTD8; CTD9; CTD-RO; CV13012; CV13012_A; DATE/TIME; Deep-sea; Deep-sea Sponge Grounds Ecosystems of the North Atlantic; Density, sigma, in situ; DEPTH, water; derived from MODIS remote sensing data; Distance; Dive_041; Dive_042; Dive_043; Dive_044; Dive_045; Dive_046; DIVER; DR10; DR15; DR4; DR7; DR9; Dredge, chain bag; Dredge, rock; Dredge, triangle; DRG_A; DRG_C; DRG_R; Duse Bay; Event label; extracted from GLODAPv2.2020; extracted from the World Ocean Atlas 2018 (WOA18); Family; G. O. Sars (2003); Gear; Genus; Geological feature; Grab; GRAB; GS16A-202; GS2016109A; GS2016109A-01-CTD-01; GS2016109A-06-ROV-01; GS2016109A-09-BC-01; GS2016109A-10-BC-02; GS2016109A-14-CTD-02; GS2016109A-16-CTD-04; GS2016109A-18-CTD-06; GS2016109A-21-BC-05; GS2016109A-24-CTD-07; GS2016109A-26-CTD-09; GS2016109A-27-CTD-10; GS2016109A-28-CTD-11; GS2016109A-32-ROV-05; GS2016109A-33-AGT-01; GS2017110; GS2017110-02-ROV-02; GS2017110-03-CTD-01; GS2017110-04-CTD-02; GS2017110-05-ROV-03; GS2017110-06-ROV-04; GS2017110-08-ROV-05; GS2017110-09-ROV-6; GS2017110-15-CTD-05; GS2017110-16-ROV8; GS2017110-19-ROV10; GS2017110-22-BC-02; GS2017110-23-ROV12; GS2017110-26-CTD-08; GS2017110-28-CTD-10; GS2017110-30-CTD-12; GS2017110-34-ROV-15; GS2017110-40-ROV-18; GS2017110-41-ROV-19; GS2017110-42-CTD-16; GS2017110-44-BC-1; GS2017110-45-BC-2; GS2017110-46-BC-3; GS2017110-47-BC-4; GS2017110-50-CTD-19; GS2017110-54-CTD-20; GS2017110-57-AGT-01; GS2017110-59-CTD-21; GS2017110-60-BC-5; GS2017110-61-BC-6; GS2017110-62-BC-7; GS2017110-63-ROV-24; GS2017110-67-CTD-23; GS2017110-68-ROV-25; GS2017110-71-BC-8; GS2017110-72-BC-9; GS2017110-73-BC-10; GS2017110-74-ROV-26; GS2018108; GS2018108-01-ROV-01; GS2018108-02-CTD-01; GS2018108-03-ROV-02; GS2018108-04-ROV-03; GS2018108-05-CTD-02; GS2018108-07-ROV-05; GS2018108-08-ROV-06; GS2018108-12-CTD-03; GS2018108-13-CTD-04; GS2018108-14-CTD-05; GS2018108-17-AGT-01; GS2018108-19-ROV-12; GS2018108-22-CTD-07; GS2018108-23-ROV-15; GS2018108-25-ROV-17; GS2018108-29-CTD-09; GS2018108-30-CTD-10; GS2018108-31-CTD-11; GS2018108-34-ROV-22; GS2018108-37-CTD-12; GS2018108-39-ROV-26; GS2018108-43-ROV-30; GS2018108-44-ROV-31; GS2018108-46-ROV-33; GS2018108-48-CTD-13; GS2018108-55-CTD-14; GS2018108-58-ROV-43; GS2018108-62-CTD-15; GS2018108-63-ROV-47; GS2018108-64-ROV-48; GS2018108-66-CTD-16; GS2018108-70-ROV-50; GS2018108-77-CTD-24; GS2018108-78-ROV-52; GS2018108-79-ROV-53; Gulf of Bothnia, Baltic sea; H045_A; Hans Brattström; HB2016952; HB2016952_2; HB2016952_5; HB2016952_6; HB2016952_7; HB2016952_8; HB27102017_A; HB27102017_B; HB27102017_C; HB27102017a; HB27102017b; HUD16/19_010; HUD16/19_012; HUD16/19_013; HUD16/19_018; HUD16/19_020; HUD16/19_383; HUD16/19_387; HUD16/19_391; HUD16/19_392; HUD16/19_395; HUD2016019; Hudson; Identification; James Clark Ross; JR17003A; JR17003A_12; JR17003A_19; JR17003A_42; JR17003A_44; JR17003A_46-1; KB2017610; KB2017610_CTD7; KB2017610_KB-28; KB2017610_KB-32; KB2017610_KB-60; KB2017610_KB-61; KB2017610_ROV9; Korsfjord; Kristine Bonnevie; LATITUDE; LONGITUDE; LULA0718_Dive1; LULA0718_Dive2; LULA0718_Dive3; Malangsgrunnen; Maria S. Merian; Martha L. Black; meta-analysis; microbes; MLB2017001; MLB2017001_004; MLB2017001_005; MLB2017001_006; MLB2017001_015; MLB2017001_017; MLB2017001_020; MOOR; Mooring; MSM86; MSM86_006; MSM86_008; MSM86_009; MSM86_010; MSM86_012; MSM86_013; MSM86_015; MSM86_016; MSM86_019; MSM86_021; MSM86_022; MSM86_027; MSM86_028; MSM86_031; MSM86_032; MSM86_034; MSM86_035; MSM86_036; MSM86_038; MSM86_040; MSM86_041; MSM86_052; MSM86_054; MSM86_061; MSM86_062; MSM86_063; MSM86_067; MSM86_080; MSM86_081; MSM86_083; MSM86_086; MSM86_088; MSM86_090; MSM86_091; MSM86_094; MSM86_101; MSM86_106; Multicorer with television; NIS; Nitrate; Nitrogen, total dissolved; Nitrogen/Phosphorus ratio; North Greenland Sea; ocean; Ocean; Order; OT; OTNMoor_275; Otter trawl; Oxygen, apparent utilization; Oxygen, dissolved; Oxygen saturation; PAA2014007; PAA2014007_003; PAA2014007_056; PAA2014007_068; PAA2014007_070; PAA2014007_078; PAA2014007_079; PAA2014007_088; PAA2014007_110; PAA2014007_120; PAA2014007_123; PAA2014007_124; PAA2014007_125; PAA2014007_131; PAA2014007_133; PAA2014007_136; Paamiut; pH; Phosphate; Phylum; Polarstern; Pori Bac NewZ; Pressure, water; Prince Gustav Channel; Profile; Project; PS101; PS101/088-1; PS101/092-1; PS101/093-1; PS101/094-1; PS101/123-1; PS101/154-1; PS101/155-1; PS101/170-1; PS101/172-1; PS101/193-1; PS101/194-1; PS101/196-1; PS101/197-1; PS101/198-1; PS101/200-1; PS101/208-1; PS101/216-1; PS107; PS107_2-1; PS107_33-1; PS107_47-1; PS107_6-3; PS80; PS80/176-9; PS80/192-1; PS96; PS96/006-1; PS96/009-3; PS96/009-4; Realm; Remote operated platform for oceanography; Remote operated vehicle; ROPOS; ROPOS 2028; ROPOS 2029; ROPOS 2030; ROPOS 2034; ROV; Salinity; Sample type; Sampling by diver; Schultz Bank; Scotia; Scotia_0915S; Scotia_0915S_A; Scotia_0915S_B; Scotia_0915S_C; Scotia_0915S_D; Sea surface chlorophyll a; seawater; sediment; Silicate; Silicon/Phosphorus ratio; SO254; SO254_10-1; SO254_1-1; SO254_14-1; SO254_18-1; SO254_2-1; SO254_22-1; SO254_23-1; SO254_33-1; SO254_34-1; SO254_36-1; SO254_69-1; SO254_76-1; SO254_77-1; SO254_78-1; SO254_79-1; SO254_8-1; SO254_81-1; SO254_84-1; SO254_85-1; SO254_diver; Sognefjord; Sonne_2; South Atlantic Ocean; South Pacific Ocean; Species; sponge; SponGES; SponGES_0617; SPONGES_0617_04-DR4; SPONGES_0617_06-BT2; SPONGES_0617_07-CTD1; SPONGES_0617_09-DR5; SPONGES_0617_10-DR6; SPONGES_0617_12-CTD2; SPONGES_0617_13-CTD3; SPONGES_0617_15-DR7; SPONGES_0617_18-CTD4; SPONGES_0617_19-CTD5; SPONGES_0617_20-BT3; SPONGES_0617_23-DR9; SPONGES_0617_24-CTD6; SPONGES_0617_26-BT4; SPONGES_0617_27-CTD7; SPONGES_0617_28-DR10; SPONGES_0617_29-CTD8; SPONGES_0617_37-DR11; SPONGES_0617_38-DR12; SPONGES_0617_40-CTD9; SPONGES_0617_41-BT5; SPONGES_0617_42-CTD10; SPONGES_0617_43-BC1; SPONGES_0617_45-BC2; SPONGES_0617_46-CTD11; SPONGES_0617_47-BT6; SPONGES_0617_48-DR14; SPONGES_0617_49-CTD12; SPONGES_0617_50-BT7; SPONGES_0617_52-BT9; SPONGES_0617_53-BC3M1; SPONGES_0617_54-BT10; SPONGES_0617_55-CTD13; SPONGES_0617_56-BT11; SPONGES_0617_57-BT12; SPONGES_0617_58-CTD14; SPONGES_0617_59-BC4M1; SPONGES_0617_60-DR15; SPONGES_0617_61-CTD15; SPONGES_0617_63-DR16; Station label; Stjernsund; SUB; Submersible; Sula reef; TAD; Television-Grab; Temperature, water; Tromsoflaket East; Tromsøflaket; TVG; TVMUC; Uniform resource locator/link to reference; Vesteris; Water bodies; Weddell Sea; Zone
    Type: Dataset
    Format: text/tab-separated-values, 54242 data points
    Location Call Number Expected Availability
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  • 21
    Publication Date: 2024-05-25
    Description: This dataset contains occurrence records (i.e., species name, latitude, longitude, depth (where available), and metadata) for six species of the demosponge genus Geodia Lamarck, 1815, belonging to the Geodiidae family: Geodia atlantica (Stephens, 1915); Geodia barretti Bowerbank, 1858; Geodia macandrewii Bowerbank, 1858; Geodia phlegraei (Sollas, 1880); Geodia hentscheli Cárdenas et al. 2010; and Geodia parva Hansen, 1885. The records fall in the North Atlantic and Arctic Oceans, and are used/described in the linked article by Roberts et al. (2021). Note that the dataset provided has not been subjected to any of the filtering stages applied in that manuscript for the purposes of various novel biogeographical analyses (i.e., it is original and complete), and the taxonomic identifications have been rigorously checked (as described therein). Definitions of institution abbreviations used in the 'Museum Specimen / Picture Information' column of the dataset spreadsheet have been provided in an accompanying table (see Comment field below). Where records are derived from earlier literature sources, full references for citations given in the 'Campaign / Source' column (and further general information on many of the records) may be found in the articles by Cárdenas et al. (2010; 2013) and Cárdenas & Rapp (2015). An earlier version of this dataset may be accessed at the DRYAD repository: Cárdenas P, Rapp HT, Klitgaard AB, Best M, Thollesson M, Tendal OS (2013), Data from: Taxonomy, biogeography and DNA barcodes of Geodia species (Porifera, Demospongiae, Tetractinellida) in the Atlantic boreo-arctic region, Dryad, Dataset, doi:10.5061/dryad.td8sb
    Keywords: 87PA0028; 87PA0067; 87PA0078; 92PA0160002; 92PA0160005; 92PA0160014; 92PA0160028; 92PA0160050; 92PA0160052; 94PA0090001; 94PA0090002; 94PA0090009; 94PA0090010; 94PA0090019; 94PA0090020; 94PA0090026; 94PA0090039; 94PA0090041; 94PA0090043; 94PA0090045; 94PA0090049; 94PA0090062; Agassiz Trawl; AGT; Arctic Ocean; ARK-VII/2; ARK-XXII/1a; Barents Sea; BEAM; Beam trawl; BIODEEP2007_Dredge2; BIODEEP2007_ROV10; BIODEEP2007_ROV9; BIOFAR_St117; BIOFAR_St119; BIOFAR_St120; BIOFAR_St122; BIOFAR_St234; BIOFAR_St279; BIOFAR_St287; BIOFAR_St297; BIOFAR_St298; BIOFAR_St375; BIOFAR_St379; BIOFAR_St389; BIOFAR_St43; BIOFAR_St451; BIOFAR_St452; BIOFAR_St486; BIOFAR_St487; BIOFAR_St498; BIOFAR_St526; BIOFAR_St530; BIOFAR_St531; BIOFAR_St535; BIOFAR_St540; BIOFAR_St550; BIOFAR_St69; BIOFAR_St734; BIOFAR_St756; BIOFAR_St89; BIOFAR_St901; BIOICE_St2022; BIOICE_St2023; BIOICE_St2218; BIOICE_St2292; BIOICE_St2293; BIOICE_St2368; BIOICE_St2374; BIOICE_St2499; BIOICE_St2501; BIOICE_St2516; BIOICE_St2518; BIOICE_St2700; BIOICE_St2728; BIOICE_St2747; BIOICE_St2756; BIOICE_St2768; BIOICE_St2769; BIOICE_St2923; BIOICE_St2926; BIOICE_St2928; BIOICE_St3227; BIOICE_St3659; BIOICE_St3661; BIOSKAG2006_St20; BIOSYS2006_DR182; BIOSYS2006_VG20-1; Blacker1957_11; Blacker1957_130; Blacker1957_131; Blacker1957_14; Blacker1957_16; Blacker1957_164; Blacker1957_165; Blacker1957_168; Blacker1957_20; Blacker1957_21; Blacker1957_22; Blacker1957_24; Blacker1957_25; Blacker1957_27; Blacker1957_28; Blacker1957_33; Blacker1957_35; Blacker1957_36; Blacker1957_44; Blacker1957_45; Blacker1957_46; Blacker1957_53; Blacker1957_55; Blacker1957_56; Blacker1957_60; Blacker1957_61; Blacker1957_62; Blacker1957_68; Blacker1957_75; Blacker1957_8; Blacker1957_80; Blacker1957_81; Blacker1957_84; Blacker1957_9; Blacker1957_94; BMT19; Boury-Esnaultetal1994_CP62; Boury-Esnaultetal1994_CP63; Boury-Esnaultetal1994_CP92; Boury-Esnaultetal1994_CP98; Bowerbank1872a_Vikna; Bowerbank1872aPlateXI_Vikna; Brattholmen_St230407; Breitfuss1930_St1237; Breitfuss1930_St1347; Breitfuss1930_St1385; Burton1934_St548; Burton1959_EIceland; Burton1959_SEIceland; Campaign; CD80_St178; CD80_St18; CD80_St91; CE13008; CE13008_ROV32; CE2008-11_M11GHaul22; CE2008-11_M11GHaul23; Celtic Explorer; Celtic Sea; CENTOBBiogasII_DS33; CGB2011_11c-16-DR01; CGB2011_11c-19-ROV05; CGB2011_11c-30-DR05; CGB2011_11c-31-DR06; Comment; CorSeaCan_B12_CG_ACH_P01_20100809; CorSeaCan_B13_MOI-ACH-P06; CV13012_51; Dana_St6001; Davis Strait; Deep-sea Sponge Grounds Ecosystems of the North Atlantic; Depth, bottom/max; Depth, top/min; DEPTH, water; Dyrelivihavet2008_SandsfjordRogaland; E17044_SP17E44001; EBS; EcosystemBarentsSea2007_St2562; Epibenthic sledge; Event label; FRVScotia2012_S12_469; FRVScotia2012_S12/469; FRVScotia2012_S12-469; G. O. Sars (2003); Giant box corer; GKG; Greenland Sea; GS06/112; GS112_BMT19; GS14; GS14-AGT03; GS14-AGT07; GS14-DR02; GS14-DR09; GS14-DR12; H2DEEP2008_ROV5; HakonMosby_St237; HakonMosby_St242; HakonMosby_St245; HakonMosby_St86072701; HakonMosby_St93060602; HakonMosby_St93060612; HakonMosby_St93060613; HakonMosby_St93061106; Hentschel1929_St40; Hentschel1929_St41; Hentschel1929_St42; Howelletal2010_WSC11; Howelletal2010_WSCE10B; Howelletal2010_WSCE3; Howelletal2010_WSCE4; HUD2007-025_DiveR1059; HUD2010-029; HUD2010-029_R1335; HUD2010-029_R1336-07; HUD2010-029_R1339-10; HUD2010-029_R1340-12; HUD2010-029_R1340-4; HUD2010-029_R1341-18; HUD2013/29; HUD2013-029_DS1-I; Hudson; Iceland Sea; Identification; IngolfExpdt_St1; IngolfExpdt_St125; IngolfExpdt_St21; IngolfExpdt_St78; IngolfExpdt_St90; IngolfExpdt_St92; JAGO; Kara Sea; Kingstonetal1979_LabradorCoast; Koltun1964_St1; Koltun1964_St10; Koltun1964_St11; Koltun1964_St26; Koltun1964_St46; Koltun1964_St7; Koltun1964_St8; Koltun1964_St9; Koltun1966_NofFranzJosephLand; Koltun1966_NofKaraSea; Koltun1966_NWofLaptevSea; Labrador Sea; Langenuen_SteinnesetSt31; Laptev Sea; LATITUDE; LONGITUDE; Lundbeck1909_Angmagsalik; Lynch_St1971; Lynch_St1972; Lynch_St1973; Lynch_St721008; Lysefjord_Uksen; M85/3; M85/3_1123; M85/3_1132; M85/3_1136; M85/3_1219; M85/3_1223; MA0200057_St90; MagnusHeinason_St150990; MAR310_St1; Mareano_StR228-12; Mareano_StR262VL282; Mareano_StR828; Mareano_StR863; Mareano2009_StR469VL491; Mareano2011_StR729VL756; Mareano2011_StR731VL759; Mareano2011_StR744VL772; Mareano2011_StR758VL786; MAR-Eco2004_St50-373; MAR-Eco2004_St70_385; MAR-Eco2004_St70-385; MAR-Eco2004_St72-386; MedSeaCan_B7_MG_PO2_20090523; MedSeaCan_B7_PA_ACH_P02_20090519; Meteor (1986); More2005_St46; MULT; Multiple investigations; NEREIDA0609_BC89; NEREIDA0710_BC237; Nereida2009-2010_BC04; Nereida2009-2010_DR04-001; Nereida2009-2010_DR07-025; Nereida2009-2010_DR10; Nereida2009-2010_DR12; Nereida2009-2010_DR18; Nereida2009-2010_DR19; Nereida2009-2010_DR20; Nereida2009-2010_DR22; Nereida2009-2010_DR23; Nereida2009-2010_DR24; Nereida2009-2010_DR3; Nereida2009-2010_DR32; Nereida2009-2010_DR38; Nereida2009-2010_DR4; Nereida2009-2010_DR6; Nereida2009-2010_DR64; Nereida2009-2010_DR66; Nereida2009-2010_DR7; Nereida2009-2010_DR70; Nereida2009-2010_DR70_BOTTOM; Nereida2009-2010_DR74; Nereida2009-2010_DR74_BOTTOM; North Greenland Sea; North Sea; Norwegian Sea; PA2010-009_Set075; PA2010-009_Set104; PA2010-009_Set105; PA2010-009_Set108; PA2010-009_Set109; PA2010-009_Set111; PA2010-009_Set113; PA2010-009_Set114; PA2010-009_Set115; PA2010-009_Set116; PA2010-009_Set126; PA2010-009_Set141; PA2010-009_Set155; PA2010-009_Set156; PA2010-009_Set157; PA2010-009_Set159; PA2010-009_Set160; PA2010-009_Set161; PA2010-009_Set162; PA2010-009_Set163; PA2010-009_Set164; PA2010-009_Set167; PA2010-009_Set168; PAA2011007; PAA2011007_127_39; PAA2011007_225_114; PAA2011007_255_126; PAA2011007_262_128; PAA2011007_533_23; PAA2011007_634_139; PAA2013008; PAA2013008_157_44; PAA2013008_169_46; PAA2013008_174_47; PAA2013008_176_48; PAA2013008_177_50; PAA2013008_302_141; PAA2013008_305_142; PAA2013008_31_10; PAA2014007; PAA2014007_278_125; PAA2014007_286_127; PAA2014007_321_136; PAA2014007_514_152; PAA2015007; PAA2015007_126_32; PAA2015007_289_60; PAA2015007_299_62; PAA2015007_303_64; Paamiut; Polarstern; PS17; PS17/223; PS70; PS70/002-2; PS70/006-1; PS70/014-4; PS70/015-1; PS70/016-1; PS70/027-1; PS70/040-4; RVMichaelSars_St102; RVMichaelSars_St76; RVMichaelSars_St85; S10176_SP10176001; S11073_SP11073001; S11471_SP11471001; S12135_SP12135001; S12444_SP12444001; S12446_SP12446001; S12447; S15A13; S16185_SP16185001; S16379_SP16379003; S16A03_SP16A03017; S16A03_SP16A03029; S16A03_SP16A03039; S16A03_SP16A03041; S18A02; S18A03; Scotland Sea; ShinkaiMaru_St004; ShinkaiMaru_St109; ShinkaiMaru_St110; ShinkaiMaru_St15; ShinkaiMaru_St18; ShinkaiMaru_St1976; ShinkaiMaru_St21; ShinkaiMaru_St26; ShinkaiMaru_St29; ShinkaiMaru_St3; ShinkaiMaru_St32; ShinkaiMaru_St43; ShinkaiMaru_St50; ShinkaiMaru_St63; ShinkaiMaru_St70; ShinkaiMaru_St79; ShinkaiMaru_St9; ShinkaiMaru1987_St104; ShinkaiMaru1987_St67; Skagerrak; South Atlantic Ocean; Species; SponGES; St89SI0240086; Station label; Submersible JAGO; SwedishArcticExp1871_St37; T0406066; T8903301; T8905093; T8905125; T8905127; T8905185; T9405259; T9405264; T9405276; T9405305; T9405315; T9405317; T9406031; T9406032; T9406036; T9406066; ThalassaZ_Z407; ThalassaZ_Z408; Traena Deep; Trollholmflua; Tromso_Haugbernes; Western Basin; WH_St569; WH47566; WH47572; ZoolPolarExp1900_St30
    Type: Dataset
    Format: text/tab-separated-values, 2307 data points
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  • 22
    Publication Date: 2024-05-25
    Description: Shallow sediment cores were collected with gravity cores from sites in the Japan Trench during cruise SO219A with R/V SONNE. In order to determine ex-situ concentrations of methane dissolved in pore water, sediment samples were taken from the sediment cores with cut-off syringes and transferred into glass vials. Methane concentrations in the headspace gas were used to calculate concentrations of methane dissolved in pore water (uncorrected for sediment porosity and Bunsen coefficient).
    Keywords: 47; Center for Marine Environmental Sciences; DEPTH, sediment/rock; GC; GeoB16449-1; Gravity corer; MARUM; Methane, porewater; SO219A/2; Sonne
    Type: Dataset
    Format: text/tab-separated-values, 5 data points
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  • 23
    Publication Date: 2024-05-25
    Keywords: Airborne Radar; ANT_2005/06; Antarctica; ANTSYO; EMR_transect_2005-2006; ice thickness; Ice thickness; Ice Thickness Radar (EMR); LATITUDE; LONGITUDE; POLAR 2
    Type: Dataset
    Format: text/tab-separated-values, 51644 data points
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  • 24
    Publication Date: 2024-05-25
    Description: Shallow sediment cores were collected with gravity cores from sites in the Japan Trench during cruise SO219A with R/V SONNE. In order to determine ex-situ concentrations of methane dissolved in pore water, sediment samples were taken from the sediment cores with cut-off syringes and transferred into glass vials. Methane concentrations in the headspace gas were used to calculate concentrations of methane dissolved in pore water (uncorrected for sediment porosity and Bunsen coefficient).
    Keywords: 28; Center for Marine Environmental Sciences; DEPTH, sediment/rock; GC; GeoB16425-1; Gravity corer; MARUM; Methane, porewater; SO219A/2; Sonne
    Type: Dataset
    Format: text/tab-separated-values, 10 data points
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  • 25
    Publication Date: 2024-05-25
    Description: Shallow sediment cores were collected with gravity cores from sites in the Japan Trench during cruise SO219A with R/V SONNE. In order to determine ex-situ concentrations of methane dissolved in pore water, sediment samples were taken from the sediment cores with cut-off syringes and transferred into glass vials. Methane concentrations in the headspace gas were used to calculate concentrations of methane dissolved in pore water (uncorrected for sediment porosity and Bunsen coefficient).
    Keywords: 24; Center for Marine Environmental Sciences; DEPTH, sediment/rock; GC; GeoB16421-1; Gravity corer; MARUM; Methane, porewater; SO219A/2; Sonne
    Type: Dataset
    Format: text/tab-separated-values, 7 data points
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  • 26
    Publication Date: 2024-05-25
    Description: Shallow sediment cores were collected with gravity cores from sites in the Japan Trench during cruise SO219A with R/V SONNE. In order to determine ex-situ concentrations of methane dissolved in pore water, sediment samples were taken from the sediment cores with cut-off syringes and transferred into glass vials. Methane concentrations in the headspace gas were used to calculate concentrations of methane dissolved in pore water (uncorrected for sediment porosity and Bunsen coefficient).
    Keywords: 30; Center for Marine Environmental Sciences; DEPTH, sediment/rock; GC; GeoB16427-1; Gravity corer; MARUM; Methane, porewater; SO219A/2; Sonne
    Type: Dataset
    Format: text/tab-separated-values, 6 data points
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  • 27
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    Exon Publications | Wilms Tumor
    Publication Date: 2024-05-24
    Description: The most important prognostic factors for Wilms tumor (WT) patients seem to be stage, histological subtype, and 1p/16q loss of heterozygosity (LOH) in chemotherapy-naive WTs. Over the last decade, age at diagnosis also was suggested to be an important risk factor for WT recurrence in Children’s Oncology Group (COG), United Kingdom (UK), and International Society of Pediatric Oncology (SIOP) studies. Several studies have analyzed age as a prognostic factor; these studies revealed age 〈2 years as a favorable prognostic factor, while age 〉4 years has been described as an adverse prognostic factor. In adults (〉18 years of age), WT represents less than 1% of all diagnosed renal tumors; therefore, diagnosis of WT in adults is often unexpected and poorly recognized, thereby inducing treatment delay with subsequent adverse outcome. One explanation for the higher risk of recurrence with increasing patient age is the higher frequency of anaplasia at higher age. Other suggested reasons are delay in diagnosis, advanced tumor stage at presentation, and intrinsically different biological behaviors. Whether age is really an independent risk factor, and whether age is a stronger prognostic factor than stage, histology, and LOH 1p/16q, needs to be further explored. This may provide some insight into whether older patients need to be treated more intensively, as is already advised for adult WT patients.
    Description: Published
    Keywords: MJR
    Language: English
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  • 28
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    Exon Publications | Wilms Tumor
    Publication Date: 2024-05-24
    Description: Wilms’ tumour (WT) is the most common paediatric renal tumour, which can present as a single nodule, as multifocal unilateral lesions or as bilateral tumours. Typically, WT comprises three histological components namely blastemal, epithelial and stromal. The proportion and the degree of maturation of these components vary significantly, making the histological appearance of each tumour unique. Classical triphasic WT rarely presents diagnostic difficulty for pathologists, but when only one component is present, especially in a small biopsy specimen, the differential diagnosis may include renal cell carcinoma, metanephric adenoma and hyperplastic nephrogenic rest for epithelial elements and clear cell sarcoma of the kidney, mesoblastic nephroma and synovial sarcoma for stromal elements. Pure blastemal-type WT may be difficult to distinguish from other embryonal ‘small round blue cell tumours’, including neuroblastoma, primitive neuroectodermal tumour/Ewing sarcoma, desmoplastic small round cell tumour and lymphoma. All the three components, though usually blastema, can become anaplastic, leading to the diagnosis of either focal or diffuse anaplasia. WT with diffuse anaplasia and WT with blastemal predominance (after preoperative che¬motherapy) are regarded as high-risk tumours and require more aggressive treatment. Careful assessment of the tumour and the normal kidney is critical for accurate subtyping and staging of WT, which is the basis for post-operative treatment. In addition, the identification and correct interpretation of nephrogenic rests may affect prognosis and management. Histological distinction between WT and nephrogenic rest is not always possible based on morphology alone, and implementation of new molecular genetic tools may aid in this regard. Other molecular genetic signatures of WT, such as P53 mutation and MYCN dysregulation, may provide future additional prognostic and therapeutic information.
    Description: Published
    Keywords: nephrogenic rest ; Wilms’ tumour ; MJR
    Language: English
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  • 29
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    Université de Carthage. Faculté des Sciences de Bizerte. Laboratoire de Biosurveillance de l’Environnement
    Publication Date: 2024-05-24
    Description: Le présent travail porte sur l’étude systématique et écologique du benthos dans les principaux étages bathymétriques du golfe de Tunis par le biais de plusieurs approches, dans le but d’établir l’état écologique du milieu. Il s’agit des paramètres de biodiversité, des faciès bionomiques, des interactions biotiques et abiotiques et des indices biotiques basés sur les groupes trophiques et les groupes écologiques. Cette étude a permis dans un premier temps d’enrichir la liste des invertébrés benthiques inventoriés dans le golfe de Tunis. Il s’agit de 4 espèces de Bryozoaires nouvelles pour la science (Trematooecia ligulata Ayari et Taylor, 2008, Herentia baptooecium sp. nov., Herentia orthosa sp. nov. et Cellepora sinusa sp. nov) et de 70 espèces nouvelles pour la Tunisie dont 24 Polychètes, 24 Bryozoaires, 7 Cnidaires et 5 Amphipodes. De plus, la description des faciès bionomiques a permis de préciser les limites des étages, mais également de tirer des renseignements scientifiques intéressants. Ainsi, au centre du golfe, l’étage bathyal supérieur commence à -120 m, après une légère déclivité du plateau continental à environ -100 m. La zone qui s’étend du nord de Ras El Fartas vers le large en passant par l’ouest de l’île de Zembra, est occupée par un herbier de Posidonies à -21 m et suivie d’un détritique côtier caractérisant la limite supérieure du circalittoral puis d’un détritique du large dont les caractéristiques témoignent de la régression du circalittoral. Au niveau de la troisième zone et en face de Sidi Daoued et de Ras El Ahmar, l’herbier de Posidonies se situe entre -22 et -38 m de profondeur. Ensuite, des faciès de sédiments meubles et de maërl en bon état se succèdent. A environ -67 m de profondeur, apparaît le rebord du plateau continental, suivi à -130 m, par l’étage bathyal supérieur vaseux. Au niveau de la quatrième zone, en face de Ras Gammarth, des tâches de Posidonies et de Cymodocées sont suivies d’un détritique côtier à -79 m, puis de la déclivité du plateau continental marquant le passage du circalittoral inférieur à l’étage bathyal supérieur caractérisé jusqu’ à -137 m par une vase appauvrie. Au niveau de la zone ouest, nous enregistrons un envasement en face de la lagune de Ghar El Melh et un faciès de maërl en face de Sidi Ali El Mekki. L’étude de la distribution des Polychètes en fonction des paramètres environnementaux considérés a permis quant à elle de déterminer les préférendums écologiques des espèces principales. Elle a montré, entre autres, que les Polychètes ne sont pas distribués dans le golfe de Tunis en fonction d’un seul gradient abiotique et que la profondeur joue ici un rôle primordial. L’approche écologique a été basée sur l’utilisation de plusieurs indices biotiques, et les résultats obtenus montrent que l’indice BENTIX est le plus fiable pour le cas du golfe de Tunis. L’utilisation conjointe des principaux indices a montré que l’état écologique est satisfaisant au large de Sidi Ali El Mekki, en face de Cap Farina, autour de l’île de Zembra, au nord du Cap Bon et en face de Ras El Ahmar et que le reste de la zone est en légère perturbation ou en changement vers un état de déséquilibre
    Description: This present work is about a systematic and an ecological study of the benthos within the main bathymetric levels of Tunis gulf using many approaches with aims to establish its ecological state. These are the biodiversity parameters, the bionomic features, biotic and abiotic interactions and the biotic indices based on the trophic groups and the ecological groups. Thanks to this present study, the species list of the macrobenthic invertebrates increases. Altogether 4 species of Bryozoa are newly described (Trematooecia ligulata Ayari et Taylor, 2008, Herentia baptooecium sp. nov., Herentia orthosa sp. nov. et Cellepora sinusa sp. nov) and 70 species are found here for the first time in Tunisia coast: 24 Polychaeta, 24 Bryozoans, 7 Cnidaria and 5 Amphipoda. In addition, description of the bionomic features, allowed to limit the bathymetric levels and also, provided much essential scientific informations. Thus, in the middle of the gulf, the upper bathyal level begins from -120 m after a slight declivity of the continental plateau at about -100 m. The area which extends from the northern of Ras Fartas to the offshore going by the west of Zembra Island is occupied by Posidonia meadows at -21 m and followed by a coastal detritic which characterizes the upper limit of the Circalittoral, after that an offshore detritic characterize the regression of the Circalittoral. At the third sector and in front of Sidi Daoued and Ras El Ahmar, The Posidonia meadows begin from -22 to -38 m. After that, soft bottoms and maerl in good state follow each other. The plateau continental edge is at about -67 m, and then the muddy Superior Bathyal comes at -130 m. Within the fourth area in front of Ras Gammarth, some Posidonia and Cymodocea are followed by a costal detritic at -79 m then by the continental plateau declivity witch indicates passing from Inferior Circalittoral to the Superior Bathyal characterized until -137 m by an impoverished muddy bottom. The west sector is characterized by a muddy bottom in front of the Ghar El Melh Lagoon and a maerl in front of Sidi Ali El Mekki. Study of Polychaeta distribution according to considered environmental parameters allowed us to establish the ecological preferendum of some principal species. It shows that Polychaeta were not distributed within Tunis Gulf according to only one abiotic gradient however the depth is a primordial factor. The ecological approach is based on the use of many biotic index, results obtained showed that the BENTIX index is the most adequate in the case of the Gulf of Tunis. According to the different index used simultaneously the ecological state is satisfactory offshore Sidi Ali El Mekki, in front of Cap Farina, around Zembra isle, at the north of Cap Bon, in front of Ras El Ahmar and that the rest of the area is slightly perturbed or on change toward an imbalance state.
    Description: PhD
    Keywords: macro-phytobenthos ; macro-zoobenthos ; Bryozoaires ; Polychètes ; systématique ; bionomie ; facteurs abiotiques ; indices biotiques ; état écologique
    Repository Name: AquaDocs
    Type: Thesis/Dissertation
    Format: 429 pp.
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  • 30
    Publication Date: 2024-05-24
    Description: Marine waste, including aquatic by-products, poses a significant environmental challenge and garners increasing attention for its potential valorization. The development of cost-effective, environmentally friendly, and circular technologies for transforming marine biomass into value-added products is crucial for the successful implementation of sustainable aquatic industries. This involves focusing on strategies that simultaneously reduce waste and energy demand. This document presents the research andbiotechnological innovations carried out under the ARIBiotech project, which aims to create new biological products from marine waste. In a circular economy perspective, this initiative seeks to turn sources of pollution into sustainable opportunities, contributing to the preservation of marine ecosystems while fostering innovative solutions. Exploiting marine biomass and valorizing sea by-products, whether by using them directly or extracting biopolymers, appears to be a promising solution for a more sustainable use of marine resources, leading to increased economic benefits. However, the realization of such developments is hindered by the lack of appropriate regulatory frameworks to enable the use of waste and by-products, ensuring product safety, quality, and acceptability. This white paper showcases a diverse range of bioproducts (Crab waste hydrolyzate, chitin, chitosan, collagen, gelatin, cellulose aerogels, shell powder, and bioactive extracts) derived from the application of biotechnologies on various marine waste and co-products,highlighting their potential to support sustainable development. This document aims to encourage policymakers to support the creation of alliances and innovations in blue biotechnology and enable the general public to benefit from advances in creating bioproducts from marine waste.
    Description: Published
    Description: Refereed
    Keywords: Marine waste ; Bioproducts ; Biotechnological innovations ; Circular economy ; Sustainable development ; Bio-technologie bleue ; Valorisation déchets marins
    Repository Name: AquaDocs
    Type: Book/Monograph/Conference Proceedings
    Format: 26 pp.
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  • 31
    Publication Date: 2024-05-24
    Description: A new subgenus Peculiaripalpus subgen. nov. with a new species Partnunia (Peculiaripalpus) longlingensis sp. nov. which belongs to Partnunia Piersig, 1896 is described and illustrated. Partnunia represents a newly record genus of Protziinae Koenike, 1909 for Chinese fauna. The diagnosis of Partnunia is modified according to the new species. An updated key is provided for the subfamilies, genera and subgenera of Hydryphantidae.
    Keywords: water mites; new taxa; scanning electron microscope
    Repository Name: National Museum of Natural History, Netherlands
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  • 32
    Publication Date: 2024-05-24
    Description: Although Pliocene temperature and pCO2 are similar to those predicted in the IPPC RCP4.5 scenario, the distribution of coral reefs in the center of maximum coral diversity, the Coral Triangle, during this period has not been explored. We discovered a significantly lower occurrence of reefs during the Pliocene, which we refer to as the Pliocene Reef Gap, but this decrease was not associated with a drop in coral genus richness. While some of the multiple local causes that drove this decline, such as sea level rise, are analogs to drivers of Anthropocene reef decline, neither warming nor increasing pCO2 are among them.
    Keywords: Pliocene · Neogene · Coral triangle · ; Paleontology · Anthropocene · Coral reef decline
    Repository Name: National Museum of Natural History, Netherlands
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  • 33
    Publication Date: 2024-05-24
    Description: A new tetramic acid glycoside, aurantoside L (1), was isolated from the sponge Siliquariaspongia japonica collected at Tsushima Is., Nagasaki Prefecture, Japan. The structure of aurantoside L (1) composed of a tetramic acid bearing a chlorinated polyene system and a trisaccharide part was elucidated using spectral analysis. Aurantoside L (1) showed anti-parasitic activity against L. amazonensis with an IC50 value of 0.74 μM.
    Keywords: aurantosides ; Siliquariaspongia japonica ; marine sponge ; nuclear magnetic resonance ; mass ; spectrometry ; anti-leishmanial activity ; marine natural products
    Repository Name: National Museum of Natural History, Netherlands
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  • 34
    Publication Date: 2024-05-24
    Description: Traditional morphological methods for species identification are highly time consuming, especially for small organisms, such as Foraminifera, a group of shell-building microbial eukaryotes. To analyze large amounts of samples more efficiently, species identification methods have extended to molecular tools in the last few decades. Although a wide range of phyla have good markers available, for Foraminifera only one hypervariable marker from the ribosomal region (18S) is widely used. Recently a new mitochondrial marker cytochrome oxidase subunit 1 (COI) has been sequenced. Here we investigate whether this marker has a higher potential for species identification compared to the ribosomal marker. We explore the genetic variability of both the 18S and COI markers in 22 benthic foraminiferal morphospecies (orders Miliolida and Rotaliida). Using single-cell DNA, the genetic variability within specimens (intra) and between specimens (inter) of each species was assessed using next-generation sequencing. Amplification success rate was twice as high for COI (151/200 specimens) than for 18S (73/200 specimens). The COI marker showed greatly decreased intra- and inter-specimen variability compared to 18S in six out of seven selected species. The 18S phylogenetic reconstruction fails to adequately cluster multiple species together in contrast to COI. Additionally, the COI marker helped recognize misclassified specimens difficult to morphologically identify to the species level. Integrative taxonomy, combining morphological and molecular characteristics, provides a robust picture of the foraminiferal species diversity. Finally, we suggest the use of a set of sequences (two or more) to describe species showing intra-genomic variability additionally to using multiple markers. Our findings highlight the potential of the newly discovered mitochondrial marker for molecular species identification and metabarcoding purposes.
    Keywords: protist ; high-throughput sequencing ; metabarcoding ; intra-genomic variation ; benthic foraminifera
    Repository Name: National Museum of Natural History, Netherlands
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  • 35
    Publication Date: 2024-05-24
    Description: Foraminifera are a species-rich phylum of rhizarian protists that are highly abundant in many marine environments and play a major role in global carbon cycling. Species recognition in Foraminifera is mainly based on morphological characters and nuclear 18S ribosomal RNA barcoding. The 18S rRNA contains variable sequence regions that allow for the identification of most foraminiferal species. Still, some species show limited variability, while others contain high levels of intragenomic polymorphisms, thereby complicating species identification. The use of additional, easily obtainable molecular markers other than 18S rRNA will enable more detailed investigation of evolutionary history, population genetics and speciation in Foraminifera. Here we present the first mitochondrial cytochrome c oxidase subunit 1 (COI) gene sequences (“barcodes”) of Foraminifera. We applied shotgun sequencing to single foraminiferal specimens, assembled COI, and developed primers that allow amplification of COI in a wide range of foraminiferal species. We obtained COI sequences of 49 specimens from 17 species from the orders Rotaliida and Miliolida. Phylogenetic analysis showed that the COI tree is largely congruent with previously published 18S rRNA phylogenies. Furthermore, species delimitation with ASAP and ABGD algorithms showed that foraminiferal species can be identified based on COI barcodes.
    Repository Name: National Museum of Natural History, Netherlands
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  • 36
    Publication Date: 2024-05-24
    Description: Mitochondria originated from an ancient bacterial endosymbiont that underwent reductive evolution by gene loss and endosymbiont gene transfer to the nuclear genome. The diversity of mitochondrial genomes published to date has revealed that gene loss and transfer processes are ongoing in many lineages. Most well-studied eukaryotic lineages are represented in mitochondrial genome databases, except for the superphylum Retaria—the lineage comprising Foraminifera and Radiolaria. Using singlecell approaches, we determined two complete mitochondrial genomes of Foraminifera and two nearly complete mitochondrial genomes of radiolarians. We report the complete coding content of an additional 14 foram species. We show that foraminiferan and radiolarian mitochondrial genomes contain a nearly fully overlapping but reduced mitochondrial gene complement compared to other sequenced rhizarians. In contrast to animals and fungi, many protists encode a diverse set of proteins on their mitochondrial genomes, including several ribosomal genes; however, some aerobic eukaryotic lineages (euglenids, myzozoans, and chlamydomonas-like algae) have reduced mitochondrial gene content and lack all ribosomal genes. Similar to these reduced outliers, we show that retarian mitochondrial genomes lack ribosomal protein and tRNA genes, contain truncated and divergent small and large rRNA genes, and contain only 14 or 15 proteincoding genes, including nad1, -3, -4, -4L, -5, and -7, cob, cox1, -2, and -3, and atp1, -6, and -9, with forams and radiolarians additionally carrying nad2 and nad6, respectively. In radiolarian mitogenomes, a noncanonical genetic code was identified in which all three stop codons encode amino acids. Collectively, these results add to our understanding of mitochondrial genome evolution and fill in one of the last major gaps in mitochondrial sequence databases.
    Keywords: Foraminifera ; mitochondrial evolution ; mitochondrial genome ; Radiolaria ; Retaria ; Rhizaria
    Repository Name: National Museum of Natural History, Netherlands
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  • 37
    Publication Date: 2024-05-24
    Description: Monitoring community composition of Foraminifera (single-celled marine protists) pro-vides valuable insights into environmental conditions in marine ecosystems. Despitethe efficiency of environmental DNA (eDNA) and bulk-sample DNA (bulk-DNA) me-tabarcoding to assess the presence of multiple taxa, this has not been straightforwardfor Foraminifera partially due to the high genetic variability in widely used ribosomalmarkers. Here, we test the correctness in retrieving foraminiferal communities by me-tabarcoding of mock communities, bulk-DNA from coral reef sediment samples, andeDNA from their associated ethanol preservative using the recently sequenced cy-tochrome c oxidase subunit 1 (COI) marker. To assess the detection success, we com-pared our results with large benthic foraminiferal communities previously reportedfrom the same sampling sites. Results from our mock communities demonstrate thatall species were detected in two mock communities and all but one in the remainingfour. Technical replicates were highly similar in number of reads for each assigned ASVin both the mock communities and bulk-DNA samples. Bulk-DNA showed a signifi-cantly higher species richness than their associated eDNA samples, and also detectedadditional species to what was already reported at the specific sites. Our study con-firms that metabarcoding using the foraminiferal COI marker adequately retrieves thediversity and community composition of both the mock communities and the bulk-DNA samples. With its decreased variability compared with the commonly used nu-clear 18 S rRNA, the COI marker renders bulk-DNA metabarcoding a powerful tool toassess foraminiferal community composition under the condition that the referencedatabase is adequate to the target taxa.
    Keywords: bulk-sample ; DNA ; community composition ; coral reef ; environmental DNA ; foraminifera ; metabarcoding
    Repository Name: National Museum of Natural History, Netherlands
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  • 38
    Publication Date: 2024-05-24
    Description: Ecological regime shifts in the marine realm have been recorded from a variety of systems and locations around the world. Coral reefs have been especially affected, with their benthic habitat changing from a dominance of stony corals to a dominance of other organisms such as fleshy algae. To detect changes in the benthic habitat of coral reefs, simple tools applicable on a global scale are necessary for future monitoring programs. Hence, the aim of this research is to explore the hypothesis that shifts in assemblages of large benthic foraminifera (LBF) can detect early signs of degradation in the reef benthic habitat. To do so, data on living assemblages of LBF collected between 1997 and 2018 at 12 islands in the Spermonde Archipelago (South Sulawesi, Indonesia) were analyzed. Foraminiferal specimens were morphologically identified to the species level and statistical analyses performed to assess changes in their assemblage composition. A clear temporal shift was observed. Typical foraminiferal assemblages in a coral-dominated (e.g., Amphistegina lobifera, Calcarina spengleri, Heterostegina depressa) and fleshy algaedominated (e.g., Neorotalia gaimardi, C. mayori) reef habitats were identified and significantly linked to the substrate type. Other species (e.g., Elphidium spp., Peneroplis planatus and Sphaerogypsina globulus) seem to reflect a spatial and temporal gradient of anthropogenic pollution from local inhabited islands and ongoing urban development on the mainland. Hence communities of LBF consistently follow gradual shifts in environmental conditions. Additionally to foraminiferal assemblages being an indicator for actual reef condition, closely monitoring LBF may provide early information on reef degradation, in time to take action against identified stressors (e.g., eutrophication or intensive fishing) at local and regional scales. The circumtropical distribution of LBF is such that they can be included worldwide in reef monitoring programs, conditional to calibration to the regional species pool.
    Keywords: Temporal dynamics ; Bioindicator ; Early detection ; Coral reef ; Spermonde Archipelago ; Indonesia
    Repository Name: National Museum of Natural History, Netherlands
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  • 39
    Publication Date: 2024-05-24
    Description: Foraminifera are a species-rich phylum of rhizarian protists that are highly abundant in most marine environments. Molecular methods such as metabarcoding have revealed a high, yet undescribed diversity of Foraminifera. However, so far only one molecular marker, the 18S ribosomal RNA, was available for metabarcoding studies on Foraminifera. Primers that allow amplification of foraminiferal mitochondrial cytochrome oxidase I (COI) and identification of Foraminifera species were recently published. Here we test the performance of these primers for the amplification of whole foraminiferal communities, and compare their performance to that of the highly degenerate LerayXT primers, which amplify the same COI region in a wide range of eukaryotes. We applied metabarcoding to 48 samples taken along three transects spanning a North Sea beach in the Netherlands from dunes to the low tide level, and analysed both sediment samples and meiofauna samples, which contained taxa between 42 mm and 1 mm in body size obtained by decantation from sand samples. We used single-cell metabarcoding (Girard et al., 2022) to generate a COI reference library containing 32 species of Foraminifera, and used this to taxonomically annotate our community metabarcoding data. Our analyses show that the highly degenerate LerayXT primers do not amplify Foraminifera, while the Foraminifera primers are highly Foraminifera- specific, with about 90% of reads assigned to Foraminifera and amplifying taxa from all major groups, i.e., monothalamids, Globothalamea, and Tubothalamea. We identified 176 Foraminifera ASVs and found a change in Foraminifera community composition along the beach transects from high tide to low tide level, and a dominance of single-chambered monothalamid Foraminifera. Our results highlight that COI metabarcoding can be a powerful tool for assessing Foraminiferal communities.
    Keywords: Foraminifera ; Metabarcoding ; Beach ; Community composition ; Intertidal ; Molecular ; biodiversity
    Repository Name: National Museum of Natural History, Netherlands
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  • 40
    Publication Date: 2024-05-24
    Description: In the marine realm, microorganisms are responsible for the bulk of primary production, thereby sustaining marine life across all trophic levels. Longhurst provinces have distinct microbial fingerprints; however, little is known about how microbial diversity and primary productivity change at finer spatial scales. Here, we sampled the Atlantic Ocean from south to north (~50°S–50°N), every ~0.5° latitude. We conducted measurements of primary productivity, chlorophyll-a and relative abundance of 16S and 18S rRNA genes, alongside analyses of the physicochemical and hydrographic environment. We analysed the diversity of autotrophs, mixotrophs and heterotrophs, and noted distinct patterns among these guilds across provinces with high and low chlorophyll-a conditions. Eukaryotic autotrophs and prokaryotic heterotrophs showed a shared inter-province diversity pattern, distinct from the diversity pattern shared by mixotrophs, cyanobacteria and eukaryotic heterotrophs. Additionally, we calculated samplewise productivity-specific length scales, the potential horizontal displacement of microbial communities by surface currents to an intrinsic biological rate (here, specific primary productivity). This scale provides key context for our trophically disaggregated diversity analysis that we could relate to underlying oceanographic features. We integrate this element to provide more nuanced insights into the mosaic-like nature of microbial provincialism, linking diversity patterns to oceanographic transport through primary production.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
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  • 41
    Publication Date: 2024-05-24
    Description: This paper demonstrates how historical research is a valuable tool for identifying past geological, geomorphological and climatic hazards and therefore critical for mitigating and reducing future risk. The authors describe the potential of a scientific field that straddles that of the geologist, geographer, historian and archivist. Historical records include a range of materials and sources of information, which can be very diverse; from written documents to cartographies, and from drawings to marble tombstones. They are all useful and convey important data, on the date of the event, the size of the phenomena, sometimes on ground effects, damage or magnitude. The authors discuss how to conduct historical research by providing a list of locations and how important historical documents can be found. Works that mention geological phenomena are listed, starting with the first occasional descriptions by individuals in letters, up to very specific publications in individual fields of interest. With this introduction, the editors of the Special Issue wish to draw attention to the importance of historical documentation, which is too often ignored or considered of low priority by the scientific community, but can contain key information on events, their impacts and social and cultural adaptations.
    Description: Published
    Description: 1777
    Description: JCR Journal
    Keywords: geological and geo-hydrological processes ; historical research; old documents ; land-use planning ; natursal hazard ; risk mitigation ; Europe
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
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  • 42
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    GEOMAR Helmholtz Centre for Ocean Research
    Publication Date: 2024-05-24
    Description: This julia package implements various tools for working with simple, non-marked, one dimensional point processes. In special it implements a bootstrap-based goodness-of-fit test for parametric models.
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  • 43
    Publication Date: 2024-05-24
    Description: Europe’s recent summer droughts have had devastating ecological and economic consequences, but the severity and cause of these extremes remain unclear. Here we present 27,080 annually resolved and absolutely dated measurements of tree-ring stable carbon and oxygen (δ13C and δ18O) isotopes from 21 living and 126 relict oaks (Quercus spp.) used to reconstruct central European summer hydroclimate from 75 BCE to 2018 CE. We find that the combined inverse δ13C and δ18O values correlate with the June–August Palmer Drought Severity Index from 1901–2018 at 0.73 (P 〈 0.001). Pluvials around 200, 720 and 1100 CE, and droughts around 40, 590, 950 and 1510 CE and in the twenty-first century, are superimposed on a multi-millennial drying trend. Our reconstruction demonstrates that the sequence of recent European summer droughts since 2015 CE is unprecedented in the past 2,110 years. This hydroclimatic anomaly is probably caused by anthropogenic warming and associated changes in the position of the summer jet stream.
    Type: Article , PeerReviewed
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  • 44
    Publication Date: 2024-05-24
    Description: Observations of spatio-temporal variability of the deep ocean are rare and little is known about occurrence of deep ocean mesoscale dynamics. Here, we make use of 2.5 years of time series data from three distributed sensor arrays, which acquired high-resolution temperature, pressure and sound speed data of the bottom layer offshore northern Chile. Estimating salinity and density from the direct observations enable access to the full spectrum of hydrographic variability from a multi-hourly to annual time scale and with average inter-station distances of less than 1 km. Analyses revealed interannual warming over the continental slope of 0.002 °C yr−1–0.003 °C yr−1, and could trace periodic hydrographic anomalies, likely related to coastal-trapped waves, as far as to the lower continental slope. A concurrent change in the shape of the warm anomalies and the rate of deep-sea warming that occurs with the crossing of the deep-sea trench suggests that the abyssal part of the eastern boundary current system off Chile does not extend past the deep sea trench. Furthermore, the comparison of anomaly timing and shape in between stations implies southwards flow over the mid to lower continental slope, centred closer to the trench.
    Type: Article , PeerReviewed
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  • 45
    Publication Date: 2024-05-24
    Description: Phytoplankton forms the base of the marine food web by transforming CO2 into organic carbon via photosynthesis. Some of the organic carbon is then transferred through the food web and exported into the deep ocean, a process known as the biological carbon pump. Despite the importance of phytoplankton for marine ecosystems and the global carbon cycle, projections of phytoplankton biomass in response to climate change differ strongly across Earth system models, illustrating uncertainty in our understanding of the underlying processes. Differences are especially large in the Southern Ocean, a region that is notoriously difficult to represent in models. Here, we argue that water column-integrated phytoplankton biomass in the Southern Ocean is projected to largely remain unchanged under climate change by the CMIP6 multi-model ensemble because of a shifting balance of bottom-up and top-down processes driven by a shoaling mixed layer depth. A shallower mixed layer is projected to improve growth conditions and consequently weaken bottom-up control. In addition to enhanced phytoplankton growth, the shoaling of the mixed layer also compresses phytoplankton closer to the surface and promotes zooplankton grazing efficiency, thus intensifying top-down control. Overall, our results suggest that while changes in bottom-up conditions stimulate enhanced growth, intensified top-down control opposes an increase in phytoplankton and becomes increasingly important for phytoplankton response under climate change in the Southern Ocean.
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  • 46
    Publication Date: 2024-05-24
    Description: We evaluated how ranges of four endemic and non-endemic aquatic ostracode species changed in response to long-term (glacial–interglacial cycles) and abrupt climate fluctuations during the last 155 kyr in the northern Neotropical region. We employed two complementary approaches, fossil records and species distribution models (SDMs). Fossil assemblages were obtained from sediment cores PI-1, PI-2, PI-6 and Petén-Itzá 22-VIII-99 from the Petén Itzá Scientific Drilling Project, Lake Petén Itzá, Guatemala. To obtain a spatially resolved pattern of (past) species distribution, a downscaling cascade is employed. SDMs were reconstructed for the last interglacial (∼120 ka), the last glacial maximum (∼22 ka) and the middle Holocene (∼6 ka). During glacial and interglacial cycles and marine isotope stages (MISs), modelled paleo-distributions and paleo-records show the nearly continuous presence of endemic and non-endemic species in the region, suggesting negligible effects of long-term climate variations on aquatic niche stability. During periods of abrupt ecological disruption such as Heinrich Stadial 1 (HS1), endemic species were resilient, remaining within their current areas of distribution. Non-endemic species, however, proved to be more sensitive. Modelled paleo-distributions suggest that the geographic range of non-endemic species changed, moving southward into Central America. Due to the uncertainties involved in the downscaling from the global numerical to the highly resolved regional geospatial statistical modelling, results can be seen as a benchmark for future studies using similar approaches. Given relatively moderate temperature decreases in Lake Petén Itzá waters (∼5 ∘C) and the persistence of some aquatic ecosystems even during periods of severe drying in HS1, our data suggest (1) the existence of micro-refugia and/or (2) continuous interaction between central metapopulations and surrounding populations, enabling aquatic taxa to survive climate fluctuations in the northern Neotropical region.
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  • 47
    Publication Date: 2024-05-24
    Description: Highlights • Investigation into the potential of Porites microatolls for SST reconstruction. • Comparison between recent and more conventional coral paleoclimatology methods. • Application of Srsingle bondU and Li/Mg paleothermometer. • Accuracy and reproducibility of Sr/Ca proved to be the most suitable proxy for SST reconstruction. Abstract Massive dome-shaped coral Porites are the predominant choice for paleoclimate studies due to their consistent and reliable growth. When growing close to sea level, they become limited in their vertical growth and form so-called ‘microatolls’. Microatolls have not yet been extensively explored for paleoclimate reconstruction. Here, we investigate how reliable modern Porites microatolls are against empirical sea-surface temperature using Sr/Ca, δ18O, Li/Mg and Srsingle bondU paleothermometry methods on samples from the Society Islands, French Polynesia. Our results show Sr/Ca ratios have the lowest Standard Error of the Inverse Prediction (SEIP) at 0.415 °C (N = 41) with a calibration of Sr/Ca (mmol mol−1) = −0.082 ± 0.006 SST (°C) + 11.256 ± 0.170 and with high reproducibility across multiple corals. The reproducibility of δ18O was less good, with SEIP increasing to 0.829 °C (N = 41). Considering methods directly from the literature, Li/Mg ratio empirically corrected for Sr/Ca had the best balance between bias and precision where no local calibration could be available. This study independently evaluates and confirms the suitability of Porites microatolls from well-flushed environments for paleoclimate studies. Fossil dome-shaped Porites grow anywhere between near-surface and roughly 20 m depths which inherently incorporates uncertainty into any sea surface temperature reconstruction. This uncertainty is significantly reduced for microatolls due to their well-constrained bathymetry. The study represents a fundamental step in paleoclimate research targeting consistently near the water-air interface bringing reliability and, especially when combined with their ability to reconstruct past sea-level changes, microatolls have the potential to be central for future paleoenvironmental studies.
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  • 48
    Publication Date: 2024-05-24
    Description: After a successful conquest of large parts of Syria in 1258 and 1259 CE, the Mongol army lost the battle of 'Ayn Jālūt against Mamluks on September 3, 1260 CE. Recognized as a turning point in world history, their sudden defeat triggered the reconfiguration of strategic alliances and geopolitical power not only in the Middle East, but also across much of Eurasia. Despite decades of research, scholars have not yet reached consensus over the causes of the Mongol reverse. Here, we revisit previous arguments in light of climate and environmental changes in the aftermath of one the largest volcanic forcings in the past 2500 years, the Samalas eruption ~1257 CE. Regional tree ring-based climate reconstructions and state-of-the-art Earth System Model simulations reveal cooler and wetter conditions from spring 1258 to autumn 1259 CE for the eastern Mediterranean/Arabian region. We therefore hypothesize that the post-Samalas climate anomaly and associated environmental variability affected an estimated 120,000 Mongol soldiers and up to half a million of their horses during the conquest. More specifically, we argue that colder and wetter climates in 1258 and 1259 CE, while complicating and slowing the campaign in certain areas, such as the mountainous regions in the Caucasus and Anatolia, also facilitated the assault on Syria between January and March 1260. A return to warmer and dryer conditions in the summer of 1260 CE, however, likely reduced the regional carrying capacity and may therefore have forced a mass withdrawal of the Mongols from the region that contributed to the Mamluks’ victory. In pointing to a distinct environmental dependency of the Mongols, we offer a new explanation of their defeat at 'Ayn Jālūt, which effectively halted the further expansion of the largest ever land-based empire.
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  • 49
    Publication Date: 2024-05-24
    Description: Social-ecological transformation has become an important concept in the face of profound planetary crises (loss of biodiversity, climate crisis). Recently, the needs for social scientific transformation research have become more clearly defined. We reflect on the role of the social sciences and the humanities in democratically shaping social transformation in interaction with other sectors of society. Finally, we sketch three examples that illustrate the kind of new methodological and institutional approaches to be pursued.
    Language: English
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  • 50
    Publication Date: 2024-05-24
    Description: Some forty years ago, the UN Convention on the Law of the Sea 1982 (UNCLOS) created an unusual regime for states to collectively manage common natural resources on the international seabed beyond national jurisdiction (known as the Area) through the International Seabed Authority (ISA). In the intervening years, scientists have increasingly been warning about the serious environmental risks of mining seabed minerals. At this pivotal point in time, when states are negotiating whether or not to allow seabed mining, this essay explores the risk of undermining by mining, that is, contravening international marine environmental law and the obligations and responsibilities of states thereunder by allowing commercial mining activities to commence. We argue that allowing seabed mining in the Area at this juncture, when so much about the deep ocean remains unknown, would risk frustrating a host of measures, achievements, and progress to enhance marine environmental protection, particularly in areas beyond national jurisdiction. We begin with an overview of the ISA and its work to date, before discussing potential interactions between seabed mining and marine environmental law and policies, with a particular focus on the new ocean biodiversity agreement. We conclude by urging states to take cognizance of their overarching duty to protect and preserve the marine environment and ensure that all decisions taken with respect to seabed mining are consistent with their obligations and responsibilities under international law.
    Language: English
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  • 51
    Publication Date: 2024-05-24
    Description: Real-world laboratories have become a recognised research format for addressing sustainability challenges. In these transdisciplinary settings, actors from civil society, local government, and academia work together using a transdisciplinary research approach to jointly experiment and learn about sustainability transformations. While these labs are considered to have potential, their impact has not yet been fully measured. Therefore, in our paper we explore the case of the Zukunftsstadt Lüneburg 2030+ process to uncover the impacts that this long-term effort has generated over the past eight years. By examining the process and its design features from three analytical perspectives, we identify emergent impacts in three dimensions: education, governance, and the lab as an actor for sustainability. Based on our case study, we suggest that real-world labs contribute to sustainability on a local level, beyond the intentional experiments, through impacts that emerge over the course of the joint operation of the lab.
    Language: English
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  • 52
    Publication Date: 2024-05-24
    Description: Numerous scientific reports have evidenced the transformation of the earth system due to human activities. These changes – captured under the term ‘Anthropocene’ – require a new perspective on global law and policy. The concept of ‘earth system law’ situates law in an earth system context and offers a new perspective to interrogate the role of law in governing planetary challenges such as climate change. The discourse on earth system law has not yet fully recognised courts as actors that could shape climate governance, while climate litigation discourse has insufficiently considered aspects of earth system law. We posit that courts play an increasingly influential climate governance role and that they need to be recognised as Anthropocene institutions within the earth system law paradigm. Drawing on a set of prominent climate cases, we discuss five inter-related domains that are relevant for earth system law and where the potential influence of courts can be discerned: establishing accountability, redefining power relations, remedying vulnerabilities and injustices, increasing the reach and impact of international climate law and applying climate science to adjudicate legal disputes. We suggest that their innovative work in these domains could provide a basis for positioning courts as planetary climate governance actors.
    Language: English
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  • 53
    Publication Date: 2024-05-24
    Description: Germany, the European Union member state with the largest fiscal space and its leading manufacturer of industrial goods, is pursuing an ambitious hydrogen strategy aiming at establishing itself as a major technology provider and importer of green hydrogen. The success of its hydrogen strategy represents not only a key element in realizing the European vision of climate neutrality but also a central driver of an emerging global hydrogen economy. This article provides a detailed review of German policy, highlighting its prominent international dimension and its implications for the development of a global renewable hydrogen economy. It provides an overview of the strategy's central goals and how these have evolved since the launch of the strategy in 2020. Next, it moves on to provide an overview of the strategy's main areas of intervention and highlights corresponding policy instruments. For this, we draw on a comprehensive assessment of hydrogen policy instruments, which have been systematically analyzed and coded. This was complemented by a detailed analysis of policy documents and information gathered in six interviews with government officials and staff of key implementing agencies. The article places particular emphasis on the strategy's international dimension. While less significant in financial terms than domestic hydrogen-related spending, it represents a defining feature of the German hydrogen strategy, setting it apart from strategies in other major economies. The article closes with a reflection on the key features of the strategy compared to other important countries, identifies gaps of the strategy and discusses important avenues for future research.
    Language: English
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  • 54
    Publication Date: 2024-05-24
    Description: Increasing interconnectedness, along with the effects of climate change and other global risk drivers, has led to mounting systemic risks in the complex systems that characterize our world. Systemic risks, with their cascading impacts and long-term sustainability concerns, necessitate transformative approaches to manage their effects across system scales and dimensions. To date, however, an “operationalization gap” impedes translating between propositions for transformative change and policy options for addressing systemic risk. Here, we propose combining systemic risk analyses with local approaches, prominently including knowledge co-production, to achieve a more comprehensive understanding of complex systems. This combined approach can support stakeholders in designing transformative risk management and adaptation interventions that balance individual and higher-order interactions, incorporate diverse viewpoints, and thus manage systemic risks and leverage transformation potential more effectively. Furthermore, we suggest that a risk-layering approach can help differentiate, prioritize, and orchestrate these options for incremental and transformative changes.
    Language: English
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  • 55
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    In:  Review of European, Comparative & International Environmental Law
    Publication Date: 2024-05-24
    Description: In two recent South African cases, Indigenous communities successfully challenged proposed fossil fuel exploration activities by the Shell petroleum company off South Africa's pristine West Coast. In contrast to earlier climate litigation cases in South Africa, the litigants relied specifically on their Indigenous rights and knowledge. In this case note, we highlight the ways in which the two courts engaged with the communities' cultural beliefs and practices as well as their knowledge related to sustainability and how this relates to protecting their livelihoods, cultural practices and identities that are threatened by the proposed activities. We highlight the important role played by Indigenous communities in the climate movement and argue that, in the future, Indigenous and related considerations could provide a strong basis for climate litigation in South Africa and potentially contribute to efforts to protect Indigenous communities against the activities of carbon majors.
    Language: English
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  • 56
    Publication Date: 2024-05-24
    Description: This article presents an enhanced emission module for the PALM model system, which collects discrete emission sources from different emission sectors and assigns them dynamically to the prognostic equations for specific pollutant species as volumetric source terms. Bidirectional lookup between each source location and cell index are maintained through using a hash key approach, while allowing all emission source modules to be conceived, developed and operated in a homogeneous and mutually independent manner. An additional generic emission mode has also been implemented to allow the use of external emission data in simulation runs. Results from benchmark runs indicate a high level of performance and scalability. Subsequently, a module for modelling parametrized emissions from domestic heating is implemented under this framework, using the approach of building energy usage and temperature deficit as a generalized form of heating degree days. An model run has been executed under idealized conditions by considering solely dispersion of PM10 from domestic heating sources. The results demonstrate a strong overall dependence on the strength and clustering of individual sources, diurnal variation in domestic heat usage, as well as the temperature deficit between the ambient and the user-defined target temperature. Vertical transport contributes additionally to a rapid attenuation of daytime PM10. Although urban topology plays a minor role on the pollutant concentrations at ground level, it has a relevant contribution to the vertical pollutant distribution.
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  • 57
    Publication Date: 2024-05-24
    Description: Key message: A decolonial approach is needed to fulfil IASC’s commitment to recognizing that Traditional Knowledge, Indigenous Knowledge and academic scientific knowledge are co-equal and complementary knowledge systems that all can and should inform its work (website ICARP IV, retrieved October 2023). This document summarizes key recommendations for actions regarding five themes: 1. Indigenous Peoples’ right to self-determination as a prerequisite for high-quality Arctic research 2. Ethics, methods and methodology as key for decolonial research 3. Indigenous-led research in design and practice 4. Indigenous Peoples’ co-equal participation in Arctic research funding structures and decision-making for securing decolonial Arctic research in practice 5. Funding for Co-Creative and Indigenous-Led Arctic Research
    Language: English
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  • 58
    Publication Date: 2024-05-24
    Description: Global projections of macroeconomic climate-change damages typically consider impacts from average annual and national temperatures over long time horizons. Here we use recent empirical findings from more than 1,600 regions worldwide over the past 40 years to project sub-national damages from temperature and precipitation, including daily variability and extremes. Using an empirical approach that provides a robust lower bound on the persistence of impacts on economic growth, we find that the world economy is committed to an income reduction of 19% within the next 26 years independent of future emission choices (relative to a baseline without climate impacts, likely range of 11–29% accounting for physical climate and empirical uncertainty). These damages already outweigh the mitigation costs required to limit global warming to 2 °C by sixfold over this near-term time frame and thereafter diverge strongly dependent on emission choices. Committed damages arise predominantly through changes in average temperature, but accounting for further climatic components raises estimates by approximately 50% and leads to stronger regional heterogeneity. Committed losses are projected for all regions except those at very high latitudes, at which reductions in temperature variability bring benefits. The largest losses are committed at lower latitudes in regions with lower cumulative historical emissions and lower present-day income.
    Language: English
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  • 59
    Publication Date: 2024-05-24
    Description: Are there group decision methods which (i) give everyone, including minorities, an equal share of effective decision power even when voters act strategically, (ii) promote consensus and equality, rather than polarization and inequality, and (iii) do not favour the status quo or rely too much on chance? We describe two non-deterministic group decision methods that meet these criteria, one based on automatic bargaining over lotteries, the other on conditional commitments to approve compromise options. Using theoretical analysis, agent-based simulations and a behavioral experiment, we show that these methods prevent majorities from consistently suppressing minorities, which can happen in deterministic methods, and keeps proponents of the status quo from blocking decisions, as in other consensus-based approaches. Our simulations show that these methods achieve aggregate welfare comparable to common voting methods, while employing chance judiciously, and that the welfare costs of fairness and consensus are small compared to the inequality costs of majoritarianism. In an incentivized experiment with naive participants, we find that a sizable fraction of participants prefers to use a non-deterministic voting method over Plurality Voting to allocate monetary resources. However, this depends critically on their position within the group. Those in the majority show a strong preference for majoritarian voting methods.
    Language: English
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  • 60
    Publication Date: 2024-05-24
    Language: English
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  • 61
    Publication Date: 2024-05-24
    Description: Data and information are central to policy processes, as they frame the policy problem, the design and the implementation of policy, and evaluation of policy impacts. Better data and information infrastructure is expected to lead to better policies and outcomes, for example, by enabling transparent decision making and enhancing capacity and accountability. However, the collection, selection, representation, framing and application of data are not merely technical and apolitical procedures, but are dependent on the interests represented in the policy processes they aim to inform. Social scientists have pointed to the “politics of numbers” and their effects on forests and trees and on the people relying on them, as well as on those involved in their measurements. We use the case of the Reducing Emissions from Deforestation and Forest Degradation (REDD+) international initiative and focus on the central aspect of understanding drivers of deforestation and measures of REDD+ performance to unpack the politics of policy processes. Data and information are socially constructed, and their interpretations are shaped by the contexts in which they emerge. Dominant beliefs in the transformative power of new data and technologies cannot explain why, often, new information does not translate into policy change and action to halt deforestation. Technological advances in making new and ever larger amounts of data available for analysis are a necessary yet insufficient condition for changing the business as usual in deforestation. Through openness, reflexivity and the tackling of silences in data and information related to the global political economy of deforestation the scientific community can make a key contribution to more equitable policy change.
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  • 62
    Publication Date: 2024-05-24
    Description: The Mufushan area, which has abundant rare-metal pegmatites within and around the Mufushan Granite Complex, has become a major target for Ta-Nb-(Li-Be) exploration in South China. The age and origin of the pegmatites and associated rare-metal mineralization are still under debate. Here, we report the in situ U-Pb ages and geochemical characteristics of granites and pegmatites in the Guanyuan and Duanfengshan districts, which are located in the central and northern parts of the Mufushan Complex. Combined zircon, apatite and monazite U-(Th)-Pb dating revealed that biotite, two-mica, and muscovite granites from the Guanyuan and Duanfengshan districts were emplaced at 143–139 Ma, which overlaps with the U-Pb ages of columbite-group minerals (CGM) from different internal zones of the Duanfengshan pegmatites (142–140 Ma). Whole-rock major and trace element compositions and Sr-Nd-Hf isotope data reveal that the granites and pegmatites experienced continuous evolution from biotite, two-mica, and muscovite granites to pegmatite and that the magma originated from the partial melting of mica schists that are abundant in the Mufushan area. Temporal, chemical and mineralogical evidence indicates a genetic link between muscovite granite and Ta-Nb pegmatites. The textures and chemical compositions of CGM from different pegmatites exhibit features typical of magmatic CGM, indicating that fractional crystallization was the driving force that promoted Ta-Nb enrichment. The increasing alumina satu- ration index [ASI: molar Al/(Ca–1.67P + Na + K)] of pegmatitic melt due to albite crystallization may have been the main factor controlling CGM deposition, explaining why major Ta-Nb mineralization is bound to albite pegmatites. The Duanfengshan and other rare-metal pegmatites in the Mufushan area are derivatives of the most evolved granitic facies (i.e., muscovite granite) of the Mufushan Complex. The Duanfengshan and Renli pegmatite fields indicate that the Early Cretaceous (~140 Ma) may have been an important, underappreciated epoch for the formation of pegmatite-related rare-metal resources in the Mufushan area and beyond in South China.
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  • 63
    Publication Date: 2024-05-24
    Description: The St1 Deep Heat Project was started in 2014 by the Finnish energy companies St1 and Fortum. This site is at Fortum's district heating plant at the Aalto University campus, west of Helsinki. The project began with the drilling of a cored 2015 m pilot hole, which encountered a few meters of alluvium over the expected crystalline basement. Follow-on ~6000 m deviated injection-andproduction wells were completed in 2018 and 2020. These wells were extensively logged, and the deep wells were stimulated after completion. In Oct 2018 the ~2500 m to ~5000 m vertical portion of the injection well was profiled with the GFZ German Geoscience Center 17 level, 10 m spaced Sercel borehole geophone array (a Vertical Seismic Profile - VSP). Near-surface shots at 4 offset and 1 near-well shot-points were used as sources. These data were analyzed and compared to (a) drilling data, (b) logging data, (c) surface geology, and (d) a short run of Seismic While Drilling (SWD) data recorded in the pilot hole using hammer-drill signals from the production hole. The VSP data establishes that a seismic velocity reversal - from a P-velocity of ~6.5 to ~6.1 km/s - extends from ~3000 m down at least to the bottom VSP position at 5000 m and is also seen in the well logs. Aside from several shallower structures, the most significant reflection feature found in these data is a ~400 m thick horizon that intersects the ~6000 m wells at ~5000 m. This horizon includes internal reflections that appear to correlate with a drilling-encountered and loginterpreted fracture zone. Owing to complex surrounding velocity structure, this feature's lateral continuation and ultimate attitude have been difficult to resolve. In one interpretation it appears as a 45 ENE dipping extension of a shallower reflector seen in the SWD data. The productionwell's trajectory was based on this interpretation - which drilling seems to confirm. Its consequences for the EGS project will be tested with a circulation campaign over the next months.
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  • 64
    Publication Date: 2024-05-24
    Description: Geomechanics play an important role in any underground activity, such as carbon dioxide (CO2) and hydrogen (H2) geo-storage, owing to the considerable hazards linked to the injection and withdrawal of fluids into and from the subsurface. In order to quantify these risks, knowledge of full stress tensor is required. Yet, most of our stress information in the Australian target basins for geo-storage is limited to the stress orientations, while stress magnitude data is sparse. 3D geomechanical modelling has proved to be an invaluable tool for prediction of full stress tensor. Nevertheless, a model requires some stress magnitude data in order to tune the model to be representative of real stress state. In situations where stress magnitude data is lacking, this means that the model is susceptible to significant uncertainties. Herein, we present a novel strategy for stress modelling, which involves the utilisation of indirect data such as borehole breakouts, drilling-induced fractures, seismic activity records, and formation integrity tests to calibrate a 3D geomechanical model. We employ the northern Bowen Basin, an onshore basin in Queensland, Australia, as a case study for a comprehensive 3D geomechanical modelling approach. We assess all the indirect information in the model’s volume to narrow down the model predictions and find the most reliable stress state. This innovative approach is an important step forward in stress modelling of Australian basins, where lack of stress magnitudes is a great challenge for geomechanical assessment of geo-storage.
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  • 65
    Publication Date: 2024-05-24
    Description: The ionosphere is an ionized part of the upper atmosphere, where the number of free electrons is large enough to affect the propagation of radio signals, including those of the GNSS systems. The knowledge of electron density values in the ionosphere is crucial for both industrial and scientific applications. Here, we develop a novel empirical model of electron density in the topside ionosphere using the radio occultation profiles collected by the CHAMP, GRACE, and COSMIC missions. We assume a linear decay of scale height with altitude and model four parameters, namely the F2-peak density and height (NmF2 and hmF2) and the slope and intercept of the linear scale height decay (dHs/dh and HO). The resulting model (NET) is based on feedforward neural networks. The model inputs include the the geographic and geomagnetic position, the solar flux and geomagnetic indices. The resulting density reconstructions are validated on more than a hundred million in-situ measurements from CHAMP, CNOFS and Swarm satellites, as well as on the GRACE/KBR data, and the developed NET model is compared to several topside options of the International Reference Ionosphere (IRI) model. The NET model yields highly accurate reconstructions of the topside ionosphere and gives unbiased predictions for different locations, seasons, and solar activity conditions.
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  • 66
    Publication Date: 2024-05-24
    Description: Continental subduction is the major cause of regional heterogeneities in the lithospheric mantle and contrasting types of magmatism and mineralization in post-collisional settings. We illustrate the relation between the nature of the subducted crust and the character of magmatism for the Late Miocene New Guinea Orogen that formed by the collision of the Australian continental margin with an island arc. The bipartite nature of the subducted Australian plate margin, with Precambrian crust in the west and Phanerozoic accreted arcs in the east, is reflected in the contrasting magmatism along the strike of the New Guinea Orogen. The chemical signature of the subducted crust is particularly prominent in small-volume Late Miocene–Quaternary ultrapotassic rocks of New Guinea. In the west, ultrapotassic lavas have low εNd values (−12.6 to −20.9), indicating the recycling of ancient continental material. Conversely, high εNd values of +3.5 to +4.5 are found in ultrapotassic lavas from eastern New Guinea. This suggests recycling of juvenile continental material, similar to the orthogneisses exposed in the Late Miocene ultrahigh-pressure metamorphic complex of the D'Entrecasteaux Islands. By comparison with ultrapotassic rocks from other orogenic belts, we show that crustal recycling is responsible for regionally contrasting redox conditions in the lithospheric mantle, which may explain why porphyry-type deposits are important in some regions but absent in others.
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  • 67
    Publication Date: 2024-05-24
    Description: Teleseismic back-projection imaging has emerged as a powerful tool for understanding the rupture propagation of large earthquakes. However, its application often suffers from artifacts related to the receiver array geometry. We developed a teleseismic back-projection technique that can accommodate data from multiple arrays. Combined processing of P and pP waveforms may further improve the resolution. The method is suitable for defining arrays ad-hoc to achieve a good azimuthal distribution for most earthquakes. We present a catalog of short-period rupture histories (0.5-2.0 Hz) for all earthquakes from 2010 to 2022 with Mw {greater than or equal to} 7.5 and depth less than 200 km (56 events). The method provides automatic estimates of rupture length, directivity, speed, and aspect ratio, a proxy for rupture complexity. We obtained short-period rupture length scaling relations that are in good agreement with previously published relations based on estimates of total slip. Rupture speeds were consistently in the sub-Rayleigh regime for thrust and normal earthquakes, whereas a tenth of strike-slip events propagated at supershear speeds. Many rupture histories exhibited complex behaviors, e.g., rupture on conjugate faults, bilateral propagation, and dynamic triggering by a P wave. For megathrust earthquakes, ruptures encircling asperities were frequently observed, with down-dip, up-dip, and balanced patterns. Although there is a preference for short-period emissions to emanate from central and down-dip parts of the megathrust, emissions up-dip of the main asperity are more frequent than suggested by earlier results. The data are presented as follows (and described in detail in the associated README): SUPPORTING DATA SET S1 (2024-001_Vera-et-al_Supporting-Data-S1.zip) This Data Set (S1) consists of *.bp files containing (1) short-period earthquake rupture patterns, (2) energy radiated maps, and (3) source time functions derived from back-projections (0.5-2.0 Hz). The Data Set S1 includes 56 folders, representing 56 processed earthquakes between 2010 and 2022 with a moment magnitude (Mw) greater than or equal to 7.5 and a depth less than 200 km. These folders are labeled in the format YYYYMMDDhhmm_EVENT_NAME_REGION (UTC) in *.bp format. SUPPORTING DATA SET S2 (2024-001_Vera-et-al_Supporting-Data-S2.csv) This Data Set (S2) comprises a *.csv file containing earthquake source information used in the back-projection and the resulting ruptur...
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  • 68
    Publication Date: 2024-05-24
    Description: Landslides are a major type of natural hazard that cause significant human and economic losses in mountainous regions worldwide. Optical and synthetic aperture radar (SAR) satellite data are increasingly being used to support landslide investigation due to their multi-spectral and textural characteristics, multi-temporal revisit rates, and large area coverage. Understanding landslide occurrence, kinematics and correlation to external triggering factors is essential for landslide hazard assessment. Landslides are usually triggered by rainfall and thus, are often covered by clouds, which limits the use of optical images only. Exploiting SAR data, and their cloud penetration and all weather measurement capability, provides more precise temporal characterization of landslide kinematics and its occurrence. However, except for a few research studies, the full potential of SAR data for operational landslide analysis are not fully exploited yet. This is a very demanding task, considering the availability of a vast amount of Sentinel-1 data that have been globally available since October 2014.In this presentation we summarise all the achievements that were made within the framework of MultiSat4SLOWS project (Multi-Satellite imaging for Space-based Landslide Occurrence and Warning Service), financed within the Helmholtz Imaging 2020 call. The project aims on developing a multi-sensor approach for detection and analysis of the landslide occurrence time and its spatial extent using freely available SAR data from Sentinel-1. Within this project, we generated a reference database based on Sentinel-1 and -2 data for training, testing and validation of deep learning algorithms. The reference database contains various landslide examples that occurred worldwide and include pre- and post-event polarimetric, coherence and backscatter features. Also, we investigated the applicability of SAR/InSAR time-series data for landslide time detection. Finally, we introduce a prototype of a Visual Analytics platform for rapid landslide analysis of spatial and temporal ground deformation patterns and correlation with external triggering factors.
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  • 69
    Publication Date: 2024-05-24
    Description: In geosciences, machine learning (ML) has become essential for solving complex problems, such as predicting natural disasters or analysing the impact of extreme temperatures on mortality rates. However, the integration of ML into geoscience scenarios faces significant challenges, especially in explaining the influence of hyperparameters (HP) on model performance and model behaviour in specific scenarios. The Explainable Artificial Intelligence (XAI) system ClarifAI developed at GFZ addresses these challenges by combining XAI concepts with interactive visualisation. ClarifAI currently provides users with two interactive XAI methods: HyperParameter Explorer (HPExplorer) and Hypothetical Scenario Explorer (HSExplorer). HPExplorer allows interactive exploration of the HP space by computing an interactive tour through stable regions of the HP space. We define a stable region in HP space as a subspace of HP space in which ML models show similar model performance. We also employ HP importance analysis to deepen the understanding of the impact of separate HPs on model performance.The Hypothetical Scenarios Explorer (HSExplorer) helps users explore model behaviour by allowing them to test how changes in input data affect the model's response. In our presentation, we will demonstrate how HSExplorer helps users understand the impact of individual HPs on model performance. As ClarifAI is an important research area in our lab, we are interested in discussing relevant XAI challenges with the XAI community in ESSI. Our goal is to create a comprehensive set of tools that explain the mechanics of ML models and allow practitioners to apply ML to a wide range of geoscience applications.
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  • 70
    Publication Date: 2024-05-24
    Description: Subduction zones are critical sites for recycling of Li and B into the mantle. The way of redistribution of Li and B and their isotopes in subduction settings is debated, and there is a lack of detailed studies on Li and B partitioning between minerals of different types of eclogites and the host rocks of the eclogites. We present Li and B concentration data of minerals and Li and B whole-rock isotope data for low-T and high-T eclogites and their phengite schist host rocks from the Changning–Menglian suture zone, SW China. Omphacite controls the Li budget in both the low-T and high-T eclogites. Low-T eclogites have Li and δ7Li values (8.4–27.0 ppm, – 5.5 to + 3.2 ‰) similar to the phengite schists (8.7–27.0 ppm, – 3.8 to + 3.0 ‰), suggesting that Li was added to low-T eclogites from the phengite schists. In contrast, high-T eclogites have much lower δ7Li values (– 13.2 to – 5.8 ‰) than the phengite schists, reflecting prograde loss of Li or exchange with wall rocks characterized by low δ7Li values. Phengite and retrograde amphibole/muscovite are the major B hosts for low-T and high-T eclogites, respectively. The budgets and isotopic compositions of B in eclogites are affected by the infiltration of fluids derived from phengite schists, as indicated by eclogite δ11B values (– 15.1 to – 8.1 ‰) overlapping with the values of the phengite schists (– 22.8 to – 9.5 ‰). Lithium and B in eclogites are hosted in different mineral phases that may have formed at different stages of metamorphism, implying that the contents and isotopic compositions of Li and B may become decoupled during subduction-related fluid-mediated redistribution. We suggest a mineralogical control on the redistribution of Li and B in eclogites during subduction and the exchange of Li and B with the immediate wall rocks. The observed contrasting Li and B isotopic signatures in eclogites are likely caused by a fluid-mediated exchange with different types of wall rocks during both prograde metamorphism and exhumation.
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  • 71
    Publication Date: 2024-05-24
    Description: Large-scale physics-based groundwater flow models are indispensable tools to contribute to an understanding required to manage our present and future water resources. For instance, large finite-element-based models can encompass up to 108 finite elements and require high performance computing environments to run. To effectively use such models for prediction and scenario analysis, proper calibrations against observation data are required. For calibration, two major challenges arise: 1) the high amount of time and computational resources required for the numerous model runs, and, 2) the high complexity of parameter optimization for heterogeneous domains that translates into multiple potentially suitable calibrations. Here, we provide a solution by integrating data science methods for meta modeling with Bayesian optimization and visual analytics into calibration workflows for physics-based groundwater flow models. With the open source simulator OpenGeoSys we developed a virtual aquifer (VA) model that serves as ground truth. From this we derived groundwater flow models with perturbed parameters for calibration. In our calibration method, we use machine-learning algorithms (e.g. Gaussian process regression) to build fast meta (surrogate) models of the physics-based groundwater flow model in order to explore the calibration parameter space in a step-wise interactive Bayesian optimization routine. In this routine, visual analytic tools (e.g. GCex) provide insights into the calibration progress and parameter sensitivities, which allow the modeler to analyze potential solutions and/or adjusting further steps in the optimization routine. In this way we are able to effectively combine the modelers expert knowledge with an intelligent parameter optimization strategy that allows the calibration of large and complex groundwater flow models with a minimum of computational resources.
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  • 72
    Publication Date: 2024-05-24
    Description: Iron tailings are crystalline powders predominantly composed of iron (Fe) and silicon dioxide (SiO2). Spatially characterizing of the physical and chemical properties of iron tailings is greatly important for optimal utilization and proper disposal of tailings. Visible–near infrared–shortwave infrared (VIS–NIR–SWIR; 350–2500 nm) spectroscopy offers a rapid, non-destructive, and cost-effective method for quantitatively analyzing tailings properties. The main objective of this study was to map the spatial distribution of total Fe (TFe) and SiO2 content in a tailings dam through the use of laboratory spectra and GF-5 hyperspectral imagery based a calibration transfer model approach. A total of 77 samples were collected from the surface of targeting field and scanned by a laboratory VIS–NIR–SWIR reflectance spectrometer. The competitive adaptive re-weighted sampling (CARS) algorithm was applied to select important spectral features. Subsequently, different spectral indices were calculated to enhance the prediction performance of the calibration models. Rulefit and random forest (RF) algorithms were used to calibrate spectral information with associated tailing properties. The results showed that the Rulefit algorithm with selected feature bands and calculated spectral indices yielded the highest estimation accuracy for TFe (R2 = 0.86, RMSE = 1.30%, LCCC = 0.87 and bias = -0.45) and SiO2 (R2 = 0.74, RMSE = 2.00%, LCCC = 0.84 and bias = 0.38). The direct standardization (DS) algorithm was applied to correct GF-5 hyperspectral images and enhance the efficiency of calibration model transfer process. Finally, the Rulefit models were transferred to corrected GF-5 hyperspectral images for mapping the spatial distribution of TFe and SiO2 contents. Our results demonstrated the possibility of successful transfer of laboratory spectral-based model to the GF-5 hyperspectral imagery for mapping spatial distribution of tailing compositions. This finding can be applied for efficiently recovering valuable metals and minimizing environmental risks.
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  • 73
    Publication Date: 2024-05-24
    Description: Research data and software are widely accepted as an outcome of scientific work. However, in comparison to text-based publications, there is not yet an established process to assess and evaluate quality of research data and research software publications. This paper presents an attempt to fill this gap. Initiated by the Working Group Open Science of the Helmholtz Association, the Task Group Helmholtz Quality Indicators for Data and Software Publications currently develops a quality indicator for research data and research software publications to be used within the Association. This report summarizes the vision of the group of what all contributes to such an indicator. The proposed approach relies on generic well-established concepts for quality criteria, such as the FAIR Principles and the COBIT Maturity Model. It does – on purpose – not limit itself to technical implementation possibilities to avoid using an existing metric for a new purpose. The intention of this paper is to share the current state for further discussion with all stakeholders, particularly with other groups also working on similar metrics but also with entities that use the metrics.
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  • 74
    Publication Date: 2024-05-24
    Description: The late Carboniferous/early Permian post-collisional rhyolites (305–285 Ma) that formed in Central Europe have generally similar whole rock compositions to that of older Late-Variscan rhyolites (330–310 Ma). However, data compilation combining zircon age with the chemical composition of rhyolites from 20 units shows a trend of increasing zircon saturation temperature with decreasing age. This trend is particularly well identified in rhyolites from the Central European Lowlands (CEL)—consisting of the NE German and NW Polish Basin—and also correlates their location with the zircon saturation temperature increasing from SE to NW from 750°C to 850°C. We infer that these higher temperatures of zircon saturation reflect a contemporaneous change in the tectonic setting from collisional to divergent, reflecting the onset of the Central European continental rifting. This interpretation is further corroborated by the trace element compositions of the CEL zircons, which resembles zircon crystallized in a divergent setting. Interestingly, the zircon formed globally in this type of setting is chemically diverse, especially considering uranium concentration. For example, zircon from locations dominated by mafic magma fractionation, such as rhyolites from Iceland, have low U concentrations and low U/Yb ratios. On the other hand, zircon formed in rhyolites in rifted margins, like western North America, tends to have much higher U and U/Yb ratios. Such high concentrations are not observed in zircon from the CEL, suggesting that the mantle input could be higher and residence times within continental crust shorter than those for rhyolites from the Cenozoic western USA. This may, in turn, suggest that the region might have been affected by a hot spot, similar to that responsible for rhyolite formation of the Snake River Plain.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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  • 75
    Publication Date: 2024-05-24
    Description: Landscape evolution models (LEMs) are prime tools for simulating the evolution of source-to-sink systems through ranges of spatial and temporal scales. A plethora of various empirical laws have been successfully applied to describe the different parts of these systems: fluvial erosion, sediment transport and deposition, hillslope diffusion, or hydrology. Numerical frameworks exist to facilitate the combination of different subsets of laws, mostly by superposing grids of fluxes calculated independently. However, the exercise becomes increasingly challenging when the different laws are inter-connected: for example when a lake breaks the upstream–downstream continuum in the amount of sediment and water it receives and transmits; or when erosional efficiency depends on the lithological composition of the sediment flux. In this contribution, we present a method mixing the advantages of cellular automata and graph theory to address such cases. We demonstrate how the former ensure interoperability of the different fluxes (e.g. water, fluvial sediments, hillslope sediments) independently of the process law implemented in the model, while the latter offers a wide range of tools to process numerical landscapes, including landscapes with closed basins. We provide three scenarios largely benefiting from our method: (i) one where lake systems are primary controls on landscape evolution, (ii) one where sediment provenance is closely monitored through the stratigraphy and (iii) one where heterogeneous provenance influences fluvial incision dynamically. We finally outline the way forward to make this method more generic and flexible.
    Type: info:eu-repo/semantics/article
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  • 76
    Publication Date: 2024-05-24
    Description: During the HALO-(AC)³ campaign in March-April 2022 airborne observations were performed with the High Altitude and LOng range research aircraft (HALO) covering the Fram Strait and north polar regions. The flight tracks covered open ocean areas, the marginal sea ice zone, and closed sea ice cover. Furthermore, cloud conditions were observed during air mass transformation events as marine cold air outbreaks and warm air intrusions. This data set summarizes the flight tracks of HALO and provides longitude, latitude, and altitude defined as position above WGS84. All data are measured by the Basic HALO Measurement and Data System (BAHAMAS) and resampled to 1 Hz temporal resolution.
    Keywords: AC3; airborne; Arctic; Arctic Amplification; Atmospheric and Earth System Research with HALO – High Altitude and Long Range Research Aircraft; GPS; HALO; HALO-(AC)³; SPP1294; track
    Type: Dataset
    Format: application/zip, 17 datasets
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  • 77
    Publication Date: 2024-05-24
    Description: Macroalgae such as kelp are important ecosystem engineers in the Polar Regions and potentially affected by freshening and ocean warming. The endemic Arctic kelp Laminaria solidungula might be particularly imperiled and become locally extinct from Arctic fjord systems in the future, since temperature increase is most pronounced in the Polar Regions. Additionally, increased temperatures cause glacier and sea ice melting and enhancing terrestrial run-off from snowfields, which eventually can result in hyposaline conditions in fjord systems. We conducted a multiple-stressor experiment at four temperatures (0, 5, 10, 15 °C) and two salinities (SA 25, 35) over 14 days to investigate the combined effects of increasing temperature and decreasing salinities on young L. solidungula sporophytes. The experiment was conducted with laboratory cultures (AWI culture number 3130) at Alfred Wegener Institute - Helmholtz Centre for Polar and Marine Research, Bremerhaven in February 2018. As physiological parameter, the maximum photosynthetic quantum yield of photosystem II (Fv/Fm; Imaging-PAM) was monitored every fourth day with an Imaging-PAM (Walz GmbH Mess- und Regeltechnik, Effeltrich, Germany). The total nitrogen, total carbon content was analyzed with an elemental analyzer and the C:N ratio calculated. Phlorotannins, mannitol as well as absolute pigment concentrations were analyzed using a HPLC and the deepoxydation state of the xanthophyll cycle (DPS) calculated.
    Keywords: beta-Carotene; C:N; Carbon, per dry mass; Carbon/Nitrogen ratio; Chlorophyll a; Chlorophyll c2; De-expoxidation state of xanthophyll cycle; DPS; Family; Fucoxanthin; Fv/Fm; High Performance Liquid Chromatography (HPLC); Imaging-PAM (Walz GmbH Mess- und Regeltechnik, Effeltrich, Germany); kelp; Mannitol; Maximum quantum yield of photosystem II; Multiple-stressor; Nitrogen, per dry mass; Phlorotannins; Replicate; Species; Treatment: salinity; Treatment: temperature; Violaxanthin + Antheraxanthin + Zeaxanthin
    Type: Dataset
    Format: text/tab-separated-values, 2212 data points
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  • 78
    Publication Date: 2024-05-24
    Description: The file includes the respiration rate (milligrams of Oxygen per gram of dry mass (without tunic) per day) of three antarctic solitary ascidians (Cnemidocarpa verrucosa, Molgula pedunculata and Ascidia challengeri) under increasing sediment concentrations (from natural seston (NS) to NS + Additional Suspended particulate matter (SPM) from 5 to 400 mg/L). Individuals were sampled carefully by SCUBA diving during austral summer 2006-2007 in Potter Cove (58°43'5.214"W; 62°14'24.184"S) at 20 m depth. Experiments where performed after acclimation to aquarium conditions in the Dallmann laboratory on Carlini station (58°43'5.214"W; 62°14'24.184"S).
    Keywords: Antarctica; ascidians; DIVER; Experimental treatment; invertebrates; Metabolic rate of oxygen, per dry mass; metabolism; PotterCove_SCUBA_06-07; Potter Cove, King George Island, Antarctic Peninsula; Respiration rate; Sampling by diver; sedimentation; Species; Specimen identification
    Type: Dataset
    Format: text/tab-separated-values, 770 data points
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  • 79
    Publication Date: 2024-05-24
    Description: The presented dataset contains chamber measurements of methane transport (mg CH₄ g dry plant mass-1 day-1) through individual aerenchymous peatland plants and the ancillary data for these measurements. Chamber measurements were performed for 7 plant species at two peatland sites, an oligotrophic fen and an ombrotrophic bog part of Siikaneva peatland complex in Southern Finland (61.8249° N, 24.1390° E, altitude 170 m a.s.l.) , during growing seasons 2013 and 2014 (between 1st of May and 28th of October). The ancillary data contains measurements of water table depth from the moss surface, air and peat temperature during the measurement as well as leaf area, dry mass of plant material, specific leaf area, number of leaves and the proportion of brown leaves in each sample that was measured. The dataset was collected to quantify the impact of plant species, plant properties and environmental factors on methane transport through aerenchymous plants. Plant CH₄ transport rate was measured using custom-made cylinder-shaped chambers that varied in volume between 0.7 and 5.0 liters. A plant sample of 2–104 leaves (depending on the growth form of the measured plant) belonging to the same species was separated from the peat and moss underneath by two plexiglass plates that were attached together with a hinge and had a smooth rubber seal between them to avoid compression of the plant. The proportion of green leaves in the sample varied from 0 to 100 % depending on the phase of the growing season. The sample was then covered with an opaque plastic chamber that was sealed with the plate by a smooth rubber seal attached to the bottom of the chamber. Airtightness of the system was ensured by tightening a belt that extended from one plate to the other over the chamber. Finally, a rubber stopper was used to seal a vent hole in the top of the chamber. Each plant sample was measured for 35 minutes, during which four 20 ml air samples were drawn from the chamber with a syringe through the rubber stopper in the top of the chamber at 5, 15, 25 and 35 minutes after chamber closure. The air samples were then injected into evacuated 12 ml glass vials (Labco Limited, UK). Simultaneous to the flux measurements, temperatures in the chamber (air) and peat at 5, 15 and 30 cm depth were recorded. WT was measured from a perforated plastic tube installed into the peat next to the sample after the WT level in the tube had stabilized for at least 30 minutes. After the flux measurement, the plant sample was cut with scissors and transported to the laboratory in a plastic bag. In each plant sample, the number of leaves was counted, the leaf area of brown and green leaf parts was measured with a scanner, and the dry weight was obtained for brown and green leaf parts separately after oven drying the sample at 60 °C for 24 hours. Using these data, specific leaf area (SLA, m²/g) was calculated for each sample. CH₄ concentration in the glass vials was analyzed with an Agilent Technologies 7890A gas chromatograph and Gilson GX-271 liquid handler. The CH₄ flux was calculated as the linear change in CH~4~ concentration in relation to time, chamber volume and temperature. Nonlinear changes in CH₄ concentration that were visually detected, were surmised to have resulted from a leak in the chamber or in the vial and were excluded from the analysis. In total 6 % of the measurements were excluded from the final dataset due to such nonlinearities.
    Keywords: Aerenchymous_peatland_plants-experiment; aerenchymous plant; Brown leaf area/leaf area, total, ratio; DATE/TIME; Day of the year; Gas chromatography on an Agilent Technologies 7890A GC; Green plant, biomass as dry weight; In situ incubation chamber; ISCHAM; Leaf area; Methane efflux, CH4, per dry mass plant; Methane emissions; Methane flux; Number of leaves; Peatland; Plant; Plant, biomass as dry weight; Sample code/label; sedge; Site; Southern Finland; Specific leaf area; Temperature, air; Temperature, peat; Water table depth; wetland
    Type: Dataset
    Format: text/tab-separated-values, 9026 data points
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  • 80
    Publication Date: 2024-05-24
    Description: Ocean acidification and warming may threaten future seafood production, safety and quality by negatively impacting the fitness of marine species. Identifying changes in nutritional quality, as well as species most at risk, is crucial if societies are to secure food production. Here, changes in the biochemical composition and nutritional properties of the commercially valuable oysters, Magallana gigas and Ostrea edulis, were evaluated following a 12-week exposure to six ocean acidification and warming scenarios that were designed to reflect the temperature (+3 °C above ambient) and atmospheric pCO2 conditions (increase of 350–600 ppm) predicted for the mid-to end-of-century. Results suggest that O. edulis, and especially M. gigas, are likely to become less nutritious (i.e. containing lower levels of protein, lipid, and carbohydrate), and have reduced caloric content under ocean acidification and warming. Important changes to essential mineral composition under ocean acidification and warming were evident in both species; enhanced accumulation of copper in M. gigas may be of concern regarding consumption safety. In light of these findings, the aquaculture industry may wish to consider a shift in focus toward species that are most robust to climate change and less prone to deterioration in quality, in order to secure future food provision and socio-economic benefits of aquaculture.
    Keywords: Alkalinity, total; Alkalinity, total, standard deviation; Animalia; Aragonite saturation state; Aragonite saturation state, standard deviation; Ash; Benthic animals; Benthos; Bicarbonate ion; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calcite saturation state; Calcite saturation state, standard deviation; Calcium; Calculated using CO2SYS; Calculated using seacarb after Nisumaa et al. (2010); Caloric content, per dry mass; Carbon, inorganic, dissolved; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Coast and continental shelf; Condition index; Copper; Crassostrea gigas; EXP; Experiment; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Iron; Laboratory experiment; Lipids; Magnesium; Moisture; Mollusca; North Atlantic; Number; OA-ICC; Ocean Acidification International Coordination Centre; Ostrea edulis; Other studied parameter or process; Partial pressure of carbon dioxide, standard deviation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); pH; pH, standard deviation; Plymouth_Sound; Potassium; Potentiometric; Potentiometric titration; Proteins; Replicate; Salinity; Salinity, standard deviation; Sample ID; Selenium; Single species; Sodium; Species, unique identification; Species, unique identification (Semantic URI); Species, unique identification (URI); Temperate; Temperature; Temperature, water; Temperature, water, standard deviation; Treatment; Type; Zinc
    Type: Dataset
    Format: text/tab-separated-values, 11142 data points
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  • 81
    Publication Date: 2024-05-24
    Description: This dataset contains sedimentary parameters pigments (Chlorophyll a, Pheophorbide, Pheophytin) measured from Multicorer (MUC) samples from the Global Sea Mineral Resources (GSR, Belgium) license area in the Clarion Clipperton Fracture Zone (CCFZ) collected on onboard the Norwegian Island Pride during expeditions Mangan21 in 2021. Pigment analysis was completed according to Van Heukelem and Thomas (2001). After addition of 90% acetone, freeze-dried samples were sonicated and extracted overnight at 4°C. After filtration, the extract was injected into an Agilent HPLC with fluorescence detector (type 1200 Infinity II, Agilent Technologies, Diegem, Belgium) equipped with an Eclipse XDB C8 column. The sum of Chl-a and phaeopigment concentrations was calculated and is referred to as the Chloroplast Pigment Equivalent (CPE). These data were collected to quantify primary productivity in the CCFZ and to correlate these values to observed levels of biodiversity. Values are given in their respective units (SI) and have been collected and measured by the Marine Biology Research Group of Ghent University (Belgium).
    Keywords: Abiotic; Area/locality; Calculated; Chlorophyll a, per dry mass; Chloroplastic pigment equivalents; Clarion Clipperton Fracture Zone; Core; Date/Time of event; Deep sea; Deployment number; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Depth comment; Elevation of event; Event label; High performance liquid chromatography (HPLC) using an Agilent 1200 Infinity II HPLC with fluorescence detector and Eclipse XDB C8 column; IP21; IP21_005MUC; IP21_019MUC; IP21_020MUC; IP21_024MUC; IP21_030MUC; IP21_031MUC; IP21_040MUC; IP21_041MUC; Island Pride; JPI Oceans - Ecological Aspects of Deep-Sea Mining; JPIO-MiningImpact; Latitude of event; Longitude of event; MANGAN21; MUC; MultiCorer; North Pacific Ocean; Pheophorbide a, per dry mass; Pheophorbide a-like, per dry mass; Pheophytin a, per dry mass; Pheophytin a-like, per dry mass; pigments; Sample code/label; Station label; Type
    Type: Dataset
    Format: text/tab-separated-values, 1056 data points
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  • 82
    Publication Date: 2024-05-24
    Description: Samples were collected between 03/26/2018 and 04/27/2018 around the northern tip of the Antarctic Peninsula (63° 0' 1.843'' S, 60° 0' 16.901''W) onboard the RV Polarstern during the PS112 campaign in order to identify the elemental composition and stoichiometry of the Antarctic krill (Euphausia superba) and salps (Salpa thompsoni). The sampling stations were situated in the survey grid of the Antarctic Marine Living Resources Program (AMLR). At the time of sampling, the study area was ice free and ambient Chlorophyll a levels were comparable to previous studies in this time frame (e.g. Schofield et al., 2017). The phytoplankton community was dominated by dinoflagellates, diatoms and prymnesiophytes, which is typical for autumn (March–May) around the NAP (Pauli et al., 2021). Krill and salps were sampled by using the 1.8 m² Isaacs-Kidd Midwater Trawl Net (IKMT) equipped with a 505 μm mesh which is suitable to collect both salps and krill in good condition. The net was towed obliquely to 170 m, or 20 m from the bottom, at a speed of 2 kts. Size in mm (using graph paper, Seibert publisher) and stage of krill and salp individuals were determined on board before further processing. Prior to the elemental analysis, the digestive system of krill and salps was dissected and stored at -20 °C to determine the elemental signature of the gut content. Salp individuals were immediately dissected on board, krill individuals were frozen on board and dissected later in the lab. Measurements of gut elemental composition were done on 50 and 16 samples for krill and salps, respectively. Prior to the analyses each sample was homogenized with 500 µl distilled water. For the carbon/nitrogen (C/N) samples, 250 µl of the homogenate were transferred into pre-weighed tin capsules while the rest of the homogenized tissue was transferred into pre-weighed glass tubes for phosphorus analysis. Samples were dried at 70 °C for three weeks prior to analysis. After drying, we measured the dry weight (DW) of all samples by using a high-resolution balance (Mettler Toledo, XP-26). After drying, all C/N samples were sealed and analyzed using a CHN analyzer (Thermo, Flash EA 1112). The phosphorus samples were combusted at 450 °C for 5 hours and the ash-free dry weight (AFDW) was measured. Particulate organic phosphorus (POP) was measured photometrically by molybdate reaction after sulfuric acid and heat digestion at 90 °C, modified after (Grasshoff et al., 2009).
    Keywords: Abbreviation; ANT-XXXIII/3; Ash free dry mass; Biomass, ash free dry mass, per dry mass; Biomass as carbon; Biomass as nitrogen; Biomass as phosphorus; Calculated; Carbon, organic, total; Carbon, per dry mass; Carbon, total, per dry mass; Carbon/Nitrogen ratio; Carbon/Phosphorus ratio; Carbon and hydrogen and nitrogen (CHN) analyzer, Thermo Scientific, FlashEA 1112; Comparator balance, Mettler Toledo, XP26; Cruise/expedition; DATE/TIME; Euphausia superba; Event label; Gear; Gut content, dry mass; IKMT; Isaac-Kid-Midwater Trawl; krill; LATITUDE; Length, total; Life stage; LONGITUDE; Nitrogen, organic, total; Nitrogen, per dry mass; Nitrogen, total, per dry mass; Nitrogen/Phosphorus ratio; Organ; Phosphorus, organic, total; Phosphorus, per dry mass; Phosphorus, total, per dry mass; Polarstern; Population Shift and Ecosystem Response – Krill vs. Salps; POSER; PS112; PS112_25-4; PS112_50-3; salps; Sample code/label; Scotia Sea; Sex; Southern Ocean; Species; Species, unique identification (URI); stoichiometry; Tunicata; West Antarctic Peninsula; Zooplankton
    Type: Dataset
    Format: text/tab-separated-values, 1808 data points
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  • 83
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20104; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 560736 data points
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  • 84
    Publication Date: 2024-05-24
    Description: Coralline algae, a major calcifying component of coastal shallow water communities, have been shown to be one of the more vulnerable taxonomic groups to ocean acidification (OA). Under OA, the interaction between corallines and epiphytes was previously described as both positive and negative. We hypothesized that the photosynthetic activity and the complex structure of non-calcifying epiphytic algae that grow on corallines ameliorate the chemical microenvironmental conditions around them, providing protection from OA. Using mesocosm and microsensor experiments, we showed that the widespread coralline Ellisolandia elongata is less susceptible to the detrimental effects of OA when covered with non-calcifying epiphytic algae, and its diffusive boundary layer is thicker than when not covered by epiphytes. By modifying the microenvironmental carbonate chemistry, epiphytes, facilitated by OA, create micro-scale shield (and refuge) with more basic conditions that may allow the persistence of corallines associated with them during acidified conditions. Such ecological refugia could also assist corallines under near-future anthropogenic OA conditions.
    Keywords: Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Aragonite saturation state, standard deviation; Benthos; Bicarbonate ion; Bicarbonate ion, standard deviation; Biomass, ash free dry mass; Biomass, ash free dry mass, standard deviation; Bottles or small containers/Aquaria (〈20 L); Calcification/Dissolution; Calcification rate, standard deviation; Calcite saturation state; Calcite saturation state, standard deviation; Calculated using CO2calc; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbonate ion; Carbonate ion, standard deviation; Carbonate system computation flag; Carbon dioxide; Carbon dioxide, aquatic; Carbon dioxide, standard deviation; Coast and continental shelf; Distance; Ellisolandia elongata; EXP; Experiment; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Laboratory experiment; Macroalgae; Mediterranean_coast_of_Israel; Mediterranean Sea; Net calcification rate of calcium carbonate; Net photosynthesis rate, oxygen; Net photosynthesis rate, standard deviation; OA-ICC; Ocean Acidification International Coordination Centre; Other; Other studied parameter or process; Oxygen; Partial pressure of carbon dioxide, standard deviation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); pH; pH, standard deviation; Plantae; Potentiometric; Potentiometric titration; Primary production/Photosynthesis; Respiration; Respiration rate, oxygen, per dry mass; Respiration rate, oxygen, standard deviation; Rhodophyta; Salinity; Single species; Species; Temperate; Temperature, water; Treatment; Treatment: pH; Type of study
    Type: Dataset
    Format: text/tab-separated-values, 7482 data points
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  • 85
    Publication Date: 2024-05-24
    Description: Multibeam data were collected with RV Polarstern along the route of cruise PS138 and data acquisition was continuously monitored during the survey. Multibeam sonar system was Teledyne/Atlas Hydrosweep DS3. SVPs were retrieved from CTD data from other working groups on board. SVPs were processed with HydrOffice SoundSpeedManager (https://www.hydroffice.org/soundspeed/main) and extended with World Ocean Atlas 18 (https://www.ncei.noaa.gov/archive/accession/NCEI-WOA18). SVP data were applied during acquisition. Multibeam data are unprocessed and may contain outliers and blunders and should not be used for grid calculations and charting projects without further editing. The raw multibeam sonar data in Teledyne/Atlas multibeam processing format (.asd) were recorded with Teledyne/Atlas Parastore software as well as Teledyne Reson format (.s7k) in Teledyne PDS. Raw data files can be processed using software packages like CARIS HIPS/SIPS. For updated vessel configuration files check further details.
    Keywords: ArcWatch-1; Bathymetry; Binary Object; Binary Object (File Size); Binary Object (Media Type); Comment; CTD/Rosette; CTD-RO; Data file recording distance; Data file recording duration; DATE/TIME; DS3; ELEVATION; Event label; Extracted with MB-System; File content; LATITUDE; LONGITUDE; Multibeam Echosounder; Number of pings; Polarstern; PS138; PS138_0_Underway-28; PS138_115-1; PS138_145-1; PS138_168-1; PS138_172-1; PS138_174-1; PS138_19-1; PS138_193-1; PS138_195-1; PS138_196-1; PS138_201-1; PS138_207-1; PS138_2-1; PS138_218-1; PS138_22-1; PS138_26-1; PS138_40-1; PS138_69-1; PS138_90-1; Ship speed; Start of data file, depth; Start of data file, heading; Start of data file recording, date/time; Start of data file recording, latitude; Start of data file recording, longitude; Stop of data file, depth; Stop of data file, heading; Stop of data file recording, date/time; Stop of data file recording, latitude; Stop of data file recording, longitude; Swath-mapping system Atlas Hydrosweep DS-3
    Type: Dataset
    Format: text/tab-separated-values, 26459 data points
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  • 86
    facet.materialart.
    Unknown
    PANGAEA
    In:  GEOMAR - Helmholtz Centre for Ocean Research Kiel
    Publication Date: 2024-05-24
    Description: Raw data acquired by position sensors on board RV METEOR during expedition M197 were processed to receive a validated master track which can be used as reference of further expedition data. During M197 the motion reference unit Kongsberg SeaTex AS MRU-5 combined with Kongsberg SeaTex AS Seapath 320 and two C and C Technologies GPS receivers C-NAV3050 were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.bsh.de) with a resolution of 1 sec. Processing and evaluation of the data is outlined in the data processing report. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
    Keywords: 1 sec resolution; CT; DAM_Underway; DAM Underway Research Data; EMS PS; M197; M197-track; Meteor (1986); Underway cruise track measurements
    Type: Dataset
    Format: application/zip, 112.5 MBytes
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  • 87
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 561328 data points
    Location Call Number Expected Availability
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  • 88
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 580044 data points
    Location Call Number Expected Availability
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  • 89
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 580187 data points
    Location Call Number Expected Availability
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  • 90
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 524000 data points
    Location Call Number Expected Availability
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  • 91
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 561050 data points
    Location Call Number Expected Availability
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  • 92
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 580078 data points
    Location Call Number Expected Availability
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  • 93
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 561280 data points
    Location Call Number Expected Availability
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  • 94
    Publication Date: 2024-05-24
    Description: This study simulated a 9-months warming scenario on the common seagrass Zostera marina from winter into summer (December 2015 - August 2016) in the Western Baltic Sea (Kiel Fijord), using outdoor mesocosms. Two treatments were applied: Ambient temperature regime (Ambient) and Ambient + 3.6C (Heat) over the entire course of the experiment. Temperature regimes were compared to the 22-year temperature average in the area. This dataset shows monthly chlorophyll-a and beta-carotene concentration of one shoot per box. Unit is µg per mg of leaf dry weight. The organization of the data is hierarchical: Treatment (Heat, Ambient), Benthocosms number (6 benthocosms per treatment), Seagrass box number (4 boxes per benthocosm).
    Keywords: Benthocosm_A1; Benthocosm_A2; Benthocosm_B1; Benthocosm_B2; Benthocosm_C1; Benthocosm_C2; Benthocosm_D1; Benthocosm_D2; Benthocosm_E1; Benthocosm_E2; Benthocosm_F1; Benthocosm_F2; beta-Carotene, per dry mass; Chlorophyll a, per dry mass; DATE/TIME; Event label; flowering; Identification; Kiel Fjord; MESO; Mesocosm experiment; Seagrass; seasonality; Sea surface temperature rise; Species; thermal tolerance; Treatment; winter warming; Zostera marina
    Type: Dataset
    Format: text/tab-separated-values, 1906 data points
    Location Call Number Expected Availability
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  • 95
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 537546 data points
    Location Call Number Expected Availability
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  • 96
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 560572 data points
    Location Call Number Expected Availability
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  • 97
    Publication Date: 2024-05-24
    Description: The dataset contains energy density values and concentrations in 19 elements analysed in whole bodies of 15 meso- to bathypelagic species sampled in the twilight zone (deep pelagic area) of the Bay of Biscay, North-East Atlantic. The species included 4 crustacean species (Pasiphaea sivado, Sergia robusta, Systellaspis debilis, Ephyrina figueirai) and 11 fish species (Xenodermichthys copei, Searsia koefoedi, Myctophum punctatum, Notoscopelus kroeyeri, Lampanyctus crocodilus, Argyropelecus olfersii, Arctozenus risso, Stomias boa, Serrivomer beanii, Chauliodus sloani, Aphanopus carbo). The elements included 6 major constitutive elements (macro-minerals) and 13 trace elements among which 9 essential (micro-nutrients) and 4 non-essential elements (undesirables, with no know biological function). Specimens were collected during a single fishery in a canyon of the slope of the Bay of Biscay in October 2017, during the EVHOE fishery survey (“Evaluation Halieutique de l'Ouest de l'Europe”; https://doi.org/10.17600/17002300) conducted each autumn by the “Institut Français de Recherche pour l'Exploitation de la Mer” (Ifremer) on R/V Thalassa. A total of 266 individuals belonging to the 15 species were collected at night using a 25 m vertical opening pelagic trawl in the deep scattering layer (ca. 800 m depth in the water column; 1330 m bottom depth). All organisms were collected during one haul of 60 min, at a speed of approximately 4 knots (geographical coordinates at the beginning of the turn/end of the fishing: 45.103°N, -3.543° W). For small fish and crustaceans, organisms belonging to the same species were pooled by individuals of similar sizes. The size of each individual (total length for fish, cephalothorax length for crustaceans, in mm) as well as the total fresh weight of individuals or pools (to the nearest 0.5 g wet mass) were determined on board, and the individuals were rinsed with ultrapure water before storage. Mean individual sizes and fresh wet weights are here reported for each sample constituted by a pool of individuals. Samples (individuals or pools of individuals, N=39 in total) were finally stored at -20°C until further treatment in the laboratory. In clean and contamination-free conditions of the laboratory, whole organisms were briefly thawed and the digestive tracts of fish (i.e. stomachs and intestines) were emptied and put back in individuals. Whole individuals were then cut into small pieces and a first fresh grinding of individuals (or pools of individuals for small fish and crustaceans) was carried out using an Ultra Turrax® type grinder with stainless steel arms. Samples were finally refrozen at -20° C in acid pre-cleaned and calcined (450°C) glass jars, lyophilized during 72 h, and ground again into a fine and homogeneous powder using a stainless-steel knife mill. If necessary, this was completed by ball milling (MM400 Retsch®) using bowls and marbles with zirconium oxide coating. Each material was conscientiously rinsed with a succession of ultrapure water/ethanol/ultrapure water between each sample. Energy density was estimated on dried homogenised samples following Spitz et al. (2010), using a Parr® 1266 semi-micro-oxygen bomb calorimeter and an adiabatic bomb-calorimetry in which gross energy is determined by measuring heat of combustion. Values are presented in kJ/g dry weight and are means of duplicate determination (deviation between two assays 〈2%). Total concentrations of calcium (Ca), potassium (K), magnesium (Mg), sodium (Na), phosphorus (P) and strontium (Sr), as major constitutive chemical elements (macro-minerals) in biological organisms, were determined by inductively coupled plasma atomic emission spectrometry (ICP-OES, Vista-Pro Varian) according to an in-laboratory approved method. Briefly with this method, aliquots of samples (~250 mg dry mass of homogenised powder) were digested using a 6:2 (v/v) mixture with nitric acid (HNO3 69%, Trace Metal Grade®, FisherScientific) and hydrochloric acid (HCl, 34%, Trace Metal Grade®, FisherScientific). Acidic digestion of the samples was performed overnight at room temperature and then in a microwave oven (START-D, Milestone). The digests were finally diluted to 50 mL with ultrapure water before analyses with ICP-OES. Total concentrations of 9 essential – arsenic (As), cobalt (Co), copper (Cu), iron (Fe), manganese (Mn), molybdenum (Mo), selenium (Se), vanadium (V), zinc (Zn) – and 4 non-essential – silver (Ag), cadmium (Cd), lead (Pb) – trace elements were determined by inductively coupled plasma mass spectrometry (ICP-MS, ICAP-Qc ThermoFisher) according to an in-laboratory approved method. Briefly with this method, aliquots of samples (~200 mg of homogenised powder) were placed in Teflon bombs and mineralized with a mixture of ultrapure HNO3 acid (PlasmaPure Plus grade, SCP Science®) and ultrapure water using a microwave (ETHOS-UP, Milestone). The digests were then diluted to 50 ml with ultrapure water before analyses with ICP-MS. Finally, total mercury (Hg) concentrations (a non-essential-element) were determined by atomic absorption spectrophotometry using an Advanced Mercury Analyser (ALTEC AMA-254, Altec Ltd), on aliquots of homogenised powder (50 ± 5 mg), according to the standard operating procedure described in the US-EPA method N°7473 (U.S. Environmental Protection Agency, 1998). The quality assurance of all metal analyses relied on blank and internal standard controls, and on the accuracy and reproducibility of data relative to the certified reference materials (CRMs) used in each analytical run. Blank values were systematically below the detection limits and CRM values concurred with certified concentrations. All elemental concentrations given on a dry weight basis can be converted on a wet weight basis according to the percentage of moisture measured for each sample.
    Keywords: Arsenic; Atomic absorption spectrophotometry (Altec, AMA 254); bathypelagic; Bay of Biscay; Cadmium; Calcium; Calorimetry (Parr 6725 semimicro calorimeter and Parr 6772 precision thermometer); Class; Cobalt; Copper; crustacea; DEPTH, water; Device type; energy density; Energy density, per dry mass; EVHOE-2017; EVHOE-2017_CHP21-V0494; Family; Field observation; fish; GOVT; Grande Ouverture Verticale trawl; ICP-OES, Varian Vista Pro; Identification; inorganic elements; Iron; Lead; Length; macro-minerals; Magnesium; Manganese; Mercury; mesopelagic; Micro-nutrients; Moisture; Molybdenum; Number of individuals; Order; Phosphorus; Phylum; Potassium; S-(Q)-ICP-MS measurements, Thermo Scientific iCAP-Qc ICP-MS; Sample ID; Sample type; Selenium; Silver; Size; Sodium; Species; Station label; Strontium; SUMMER; Sustainable Management of Mesopelagic Resources; temperate marine system; Thalassa; Tissue Descriptor; trace metals; Uniform resource locator/link to reference; Vanadium; Wet mass; Zinc
    Type: Dataset
    Format: text/tab-separated-values, 1465 data points
    Location Call Number Expected Availability
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  • 98
    Publication Date: 2024-05-24
    Description: Ongoing climate change is leading to warmer and more acidic oceans. The future distribution of fish within the oceans depends on their capacity to adapt to these new environments. Only few studies have examined the effects of ocean acidification (OA) and warming (OW) on the metabolism of long-lived fish over successive generations. We therefore aimed to investigate the effect of OA on larval and juvenile growth and metabolism on two successive generations of European sea bass (Dicentrarchus labrax L.) as well as the effect of OAW on larval and juvenile growth and metabolism of the second generation. European sea bass is a large economically important fish species with a long generation time. F0 larvae were produced at the aquaculture facility Aquastream (Ploemeur-Lorient, France) and obtained at 2 days post-hatch (dph). From 2 dph F0 larvae were reared in the laboratory in two PCO2 conditions (ambient and Δ1000). Larval rearing was performed in a temperature controlled room and water temperatures were fixed to 19°C in F0. In juveniles and adults, water temperatures of F0 sea bass were adjusted to ambient temperature in the Bay of Brest during summer (up to 19°C), but were kept constant at 15 and 12°C for juveniles and adults, respectively, when ambient temperature decreased below these values. F1 embryos were obtained by artificial reproduction of F0 broodstock fish. Fertilized eggs were incubated at 15°C and at the same PCO2 conditions as respective F0. Division of F1 larvae from egg rearing tanks into experimental tanks took place at 2 dph. F1 larvae were reared in four OAW conditions: two temperatures (cold and warm life condition, C and W) and two PCO2 conditions (ambient and Δ1000). Larval rearing was performed in a temperature controlled room and water temperatures were fixed to 15 and 20°C for C and W larvae, respectively. In juveniles, water temperatures of F1 sea bass were adjusted to ambient temperature in the Bay of Brest during summer (up to 19°C), but were kept constant at 15°C when ambient temperature decreased below these values. F1-W was always 5°C warmer than the F1-C treatment. OAW conditions for F0 and F1 rearing were chosen to follow the predictions of the IPCC for the next 130 years: ΔT = 5°C and ΔPCO2 = 1000 µatm, following RCP 8.5. We analysed larval and juvenile growth in F0 and F1. Larval routine metabolic rates (RMR, in F1), juvenile standard metabolic rates (SMR, in F0 and F1) and juvenile critical oxygen concentrations (PO2crit, in F0 and F1) were obtained on individuals via intermittent flow-respirometry. Measurements were conducted at the rearing conditions of the respective larva or juvenile. Fish were fasted for 3h and 48-72h for larvae and juveniles, respectively. After the respirometry trial, larvae were photographed to measure there body length and frozen until measurement of dry mass. Juveniles body length and wet mass was directly determined with calipers and a balance.
    Keywords: Age; Calculated; Caliper; DATE/TIME; Dicentrarchus labrax, body length; Dicentrarchus labrax, dry mass; Dicentrarchus labrax, fork length; Dicentrarchus labrax, mass; Dicentrarchus labrax, routine metabolic rate, per dry mass; Dicentrarchus labrax, standard metabolic rate per fresh mass; Fish, wet weighted; Fulton's condition factor; Generation; Identification; juvenile growth; Laboratory experiment; larval growth; Life stage; metabolic rates; Ocean acidification; ocean warming; Optical oxygen meter with sensor OXR50 (FireSting, PyroScience GmbH, Germany); Optical oxygen meter with sensor OXROB10 (FireSting, PyroScience GmbH, Germany); Oxygen, dissolved; Sample ID; Species; Stereomicroscopy (Leica); Tank number; teleost; Treatment: partial pressure of carbon dioxide; Treatment: temperature; Type of study; Uniform resource locator/link to reference; Weighted
    Type: Dataset
    Format: text/tab-separated-values, 3746 data points
    Location Call Number Expected Availability
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  • 99
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120327, WRMC No. 20103; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 561046 data points
    Location Call Number Expected Availability
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  • 100
    Publication Date: 2024-05-24
    Description: Fatty acid composition data for the two dominant copepods in the mesocosms (Paracalanus sp. and Hemicyclops sp.).
    Keywords: Abundance; Biomass; Climate - Biogeochemistry Interactions in the Tropical Ocean; Coastal Upwelling System in a Changing Ocean; CUSCO; DATE/TIME; Day of experiment; Fatty acid of total lipids; Fatty alcohol of total lipids; Gut fluorescence; Humboldt Current System; KOSMOS_2017; KOSMOS_2017_Peru; KOSMOS Peru; Lipid; Lipids, total, per dry mass; MESO; mesocosm experiment; Mesocosm experiment; Mesocosm label; Oxygen Minimun zone; Phase; Polyunsaturated fatty acids of total lipids; Saturated fatty acids of total lipids; SFB754; Species; Stable isotopes; Treatment; Zooplankton
    Type: Dataset
    Format: text/tab-separated-values, 1431 data points
    Location Call Number Expected Availability
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