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  • 2015-2019  (6,925)
  • 1980-1984
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  • 1925-1929  (3)
  • 2015  (6,925)
  • 1926  (3)
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  • 2015-2019  (6,925)
  • 1980-1984
  • 1965-1969
  • 1960-1964
  • 1925-1929  (3)
Year
  • 101
    Publication Date: 2023-03-16
    Keywords: Carlini_Base_C2; Carlini/Jubany Station; DATE/TIME; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; Jubany; Jubany_Station_C2; Potter Cove, King George Island, Antarctic Peninsula; Research station; RS; Uniform resource locator/link to image; Uniform resource locator/link to thumbnail; Webcam
    Type: Dataset
    Format: text/tab-separated-values, 1392 data points
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  • 102
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2005; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 354 data points
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  • 103
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2009; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 516 data points
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  • 104
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2010; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 541 data points
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  • 105
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2013; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 551 data points
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  • 106
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2011; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 561 data points
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  • 107
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2012; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 480 data points
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  • 108
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Area/locality; Comment; CT; DATE/TIME; Investigator; North Sea; Underway cruise track measurements; UT2014; Uthörn
    Type: Dataset
    Format: text/tab-separated-values, 543 data points
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  • 109
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Brandal; Conductivity/temperature logger µS-Log540, Driesen + Kern GmbH; DATE/TIME; DEPTH, water; Kongsfjorden, Spitsbergen, Arctic; MULT; Multiple investigations; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 52266 data points
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  • 110
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: AWI_Coast; AWI Arctic Land Expedition; Carbon, organic, dissolved; Coastal Ecology @ AWI; Colorometric autoanalysis; DATE/TIME; Depth, bathymetric; DEPTH, water; High temperature catalytic oxidation; LATITUDE; Lena2010; Lena Delta, Siberia, Russia; Location type; LONGITUDE; MULT; Multiple investigations; Nitrate and Nitrite; Nitrogen, total dissolved; Phosphate; RU-Land_2010_Lena; Salinity; Sample code/label; Sample ID; Spectrophotometry; Station label; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 606 data points
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  • 111
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: ARK-XXIX/2.2; Calculated; Course; CT; DATE/TIME; LATITUDE; LONGITUDE; Polarstern; PS93.2; PS93.2-track; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 7102 data points
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  • 112
    Publication Date: 2023-03-16
    Keywords: AWI_Paleo; CT; DATE/TIME; LATITUDE; LONGITUDE; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; SO213/2; SO213/2-track; Sonne; SOPATRA; South Pacific Ocean; Underway cruise track measurements; Uniform resource locator/link to raw data file
    Type: Dataset
    Format: text/tab-separated-values, 282 data points
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  • 113
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: ARK-XXIX/2.2; AWI_Meteo; CT; DATE/TIME; File name; Laser ceilometer, Vaisala, CL51; LATITUDE; LONGITUDE; Meteorological Long-Term Observations @ AWI; Polarstern; PS93.2; PS93.2-track; Underway cruise track measurements; Uniform resource locator/link to raw data file
    Type: Dataset
    Format: text/tab-separated-values, 36 data points
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  • 114
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Arctic Ocean; ARK-XXVIII/3 AURORA; AWI_PhyOce; Calculated; Conductivity; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Elevation of event; Event label; Expendable CTD; Latitude of event; Longitude of event; North Greenland Sea; Optional event label; Physical Oceanography @ AWI; Polarstern; Pressure, water; PS86; PS86/001-1; PS86/002-1; PS86/003-1; PS86/004-1; PS86/005-1; PS86/007-1; PS86/008-1; PS86/009-1; PS86/010-1; PS86/011-1; PS86/012-1; PS86/013-1; PS86/015-1; PS86/016-1; PS86/017-1; PS86/XCTD1; PS86/XCTD10; PS86/XCTD11; PS86/XCTD12; PS86/XCTD13; PS86/XCTD14; PS86/XCTD15; PS86/XCTD2; PS86/XCTD3; PS86/XCTD4; PS86/XCTD5; PS86/XCTD6; PS86/XCTD7; PS86/XCTD8; PS86/XCTD9; Salinity; Temperature, water; Temperature, water, potential; XCTD; XCTD, TSK_MK-150N/LM3A, Type: XCTD-1
    Type: Dataset
    Format: text/tab-separated-values, 86130 data points
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  • 115
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    PANGAEA
    In:  Supplement to: Falk, Ulrike; Gieseke, Hilke; Kotzur, Franziska; Braun, Matthias Holger (2015): Monitoring snow and ice surfaces on King George Island, Antarctic Peninsula, with high-resolution TerraSAR-X time series. Antarctic Science, 15 pp, https://doi.org/10.1017/S0954102015000577
    Publication Date: 2023-03-16
    Description: Changes of glaciers and snow cover in polar regions affect a wide range of physical and ecosystem processes on land and in the adjacent marine environment. In this study, we investigate the potential of 11-day repeat high-resolution satellite image time series from the TerraSAR-X mission to derive glaciological and hydrological parameters on King George Island, Antarctica during the period Oct/25/2010 to Apr/19/2011. The spatial pattern and temporal evolution of snow cover extent on ice-free areas can be monitored using multi-temporal coherence images. SAR coherence is used to map glacier extent of land terminating glaciers with an average accuracy of 25 m. Multi-temporal SAR color composites identify the position of the late summer snow line at about 220 m above sea level. Glacier surface velocities are obtained from intensity feature-tracking. Surface velocities near the calving front of Fourcade Glacier were up to 1.8 ± 0.01 m/d. Using an intercept theorem based on fundamental geometric principles together with differential GPS field measurements, the ice discharge of Fourcade Glacier was estimated to 20700 ± 5500 m**3/d (corresponding to ~19 ± 5 kt/d). The rapidly changing surface conditions on King George Island and the lack of high-resolution digital elevation models for the region remain restrictions for the applicability of SAR data and the precision of derived products.
    Keywords: File content; File format; File size; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King_George_Island; King George Island, Antarctic Peninsula; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 16 data points
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  • 116
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: Calculated; Course; CT; DATE/TIME; HE280/1; HE280/1-track; Heincke; LATITUDE; LONGITUDE; North Sea; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 380 data points
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  • 117
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    PANGAEA
    In:  Supplement to: Falk, Ulrike; López, Damián; Sala, Hernán (in prep.): Tipping point of glacier mass balance changes for the inland ice cap of King George Island, West Antarctica.
    Publication Date: 2023-03-16
    Description: The east coast of the AP is highly influenced by cold and dry air masses stemming from the adjacent Weddell Sea. By the contrary, the west coast jointly with the South Shetland Islands are directly exposed to the humid and relatively warm air masses from the South Pacific Ocean carried by the strong and persistent westerly winds. Systematic glaciological field studies are very scarce on both sides of the AP, among them can be mentioned a mass-balance program performed continuously since summer 1998/99 by the Instituto Antártico Argentino (IAA) on Vega Island, James Ross Archipelago, on the northeastern flank of the AP. Another continuous plurianual glaciological research has been initiated in 2010 jointly by the University of Bonn and the IAA at the Fourcade Glacier on King George Island (KGI) within the framework of the ESF project IMCOAST (FK 03F0617B). Two transects of mass balance stakes were installed from the top of the Warszawa Ice Dome down to the border of the glaciers Fourcade and Polar Club, to serve for calibration and validation of modeling efforts. The stakes were measured at the beginning and end of each summer field campaign in November 2010, February - March 2011, January - March 2012, and especially during the austral winter 2012 up to March 2013 every 10 to 14 days depending on weather conditions. During the austral winter 2013 and until June 2014 the measurements were conducted every 20 to 30 days, weather permitting. Snow density was measured as well in every field trip from June 2012 until June 2104, establishing a rather homogeneous value along the different parts of the glacier. Snow density in late summer, rho_s is usually higher than the one in late winter, rho_w. Seasonal average values were calculated for the area covered by the mass balance stakes, being rho_s= 471 Kg/m**3 and rho_w = 363 Kg/m**3.
    Keywords: Automatic weather station; AWS; Calculated; DATE/TIME; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Length, difference; Melt rate in water equivalent per day; Warszawa_Icefield_AWS
    Type: Dataset
    Format: text/tab-separated-values, 186 data points
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  • 118
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: ARK-VI/2; Calculated; Course; CT; DATE/TIME; LATITUDE; LONGITUDE; Polarstern; PS15; PS15/2-track; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 6446 data points
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  • 119
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: ARK-VII/2; Calculated; Course; CT; DATE/TIME; LATITUDE; LONGITUDE; Polarstern; PS17; PS17/2-track; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 10492 data points
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  • 120
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: ARK-VIII/2; Calculated; Course; CT; DATE/TIME; LATITUDE; LONGITUDE; Polarstern; PS19/2-track; PS19 EPOS II; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 12094 data points
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  • 121
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: ARK-IX/3; Calculated; Course; CT; DATE/TIME; LATITUDE; LONGITUDE; Polarstern; PS26/3-track; PS26 NEW; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 12092 data points
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  • 122
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Type: Dataset
    Format: application/zip, 8.6 MBytes
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  • 123
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven | Supplement to: Driemel, Amelie; Loose, Bernd; Grobe, Hannes; Sieger, Rainer; König-Langlo, Gert (2016): 30 years of upper air soundings on board of R/V POLARSTERN. Earth System Science Data, 8, 213-220, https://doi.org/10.5194/essd-8-213-2016
    Publication Date: 2023-03-16
    Description: The research vessel and supply icebreaker POLARSTERN is the flagship of the Alfred-Wegener-Institut in Bremerhaven (Germany) and one of the infrastructural pillars of German Antarctic research. Since its commissioning in 1982, POLARSTERN has conducted 30 campaigns to Antarctica (157 legs, mostly austral summer), and 29 to the Arctic (94 legs, northern summer). Usually, POLARSTERN is more than 300 days per year in operation and crosses the Atlantic Ocean in a meridional section twice a year. The first radiosonde on POLARSTERN was released on the 29th of December 1982, two days after POLARSTERN started on its maiden voyage to the Antarctic. And these daily soundings have continued up to the present. Due to the fact that POLARSTERN has reliably and regularly been providing upper air observations from data sparse regions (oceans and polar regions), the radiosonde data are of special value for researchers and weather forecast services alike. In the course of 30 years (1982-12-29 to 2012-11-25) a total of 12378 radiosonde balloons were started on POLARSTERN. All radiosonde data can now be found here. Each dataset contains the directly measured parameters air temperature, relative humidity and air pressure, and the derived altitude, wind direction and wind speed. 432 datasets additionally contain ozone measurements.
    Keywords: AWI_Meteo; Campaign; Date/time end; Date/time start; Meteorological Long-Term Observations @ AWI; Method comment; Number of observations; Persistent Identifier; Uniform resource locator/link to reference
    Type: Dataset
    Format: text/tab-separated-values, 1453 data points
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  • 124
    Publication Date: 2023-03-16
    Keywords: Alpine wind monitor, R.M. Young, model 05108-45; Automatic weather station; AWS; Barometric pressure sensor, R.M. Young, model 61302V; DATE/TIME; HEIGHT above ground; Humidity, relative; Humidity, relative, standard deviation; Humidity-Temperature probe, Vaisala, HMP155A; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Pressure, atmospheric; Pressure, atmospheric, standard deviation; Temperature, air; Temperature, air, standard deviation; Warszawa_Icefield_AWS; Wind direction; Wind direction, standard deviation; Wind speed; Wind speed, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 109360 data points
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  • 125
    Publication Date: 2023-03-16
    Keywords: Automatic weather station; AWS; DATE/TIME; DEPTH, ice/snow; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Temperature, ice/snow; Temperature, ice/snow, standard deviation; Thermistor soil temperature probe 107, Campbell Scientific; Warszawa_Icefield_AWS
    Type: Dataset
    Format: text/tab-separated-values, 51064 data points
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  • 126
    Publication Date: 2023-03-16
    Keywords: Automatic weather station; AWS; Battery terminal voltage; Calculated; DATE/TIME; DEPTH, ice/snow; Depth, relative; HEIGHT above ground; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; King George Island, Antarctic Peninsula; Temperature, ice/snow; Thermistor soil temperature probe 107, Campbell Scientific; Warszawa_Icefield_ZAWS
    Type: Dataset
    Format: text/tab-separated-values, 8874 data points
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  • 127
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    In:  Supplement to: Jung, Richard (submitted): Sediment classification on Norderney. Remote Sensing of Environment
    Publication Date: 2023-03-08
    Description: The Wadden Sea is located in the southeastern part of the North Sea forming an extended intertidal area along the Dutch, German and Danish coast. It is a highly dynamic and largely natural ecosystem influenced by climatic changes and anthropogenic use of the North Sea. Changes in the environment of the Wadden Sea, natural or anthropogenic origin, cannot be monitored by the standard measurement methods alone, because large-area surveys of the intertidal flats are often difficult due to tides, tidal channels and unstable underground. For this reason, remote sensing offers effective monitoring tools. In this study a multi-sensor concept for classification of intertidal areas in the Wadden Sea has been developed. Basis for this method is a combined analysis of RapidEye (RE) and TerraSAR-X (TSX) satellite data coupled with ancillary vector data about the distribution of vegetation, mussel beds and sediments. The classification of the vegetation and mussel beds is based on a decision tree and a set of hierarchically structured algorithms which use object and texture features. The sediments are classified by an algorithm which uses thresholds and a majority filter. Further improvements focus on radiometric enhancement and atmospheric correction. First results show that we are able to identify vegetation and mussel beds with the use of multi-sensor remote sensing. The classification of the sediments in the tidal flats is a challenge compared to vegetation and mussel beds. The results demonstrate that the sediments cannot be classified with high accuracy by their spectral properties alone due to their similarity which is predominately caused by their water content.
    Keywords: WIMO; Wissenschaftliche Monitoringkonzepte für die Deutsche Bucht
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 128
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    PANGAEA
    In:  Supplement to: Overduin, Pier Paul; Liebner, Susanne; Knoblauch, Christian; Günther, Frank; Wetterich, Sebastian; Schirrmeister, Lutz; Hubberten, Hans-Wolfgang; Grigoriev, Mikhail N (2015): Methane oxidation following submarine permafrost degradation: Measurements from a central Laptev Sea shelf borehole. Journal of Geophysical Research: Biogeosciences, 120(5), 965-978, https://doi.org/10.1002/2014JG002862
    Publication Date: 2023-03-07
    Description: Submarine permafrost degradation has been invoked as a cause for recent observations of methane emissions from the seabed to the water column and atmosphere of the East Siberian shelf. Sediment drilled 52 m down from the sea ice in Buor Khaya Bay, central Laptev Sea revealed unfrozen sediment overlying ice-bonded permafrost. Methane concentrations in the overlying unfrozen sediment were low (mean 20 µM) but higher in the underlying ice-bonded submarine permafrost (mean 380 µM). In contrast, sulfate concentrations were substantially higher in the unfrozen sediment (mean 2.5 mM) than in the underlying submarine permafrost (mean 0.1 mM). Using deduced permafrost degradation rates, we calculate potential mean methane efflux from degrading permafrost of 120 mg/m**2 per year at this site. However, a drop of methane concentrations from 190 µM to 19 µM and a concomitant increase of methane d13C from -63 per mil to -35 per mil directly above the ice-bonded permafrost suggest that methane is effectively oxidized within the overlying unfrozen sediment before it reaches the water column. High rates of methane ebullition into the water column observed elsewhere are thus unlikely to have ice-bonded permafrost as their source.
    Keywords: AWI_PerDyn; Permafrost Research (Periglacial Dynamics) @ AWI
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 129
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    PANGAEA
    In:  Supplement to: Fritz, Michael; Herzschuh, Ulrike; Wetterich, Sebastian; Lantuit, Hugues; De Pascale, Gregory P; Pollard, Wayne H; Schirrmeister, Lutz (2012): Late glacial and Holocene sedimentation, vegetation, and climate history from easternmost Beringia (northern Yukon Territory, Canada). Quaternary Research, 78(3), 549-560, https://doi.org/10.1016/j.yqres.2012.07.007
    Publication Date: 2023-03-07
    Description: Beringian climate and environmental history are poorly characterized at its easternmost edge. Lake sediments from the northern Yukon Territory have recorded sedimentation, vegetation, summer temperature and precipitation changes since ~16 cal ka BP. Herb-dominated tundra persisted until ~14.7 cal ka BP with mean July air temperatures less than or equal to 5 °C colder and annual precipitation 50 to 120 mm lower than today. Temperatures rapidly increased during the Bølling/Allerød interstadial towards modern conditions, favoring establishment of Betula-Salix shrub tundra. Pollen-inferred temperature reconstructions recorded a pronounced Younger Dryas stadial in east Beringia with a temperature drop of ~1.5 °C (~2.5 to 3.0 °C below modern conditions) and low net precipitation (90 to 170 mm) but show little evidence of an early Holocene thermal maximum in the pollen record. Sustained low net precipitation and increased evaporation during early Holocene warming suggest a moisture-limited spread of vegetation and an obscured summer temperature maximum. Northern Yukon Holocene moisture availability increased in response to a retreating Laurentide Ice Sheet, postglacial sea level rise, and decreasing summer insolation that in turn led to establishment of Alnus-Betula shrub tundra from ~5 cal ka BP until present, and conversion of a continental climate into a coastal-maritime climate near the Beaufort Sea.
    Keywords: AWI_PerDyn; Permafrost Research (Periglacial Dynamics) @ AWI
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 130
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    In:  Supplement to: Boike, Julia; Grau, Thomas; Heim, Birgit; Günther, Frank; Langer, Moritz; Muster, Sina; Gouttevin, Isabelle; Lange, Stephan (2016): Satellite-derived changes in the permafrost landscape of central Yakutia, 2000–2011: Wetting, drying, and fires. Global and Planetary Change, 139, 116-127, https://doi.org/10.1016/j.gloplacha.2016.01.001
    Publication Date: 2023-03-07
    Description: The focus of this research has been on detecting changes in lake areas, vegetation, land surface temperatures, and the area covered by snow, using data from remote sensing. The study area covers the main (central) part of the Lena River catchment in the Yakutia region of Siberia (Russia), extending from east of Yakutsk to the central Siberian Plateau, and from the southern Lena River to north of the Vilyui River. Approximately 90% of the area is underlain by continuous permafrost. Remote sensing products were used to analyze changes in water bodies, land surface temperature (LST), and leaf area index (LAI), as well as the occurrence and extent of forest fires, and the area and duration of snow cover. The remote sensing analyses (for LST, snow cover, LAI, and fire) were based on MODIS-derived NASA products (250-1000 m) for 2000 to 2011. Changes in water bodies were calculated from two mosaics of (USGS) Landsat (30 m) satellite images from 2002 and 2009. Within the study area's 315,000 km**2 the total area covered by lakes increased by 17.9% between 2002 and 2009, but this increase varied in different parts of the study area, ranging between 11% and 42%. The land surface temperatures showed a consistent warming trend, with an average increase of about 0.12 °C/year. The average rate of warming during the April-May transition period was 0.17 °C/year and 0.19 °C/year in the September-October period, but ranged up to 0.49 °C/year during September-October. Regional differences in the rates of land surface temperature change, and possible reasons for the temperature changes, are discussed with respect to changes in the land cover. Our analysis of a broad spectrum of variables over the study area suggests that the spring warming trend is very likely to be due to changes in the area covered by snow. The warming trend observed in fall does not, however, appear to be directly related to any changes in the area of snow cover, or to the atmospheric conditions, or to the proportion of the land surface that is covered by water (i.e., to wetting and drying).
    Keywords: AWI_PerDyn; Permafrost Research (Periglacial Dynamics) @ AWI
    Type: Dataset
    Format: application/zip, 9 datasets
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  • 131
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    PANGAEA
    In:  Supplement to: Niemeyer, Bastian; Klemm, Juliane; Pestryakova, Luidmila A; Herzschuh, Ulrike (2015): Relative pollen productivity estimates for common taxa of the northern Siberian Arctic. Review of Palaeobotany and Palynology, 221, 71-82, https://doi.org/10.1016/j.revpalbo.2015.06.008
    Publication Date: 2023-03-07
    Description: Pollen productivity estimates (PPE) are used to quantitatively reconstruct variations in vegetation within a specific distance of the sampled pollen archive. Here, for the first time, PPEs from Siberia are presented. The study area (Khatanga region, Krasnoyarsk territory, Russia) is located in the Siberian Sub-arctic where Larixis the sole forest-line forming tree taxon. Pollen spectra from two different sedimentary environments, namely terrestrial mosses (n=16) and lakes (n=15, median radius ~100 m) and their surrounding vegetation were investigated to extract PPEs. Our results indicate some differences in pollen spectra between moss and lake pollen. Larix and Cyperaceae for example obtained higher representation in the lacustrine than in terrestrial moss samples. This highlights that in calibration studies modern and fossil dataset should be of similar sedimentary origin. The results of the Extended R-Value model were applied to assess the relevant source area of pollen (RSAP) and to calculate the PPEs for both datasets. As expected, the RSAP of the moss samples was very small (about 10 m) compared to the lacustrine samples (about 25 km). Calculation of PPEs for the six most common taxa yielded generally similar results for both datasets. Relative to Poaceae (reference taxon, PPE=1) Betula nana-type (PPEmoss: 1.8, PPElake: 1.8) and Alnusfruticosa-type (PPEmoss: 6.4, PPElake: 2.9) were overrepresented while Cyperaceae (PPEmoss: 0.5, PPElake: 0.1), Ericaceae (PPEmoss: 0.3, PPElake 〈0.01), Salix (PPEmoss: 0.03, PPElake 〈0.01) and Larix (PPEmoss 〈0.01, PPElake: 0.2) were under-represented in the pollen spectra compared to the vegetation in the RSAP. The estimation for the dominant tree in the region, Larixgmelinii, is the first published result for this species, but need to be considered very preliminary. The inferred sequence from over- to under-representation is mostly consistent with results from Europe; however, still the absolute values show some differences. Gathering vegetation data was limited by flowering season and low resolute satellite imagery and accessibility of the remote location of our study area. Therefore, our estimate may serve as first reference to strengthen future vegetation reconstructions in this climate-sensitive region.
    Keywords: AWI_PerDyn; Permafrost Research (Periglacial Dynamics) @ AWI
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 132
    Publication Date: 2023-03-07
    Description: This vector data layer covers 6 major lake districts (Baldwin Peninsula, Kobuk Delta, Selawik Lowland, Northern Seward Peninsula, Central Seward Peninsula, and Yukon-Kuskokwim Delta) in the northern and central sub-regions of the Western Alaska Landscape Conservation Cooperative (WALCC) region and consists of polygons of lakes with areas equal or greater than 1.0 ha. More than 58000 Lakes were mapped from Landsat TM and ETM+ imagery acquired between 1972 and 1975, 2002 and 2009, and 2013 and 2014 using Object-Based Image Analysis (OBIA) techniques with an classification accuracy of 96%. The spatial image resolution of Landsat TM and ETM+ is 30 m. Permafrost characteristics and surficial geology associated with lake polygons were determined from the Alaska permafrost map (Jorgenson et al. 2008).
    Keywords: Alaska, USA; AWI_PerDyn; LSAT; Permafrost Research (Periglacial Dynamics) @ AWI; Remote sensing (Landsat); Western-Alaska-LCC
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 133
    Publication Date: 2023-03-07
    Keywords: 11-CH-17A; Age; Age, 14C AMS; Age, 14C calibrated; Age, dated; Age, dated material; Age, dated standard deviation; Age, standard deviation; AWI_PerDyn; AWI Arctic Land Expedition; Calculated; Chatanga2011; DEPTH, sediment/rock; GCUWI; Gravity corer, UWITEC; Permafrost Research (Periglacial Dynamics) @ AWI; RU-Land_2011_Khatanga; Sample, optional label/labor no; Taymyr peninsula, northern Siberia
    Type: Dataset
    Format: text/tab-separated-values, 36 data points
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  • 134
    Publication Date: 2023-03-07
    Keywords: Alaska, USA; AWI_PerDyn; LSAT; Permafrost Research (Periglacial Dynamics) @ AWI; Remote sensing (Landsat); Western-Alaska-LCC
    Type: Dataset
    Format: application/zip, 18.2 MBytes
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  • 135
    Publication Date: 2023-03-07
    Keywords: 11-CH-moss10I; 11-CH-moss16I; 11-CH-moss17I; 11-CH-moss17II; 11-CH-moss2I; 11-CH-moss2II; 11-CH-moss6I; 11-CH-moss6II; 11-CH-moss6III; 11-CH-moss6IV; 13-TY-moss4K1; 13-TY-moss4K2; 13-TY-moss7K1; 13-TY-moss7K2; 13-TY-moss9K1; 13-TY-moss9K2; AWI_PerDyn; AWI Arctic Land Expedition; Calculated; Chatanga2011; Counting, palynology; Event label; Khatanga region, Russia; LAKE; LAND; Latitude of event; Longitude of event; Permafrost Research (Periglacial Dynamics) @ AWI; Pollen productivity estimate; Ring sector, in; Ring sector, out; RU-Land_2011_Khatanga; Sample ID; Sampling/measurement on land; Sampling lake
    Type: Dataset
    Format: text/tab-separated-values, 2410 data points
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  • 136
    Publication Date: 2023-03-07
    Keywords: Alaska, USA; AWI_PerDyn; LSAT; Permafrost Research (Periglacial Dynamics) @ AWI; Remote sensing (Landsat); Western-Alaska-LCC
    Type: Dataset
    Format: application/zip, 10.2 MBytes
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  • 137
    Publication Date: 2023-03-07
    Keywords: Alaska, USA; AWI_PerDyn; LSAT; Permafrost Research (Periglacial Dynamics) @ AWI; Remote sensing (Landsat); Western-Alaska-LCC
    Type: Dataset
    Format: application/zip, 10.2 MBytes
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  • 138
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; Permafrost Research (Periglacial Dynamics) @ AWI; Sakha Republic, Russia
    Type: Dataset
    Format: application/zip, 480.6 kBytes
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  • 139
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; Permafrost Research (Periglacial Dynamics) @ AWI; Sakha Republic, Russia
    Type: Dataset
    Format: application/zip, 23.9 MBytes
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  • 140
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; Permafrost Research (Periglacial Dynamics) @ AWI; Sakha Republic, Russia
    Type: Dataset
    Format: application/zip, 2 MBytes
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  • 141
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; Permafrost Research (Periglacial Dynamics) @ AWI; Sakha Republic, Russia
    Type: Dataset
    Format: application/zip, 1.7 MBytes
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  • 142
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; File content; File size; Latitude, northbound; Latitude, southbound; Longitude, eastbound; Longitude, westbound; Permafrost Research (Periglacial Dynamics) @ AWI; Projection; Sakha Republic, Russia; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 16 data points
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  • 143
    Publication Date: 2023-03-07
    Keywords: AWI_PerDyn; Central_Yakutia; Permafrost Research (Periglacial Dynamics) @ AWI; Sakha Republic, Russia
    Type: Dataset
    Format: application/zip, 336.6 kBytes
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  • 144
    Publication Date: 2023-03-07
    Description: The dataset was obtained on samples taken from 6 stations in the Dardanelles Straits, Marmara Sea and Bosporus Straits. These experiments were set up according to DoW of SESAME project. Ciliate abundance: Borax-buffered formalin (final concentration 2% formaldehyde). Samples for ciliate counting were stored at 4°C in the dark until observation. For ciliate identification and enumeration, 100 ml samples were left for 24 h in sedimentation cylinders and then observed under an inverted epifluorescence microscope. Ciliate biomass: Ciliate cell sizes were measured and converted into cell volumes using appropriate geometric formulae (Peuto-Moreau 1991). For biomass estimation, the conversion factor 140 fgC µm**3 was used (Putt and Stoecker (1989), doi:10.4319/lo.1989.34.6.1097)).
    Keywords: Bilim_TurkishStraits__L095L029_NIS_200804_53; Bilim_TurkishStraits_2008-04; Bilim_TurkishStraits_K03I45_NIS_200804_49; Bilim_TurkishStraits_K35J18_NIS_200804_52; Bilim_TurkishStraits_K465L00_NIS_200804_51; Bilim_TurkishStraits_K51K03_NIS_200804_50; Bilim_TurkishStraits_NIS_200804_54; Bilim 2; Bottle, Niskin; Ciliates; Ciliates, biomass as carbon; Computed/Converted; Date/Time of event; DEPTH, water; Eastern Mediterranean Sea; Event label; K03I45; K35J18; K465L00; K51K03; L095L029; L18L105; Latitude of event; Longitude of event; Measured/Determined; NIS; Optional event label; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes
    Type: Dataset
    Format: text/tab-separated-values, 52 data points
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  • 145
    Publication Date: 2023-03-07
    Description: The SES_GR2-Mesozooplankton faecal pellet production rates dataset is based on samples taken during August and September 2008 in the Northern Libyan Sea, Southern Aegean Sea and the North-Eastern Aegean Sea. Mesozooplankton is collected by vertical tows within the 0–100 m layer or within the Black sea water body mass layer in the case of the NE Aegean, using a WP-2 200 µm net equipped with a large non-filtering cod-end (10 l). Macrozooplankton organisms are removed using a 2000 µm net. A few unsorted animals (approximately 100) are placed inside several glass beaker of 250 ml filled with GF/F or 0.2 µm Nucleopore filtered seawater and with a 100 µm net placed 1 cm above the beaker bottom. Beakers are then placed in an incubator at natural light and maintaining the in situ temperature. After 1 hour pellets are separated from animals and placed in separated flasks and preserved with formalin. Pellets are counted and measured using an inverted microscope. Animals are scanned and counted using an image analysis system. Carbon- Specific faecal pellet production is calculated from a) faecal pellet production, b) individual carbon: Animals are scanned and their body area is measured using an image analysis system. Body volume is then calculated as an ellipsoid using the major and minor axis of an ellipse of same area as the body. Individual carbon is calculated from a carbon- total body volume of organisms (relationship obtained for the Mediterranean Sea by Alcaraz et al. (2003) divided by the total number of individuals scanned and c) faecal pellet carbon: Faecal pellet length and width is measured using an inverted microscope. Faecal pellet volume is calculated from length and width assuming cylindrical shape. Conversion of faecal pellet volume to carbon is done using values obtained in the Mediterranean from: a) faecal pellet density 1,29 g cm**3 (or pg µm**3) from Komar et al. (1981); b) faecal pellet DW/WW=0,23 from Elder and Fowler (1977) and c) faecal pellet C%DW=25,5 Marty et al. (1994).
    Keywords: 00A1b; 0A10c; 0I05d; 0L02c; Aegaeo; Computed/Converted; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Eastern Mediterranean Sea; Event label; Fecal pellet production as carbon; Fecal pellet production rate per individual; Latitude of event; Longitude of event; Measured/Determined; Mediterranean Sea; Optional event label; SES_GR2; SES_GR2-00A1b_WP2; SES_GR2-0A10c_WP2; SES_GR2-0I05d_WP2; SES_GR2-0L02c_WP2; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; WP2; WP-2 towed closing plankton net
    Type: Dataset
    Format: text/tab-separated-values, 16 data points
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  • 146
    Publication Date: 2023-03-07
    Description: The SES_GR1-Mesozooplankton faecal pellet production rates dataset is based on samples taken during April 2008 in the North-Eastern Aegean Sea. Mesozooplankton is collected by vertical tows within the Black sea water body mass layer in the NE Aegean, using a WP-2 200 µm net equipped with a large non-filtering cod-end (10 l). Macrozooplankton organisms are removed using a 2000 µm net. A few unsorted animals (approximately 100) are placed inside several glass beaker of 250 ml filled with GF/F or 0.2 µm Nucleopore filtered seawater and with a 100 µm net placed 1 cm above the beaker bottom. Beakers are then placed in an incubator at natural light and maintaining the in situ temperature. After 1 hour pellets are separated from animals and placed in separated flasks and preserved with formalin. Pellets are counted and measured using an inverted microscope. Animals are scanned and counted using an image analysis system. Carbon- Specific faecal pellet production is calculated from a) faecal pellet production, b) individual carbon: Animals are scanned and their body area is measured using an image analysis system. Body volume is then calculated as an ellipsoid using the major and minor axis of an ellipse of same area as the body. Individual carbon is calculated from a carbon- total body volume of organisms (relationship obtained for the Mediterranean Sea by Alcaraz et al. (2003) divided by the total number of individuals scanned and c) faecal pellet carbon: Faecal pellet length and width is measured using an inverted microscope. Faecal pellet volume is calculated from length and width assuming cylindrical shape. Conversion of faecal pellet volume to carbon is done using values obtained in the Mediterranean from: a) faecal pellet density 1,29 g cm**3 (or pg µm**3) from Komar et al. (1981); b) faecal pellet DW/WW=0,23 from Elder and Fowler (1977) and c) faecal pellet C%DW=25,5 Marty et al. (1994).
    Keywords: 00NA3b; 00NA4; 00NA6; 00NA7; 00NA8b; Aegaeo; Computed/Converted; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Fecal pellet production as carbon; Fecal pellet production rate per individual; Latitude of event; Longitude of event; Measured/Determined; Mediterranean Sea; Optional event label; SES_GR1; SES_GR1-00NA3b_WP2; SES_GR1-00NA4_WP2; SES_GR1-00NA6_WP2; SES_GR1-00NA7_WP2; SES_GR1-00NA8b_WP2; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; WP2; WP-2 towed closing plankton net
    Type: Dataset
    Format: text/tab-separated-values, 20 data points
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  • 147
    Publication Date: 2023-03-07
    Description: The SES_UNLUATA_GR1-Mesozooplankton faecal pellet production rates dataset is based on samples taken during March and April 2008 in the Northern Libyan Sea, Southern Aegean Sea and in the North-Eastern Aegean Sea. Mesozooplankton is collected by vertical tows within the 0-100 m layer or within the Black sea water body mass layer in the case of the NE Aegean, using a WP-2 200 µm net equipped with a large non-filtering cod-end (10 l). Macrozooplankton organisms are removed using a 2000 µm net. A few unsorted animals (approximately 100) are placed inside several glass beaker of 250 ml filled with GF/F or 0.2 µm Nucleopore filtered seawater and with a 100 µm net placed 1 cm above the beaker bottom. Beakers are then placed in an incubator at natural light and maintaining the in situ temperature. After 1 hour pellets are separated from animals and placed in separated flasks and preserved with formalin. Pellets and are counted and measured using an inverted microscope. Animals are scanned and counted using an image analysis system. Carbon- Specific faecal pellet production is calculated from a) faecal pellet production, b) individual carbon: Animals are scanned and their body area is measured using an image analysis system. Body volume is then calculated as an ellipsoid using the major and minor axis of an ellipse of same area as the body. Individual carbon is calculated from a carbon- total body volume of organisms (relationship obtained for the Mediterranean Sea by Alcaraz et al. (2003) divided by the total number of individuals scanned and c) faecal pellet carbon: Faecal pellet length and width is measured using an inverted microscope. Faecal pellet volume is calculated from length and width assuming cylindrical shape. Conversion of faecal pellet volume to carbon is done using values obtained in the Mediterranean from: a) faecal pellet density 1,29 g cm**3 (or pg µm**3) from Komar et al. (1981); b) faecal pellet DW/WW=0,23 from Elder and Fowler (1977) and c) faecal pellet C%DW=25,5 Marty et al. (1994).
    Keywords: 000L2a; 0A01c; 0A10c; Aegaeo; Computed/Converted; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Fecal pellet production as carbon; Fecal pellet production rate per individual; Latitude of event; Longitude of event; Measured/Determined; Mediterranean Sea; Optional event label; SES_GR1; SES_GR1-000L2a_WP2; SES_GR1-0A01c_WP4; SES_GR1-0A10c_WP3; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; WP2; WP-2 towed closing plankton net
    Type: Dataset
    Format: text/tab-separated-values, 12 data points
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  • 148
    Publication Date: 2023-03-07
    Description: Mesozooplankton is collected by vertical tows within the Black sea water body mass layer in the NE Aegean, using a WP-2 200 µm net equipped with a large non-filtering cod-end (10 l). Macrozooplankton organisms are removed using a 2000 µm net. A few unsorted animals (approximately 100) are placed inside several glass beaker of 250 ml filled with GF/F or 0.2 µm Nucleopore filtered seawater and with a 100 µm net placed 1 cm above the beaker bottom. Beakers are then placed in an incubator at natural light and maintaining the in situ temperature. After 1 hour pellets are separated from animals and placed in separated flasks and preserved with formalin. Pellets are counted and measured using an inverted microscope. Animals are scanned and counted using an image analysis system. Carbon- Specific faecal pellet production is calculated from a) faecal pellet production, b) individual carbon: Animals are scanned and their body area is measured using an image analysis system. Body volume is then calculated as an ellipsoid using the major and minor axis of an ellipse of same area as the body. Individual carbon is calculated from a carbon- total body volume of organisms (relationship obtained for the Mediterranean Sea by Alcaraz et al. (2003) divided by the total number of individuals scanned and c) faecal pellet carbon: Faecal pellet length and width is measured using an inverted microscope. Faecal pellet volume is calculated from length and width assuming cylindrical shape. Conversion of faecal pellet volume to carbon is done using values obtained in the Mediterranean from: a) faecal pellet density 1,29 g cm**3 (or pg µm**3) from Komar et al. (1981); b) faecal pellet DW/WW=0,23 from Elder and Fowler (1977) and c) faecal pellet C%DW=25,5 Marty et al. (1994).
    Keywords: 0NA1b; 0NA7c; Aegaeo; Computed/Converted; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Eastern Mediterranean Sea; Event label; Fecal pellet production as carbon; Fecal pellet production rate per individual; Latitude of event; Longitude of event; Measured/Determined; Optional event label; SES_GR2; SES_GR2-0NA1b_WP2; SES_GR2-0NA7c_WP2; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; WP2; WP-2 towed closing plankton net
    Type: Dataset
    Format: text/tab-separated-values, 8 data points
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  • 149
    Publication Date: 2023-03-07
    Description: The NA64-Mesozooplankton dataset contains biogeochemistry and mesozooplankton data collected in a series of 9 cruises in the Northern Adriatic completed from January 1965 to September 1965 monthly, and December 1965. Biogeochemistry sampling was undertaken using 5L Nansen bottles fired at 0m, 5m, 10m, 20m, 30m and/or bottom depths. The dataset includes 709 samples analysed for nitrate, phosphate, temperature, salinity and density. Mesozooplankton sampling was undertaken at the same locations as for biogeochemistry, using two different net (Hensen non-closing and Appstein closing net). The dataset includes 146 samples analysed for mesozooplankton composition (at higher taxonomic level), abundance and volume settlement. Temperature was measured with a standard oceanographic thermometers. Salinity was determined by titration after Mohr-Knudsen using standardised water I.C.E.S. Copenhagen with 0,01 permil accuracy. Density was calculated using the following equation Sigma-t = T - (sigma 0 + 0,1324) 1 - At + Bt (sigma 0 - 0,1324). Phosphate samples for the determination of nutrients were collected in 500 ml and filtrated through 0,3 µm membrane filter. 3ml of cloroform was added to stabilize the samples. They were analysed after few days in the laboratory on land. Nitrate samples for the determination of nutrients were collected in 500 ml and filtrated through 0,3 µm membrane filter. 3ml of cloroform was added to stabilize the samples. They were analysed after few days in the laboratory on land.
    Keywords: 1; 10; 11; 12; 13; 14; 15; 16; 17; 18; 2; 3; 4; 5; 6; 7; 8; 9; Adriatic Sea; Bottle, Nansen; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Event label; Latitude of event; Longitude of event; NA64; NA64_19650126-02; NA64_19650126-03; NA64_19650126-04; NA64_19650126-05; NA64_19650126-08; NA64_19650126-12; NA64_19650127-10; NA64_19650127-13; NA64_19650127-14; NA64_19650127-15; NA64_19650127-17; NA64_19650128-01; NA64_19650128-18; NA64_19650225-2; NA64_19650225-3; NA64_19650225-4; NA64_19650225-5; NA64_19650225-6; NA64_19650225-7; NA64_19650225-8; NA64_19650225-9; NA64_19650226-10; NA64_19650226-11; NA64_19650226-12; NA64_19650227-17; NA64_19650227-18; NA64_19650228-1; NA64_19650324-15; NA64_19650324-16; NA64_19650324-17; NA64_19650324-18; NA64_19650327-10; NA64_19650327-11; NA64_19650327-12; NA64_19650327-13; NA64_19650327-14; NA64_19650327-8; NA64_19650327-9; NA64_19650328-2; NA64_19650328-3; NA64_19650328-4; NA64_19650328-5; NA64_19650328-6; NA64_19650328-7; NA64_19650507-2; NA64_19650507-3; NA64_19650507-4; NA64_19650507-5; NA64_19650507-6; NA64_19650507-7; NA64_19650507-8; NA64_19650507-9; NA64_19650508-10; NA64_19650508-11; NA64_19650508-12; NA64_19650508-13; NA64_19650508-14; NA64_19650508-15; NA64_19650508-16; NA64_19650509-1; NA64_19650509-17; NA64_19650509-18; NA64_19650526-10; NA64_19650526-2; NA64_19650526-3; NA64_19650526-4; NA64_19650526-5; NA64_19650526-6; NA64_19650526-7; NA64_19650526-8; NA64_19650526-9; NA64_19650527-11; NA64_19650527-12; NA64_19650527-13; NA64_19650527-14; NA64_19650527-15; NA64_19650527-16; NA64_19650528-1; NA64_19650528-17; NA64_19650528-18; NA64_19650628-2; NA64_19650628-3; NA64_19650628-4; NA64_19650628-5; NA64_19650628-6; NA64_19650628-7; NA64_19650628-8; NA64_19650628-9; NA64_19650630-10; NA64_19650630-11; NA64_19650630-12; NA64_19650630-13; NA64_19650630-14; NA64_19650630-15; NA64_19650705-16; NA64_19650705-17; NA64_19650706-1; NA64_19650706-18; NA64_19650805-2; NA64_19650805-3; NA64_19650805-4; NA64_19650805-5; NA64_19650805-6; NA64_19650805-7; NA64_19650805-8; NA64_19650805-9; NA64_19650806-10; NA64_19650806-11; NA64_19650806-12; NA64_19650806-13; NA64_19650806-14; NA64_19650806-15; NA64_19650807-16; NA64_19650808-1; NA64_19650808-17; NA64_19650808-18; NA64_19650915-2; NA64_19650915-3; NA64_19650915-4; NA64_19650915-5; NA64_19650915-6; NA64_19650915-7; NA64_19650915-8; NA64_19650915-9; NA64_19650916-10; NA64_19650916-11; NA64_19650916-12; NA64_19650916-13; NA64_19650916-14; NA64_19650916-15; NA64_19650918-16; NA64_19650918-17; NA64_19650919-1; NA64_19651214-16; NA64_19651214-17; NA64_19651214-18; NA64_19651226-10; NA64_19651226-11; NA64_19651226-12; NA64_19651226-13; NA64_19651226-14; NA64_19651226-15; NA64_19651226-9; NA64_19651227-3; NA64_19651227-4; NA64_19651227-5; NA64_19651227-6; NA64_19651227-7; NA64_19651227-8; NAS; Nitrate; Phosphate; Salinity; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 2705 data points
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  • 150
    Publication Date: 2023-03-07
    Description: hyDRaCAT Spectral Reflectance Library for tundra provides the surface reflectance data and the bidirectional reflectance distribution function (BRDF) of important Arctic tundra vegetation communities at representative Siberian and Alaskan tundra sites. The aim of this dataset is the hyperspectral and spectro-directional reflectance characterization as basis for the extraction of vegetation parameters, and the normalization of BRDF effects in off-nadir and multi-temporal remote sensing data. The spectroscopic and field spectro-goniometric measurements were undertaken on the YAMAL2011 expedition of representative Siberian vegetation fields and on the North American Arctic Transect NAAT2012 expedition of Alaskan vegetation fields both belonging to the Greening-of-the-Arctic (GOA) program. For the field spectroscopy each 100 m2 vegetation study grid was divided into quadrats of 1 × 1 m. The averaged reflectance of all quadrats represents the spectral reflectance at the scale of the whole grid at the 10 × 10 m scale. For the surface radiometric measurements two GER1500 portable field spectroradiometers (Spectra Vista Corporation, Poughkeepsie, NY, USA) were used. The GER1500 measures radiance across the wavelength range of 350-1,050 nm, with sampling intervals of 1.5 nm and a radiance accuracy of 1.2 × 10**-1 W/cm**2/nm/sr. In order to increase the signal-to-noise ratio, 32 individual measurements were averaged per one target scan. To minimize variations in the target reflectance due to sun zenith angle changes, all measurements at one study location have been performed under similar sun zenith angles and during clear-sky conditions. The field spectrometer measurements were carried out with a GER1500 UV-VIS spectrometer The spectrogoniometer measurements were carried out with a self-designed spectro-goniometer: the Manual Transportable Instrument platform for ground-based Spectro-directional observations (ManTIS, patent publication number: DE 10 2011 117 713.A1). The ManTIS was equipped with the GER1500 spectrometer allowing spectro-directional measurements with up to 30° viewing zenith angle by full 360° viewing azimuth angles. Measurements in central Yamal (Siberia) at the research site 'Vaskiny Dachi' were carried out in the late summer phenological state from August 12 2011 to August 28 2011. All measurements in Alaska along the North South transect on the North Slope were taken between 29 June and 11 July 2012, ensuring that the vegetation was in the same phenological state near peak growing season.
    Keywords: AWI_PerDyn; AWI Arctic Land Expedition; Comment of event; Date/Time of event; Elevation of event; Event label; FBG1; FBG2; FBG3; FBG4; File name; File size; Franklin Bluffs, Arctic North Slope, Alaska, United States of America; Happy Valley, Arctic North Slope, Alaska, United States of America; HVG1; HVG2; Latitude of event; Location of event; Longitude of event; Permafrost Research (Periglacial Dynamics) @ AWI; Persistent Identifier; Remote Sensing of POlar Non-glaciated and Sensitive Environments; RESPONSE; Vaskiny Dachi, Yamal Peninsula, West Siberia, Russian Federation; VDG1; VDG2
    Type: Dataset
    Format: text/tab-separated-values, 35 data points
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  • 151
    Publication Date: 2023-03-10
    Keywords: Bubble catcher; Bubble flux; BUC; Carbon dioxide, flux; DATE/TIME; DEPTH, water; ECO2; ECO2-9; ECO2-9-162; ECO2-9-167; Event label; LATITUDE; LONGITUDE; Panarea; Sample code/label; Sub-seabed CO2 Storage: Impact on Marine Ecosystems
    Type: Dataset
    Format: text/tab-separated-values, 18 data points
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  • 152
    Publication Date: 2023-03-07
    Keywords: Alaska, USA; AWI_PerDyn; CSAT; Permafrost Research (Periglacial Dynamics) @ AWI; Remote sensing (Corona); Seward_Peninsula
    Type: Dataset
    Format: application/zip, 569.9 MBytes
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  • 153
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    In:  Alfred Wegener Institute - Research Unit Potsdam
    Publication Date: 2023-03-07
    Keywords: 11-CH-12A; AWI_PerDyn; AWI Arctic Land Expedition; awilinescan2015; Chatanga2011; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; File size; GCUWI; Gravity corer, UWITEC; Line Scan Camera; Permafrost Research (Periglacial Dynamics) @ AWI; RU-Land_2011_Khatanga; Taymyr peninsula, northern Siberia; Uniform resource locator/link to image
    Type: Dataset
    Format: text/tab-separated-values, 10 data points
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  • 154
    Publication Date: 2023-03-04
    Keywords: Mode of life; North America, U.S.A.; Parameter; Western_North_America; Zone
    Type: Dataset
    Format: text/tab-separated-values, 13776 data points
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  • 155
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    In:  Supplement to: Harsch, Melanie A; HilleRisLambers, Janneke: Climate warming and seasonal precipitation change interact to limit species distribution shifts across western North America. PLoS ONE, https://doi.org/10.1371/journal.pone.0159184
    Publication Date: 2023-03-04
    Description: Using an extensive network of occurrence records for 293 plant species collected over the past 40 years across a climatically diverse geographic section of western North America, we find that plant species distributions were just as likely to shift upwards (i.e., towards higher elevations) as downward (i.e., towards lower elevations) – despite consistent warming across the study area. Although there was no clear directional response to climate warming across the entire study area, there was significant region-to region- variation in responses (i.e. from as many as 73% to as few as32% of species shifting upward or downward). To understand the factors that might be controlling region-specific distributional shifts, we explored the relationship between the direction of change in distribution limits and the nature of recent climate change. We found that the direction of distribution limit shifts was explained by an interaction between the rate of change in local summer temperatures and seasonal precipitation. Specifically, species shifted upward at their upper elevational limit when snowfall declined at slower rates and minimum temperatures increased. By contrast, species shifted upwards at their lower elevation limit when maximum temperatures increased or both temperature and precipitation decreased. Our results suggest that future species' elevational distribution shifts will be complex, depending on the interaction between seasonal temperature and precipitation change.
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 156
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    In:  Supplement to: Voigt, Ines; Chiessi, Cristiano Mazur; Prange, Matthias; Mulitza, Stefan; Groeneveld, Jeroen; Varma, Vidya; Henrich, Rüdiger (2015): Holocene shifts of the southern westerlies across the South Atlantic. Paleoceanography, 30(2), 39-51, https://doi.org/10.1002/2014PA002677
    Publication Date: 2023-03-03
    Description: The Southern Westerly Winds (SWW) exert a crucial influence over the world ocean and climate. Nevertheless, a comprehensive understanding of the Holocene temporal and spatial evolution of the SWW remains a significant challenge due to the sparsity of high-resolution marine archives and appropriate SWW proxies. Here, we present a north-south transect of high-resolution planktonic foraminiferal oxygen isotope records from the western South Atlantic. Our proxy records reveal Holocene migrations of the Brazil- Malvinas Confluence (BMC), a highly sensitive feature for changes in the position and strength of the northern portion of the SWW. Through the tight coupling of the BMC position to the large-scale wind field, the records allow a quantitative reconstruction of Holocene latitudinal displacements of the SWW across the South Atlantic. Our data reveal a gradual poleward movement of the SWW by about 1-1.5° from the early to the mid-Holocene. Afterwards variability in the SWW is dominated by millennial-scale displacements in the order of 1° in latitude with no recognizable longer-term trend. These findings are confronted with results from a state-of-the-art transient Holocene climate simulation using a comprehensive coupled atmosphere-ocean general circulation model. Proxy-inferred and modeled SWW shifts compare qualitatively, but the model underestimates both orbitally forced multi-millennial and internal millennial SWW variability by almost an order of magnitude. The underestimated natural variability implies a substantial uncertainty in model projections of future SWW shifts.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 157
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    In:  Supplement to: Razik, Sebastian; Govin, Aline; Chiessi, Cristiano Mazur; von Dobeneck, Tilo (2015): Depositional provinces, dispersal, and origin of terrigenous sediments along the SE South American continental margin. Marine Geology, 363, 261-272, https://doi.org/10.1016/j.margeo.2015.03.001
    Publication Date: 2023-03-03
    Description: Continental margin sediments of SE South America originate from various terrestrial sources, each conveying specific magnetic and element signatures. Here, we aim to identify the sources and transport characteristics of shelf and slope sediments deposited between East Brazil and Patagonia (20°-48°S) using enviromagnetic, major element, and grain-size data. A set of five source-indicative parameters (i.e., chi-fd%, ARM/IRM, S0.3T, SIRM/Fe and Fe/K) of 25 surface samples (16-1805 m water depth) was analyzed by fuzzy c-means clustering and non-linear mapping to depict and unmix sediment-province characteristics. This multivariate approach yields three regionally coherent sediment provinces with petrologically and climatically distinct source regions. The southernmost province is entirely restricted to the slope off the Argentinean Pampas and has been identified as relict Andean-sourced sands with coarse unaltered magnetite. The direct transport to the slope was enabled by Rio Colorado and Rio Negro meltwaters during glacial and deglacial phases of low sea level. The adjacent shelf province consists of coastal loessoidal sands (highest hematite and goethite proportions) delivered from the Argentinean Pampas by wave erosion and westerly winds. The northernmost province includes the Plata mudbelt and Rio Grande Cone. It contains tropically weathered clayey silts from the La Plata Drainage Basin with pronounced proportions of fine magnetite, which were distributed up to ~24° S by the Brazilian Coastal Current and admixed to coarser relict sediments of Pampean loessoidal origin. Grain-size analyses of all samples showed that sediment fractionation during transport and deposition had little impact on magnetic and element source characteristics. This study corroborates the high potential of the chosen approach to access sediment origin in regions with contrasting sediment sources, complex transport dynamics, and large grain-size variability.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 5 datasets
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  • 158
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    PANGAEA
    In:  Supplement to: Steinle, Lea; Graves, Carolyn; Treude, Tina; Ferre, Benedicte; Biastoch, Arne; Bussmann, Ingeborg; Berndt, Christian; Krastel, Sebastian; James, Rachael H; Behrens, Erik; Böning, Claus W; Greinert, Jens; Sapart, Célia-Julia; Scheinert, Markus; Sommer, Stefan; Lehmann, Moritz F; Niemann, Helge (2015): Water column methanotrophy controlled by a rapid oceanographic switch. Nature Geoscience, 8(5), 378–382, https://doi.org/10.1038/ngeo2420
    Publication Date: 2023-03-03
    Description: Large amounts of the greenhouse gas methane are released from the seabed to the water column where it may be consumed by aerobic methanotrophic bacteria. This microbial filter is consequently the last marine sink for methane before its liberation to the atmosphere. The size and activity of methanotrophic communities, which determine the capacity of the water column methane filter, are thought to be mainly controlled by nutrient and redox dynamics, but little is known about the effects of ocean currents. Here, we report measurements of methanotrophic activity and biomass (CARD-FISH) at methane seeps west of Svalbard, and related them to physical water mass properties (CTD) and modelled current dynamics. We show that cold bottom water containing a large number of aerobic methanotrophs was rapidly displaced by warmer water with a considerably smaller methanotrophic community. This water mass exchange, caused by short-term variations of the West Spitsbergen Current, constitutes a rapid oceanographic switch severely reducing methanotrophic activity in the water column. Strong and fluctuating currents are widespread oceanographic features common at many methane seep systems and are thus likely to globally affect methane oxidation in the ocean water column.
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 159
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    In:  Supplement to: Wei, Jiangong; Pape, Thomas; Sultan, Nabil; Colliat, Jean-Louis; Himmler, Tobias; Ruffine, Livio; de Prunelé, Alexis; Dennielou, Bernard; Garziglia, Sebastien; Marsset, Tania; Peters, Carl A; Rabiu, Abdulkarim; Bohrmann, Gerhard (2015): Gas hydrate distributions in sediments of pockmarks from the Nigerian margin – Results and interpretation from shallow drilling. Marine and Petroleum Geology, 59, 359-370, https://doi.org/10.1016/j.marpetgeo.2014.09.013
    Publication Date: 2023-03-03
    Description: A joint research expedition between the French IFREMER and the German MARUM was conducted in 2011 using the R/V 'Pourquoi pas?' to study gas hydrate distributions in a pockmark field (1141-1199 m below sea surface) at the continental margin of Nigeria. The seafloor drill rig MeBo of MARUM was used to recover sediments as deep as 56.74 m below seafloor. The presence of gas hydrates in specific core sections was deduced from temperature anomalies recorded during continuous records of infrared thermal scanning and anomalies in pore water chloride concentrations. In situ sediment temperature measurements showed elevated geothermal gradients of up to 258 °C/km in the center of the so-called pockmark A which is up to 4.6 times higher than that in the background sediment (72 °C/km). The gas hydrate distribution and thermal regime in the pockmark are largely controlled by the intensity, periodicity and direction of fluid flow. The joint interaction between fluid flow, gas hydrate formation and dissolution, and the thermal regime governs pockmark formation and evolution on the Nigerian continental margin.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 13 datasets
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  • 160
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    PANGAEA
    In:  Supplement to: Kuhlmann, Jannis; Asioli, Alessandra; Trincardi, Fabio; Klügel, Andreas; Huhn, Katrin (2015): Sedimentary response to Milankovitch-type climatic oscillations and formation of sediment undulations: evidence from a shallow-shelf setting at Gela Basin on the Sicilian continental margin. Quaternary Science Reviews, 108, 76-94, https://doi.org/10.1016/j.quascirev.2014.10.030
    Publication Date: 2023-03-03
    Description: A multi-proxy chronological framework along with sequence-stratigraphic interpretations unveils composite Milankovitch cyclicity in the sedimentary records of the Last GlacialeInterglacial cycle at NE Gela Basin on the Sicilian continental margin. Chronostratigraphic data (including foraminifera-based eco-biostratigraphy and d18O records, tephrochronological markers and 14C AMS radiometric datings) was derived from the shallow-shelf drill sites GeoB14403 (54.6 m recovery) and GeoB14414 (27.5 m), collected with both gravity and drilled MeBo cores in 193 m and 146 m water depth, respectively. The recovered intervals record Marine Isotope Stages and Substages (MIS) from MIS 5 to MIS 1, thus comprising major stratigraphic parts of the progradational deposits that form the last 100-ka depositional sequence. Calibration of shelf sedimentary units with borehole stratigraphies indicates the impact of higher-frequency (20-ka) sea level cycles punctuating this 100-ka cycle. This becomes most evident in the alternation of thick interstadial highstand (HST) wedges and thinner glacial forced-regression (FSST) units mirroring seaward shifts in coastal progradation. Albeit their relatively short-lived depositional phase, these subordinate HST units form the bulk of the 100-ka depositional sequence. Two mechanisms are proposed that likely account for enhanced sediment accumulation ratios (SAR) of up to 200 cm/ka during these intervals: (1) intensified activity of deep and intermediate Levantine Intermediate Water (LIW) associated to the drowning of Mediterranean shelves, and (2) amplified sediment flux along the flooded shelf in response to hyperpycnal plumes that generate through extreme precipitation events during overall arid conditions. Equally, the latter mechanism is thought to be at the origin of undulated features resolved in the acoustic records of MIS 5 Interstadials, which bear a striking resemblance to modern equivalents forming on late-Holocene prodeltas of other Mediterranean shallow-shelf settings.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 161
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    PANGAEA
    In:  Supplement to: Kwiatkowski, Cornelia; Prange, Matthias; Varma, Vidya; Steinke, Stephan; Hebbeln, Dierk; Mohtadi, Mahyar (2015): Holocene variations of thermocline conditions in the eastern tropical Indian Ocean. Quaternary Science Reviews, 114, 33-42, https://doi.org/10.1016/j.quascirev.2015.01.028
    Publication Date: 2023-03-03
    Description: Climate phenomena like the monsoon system, El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) are interconnected via various feedback mechanisms and control the climate of the Indian Ocean and its surrounding continents on various timescales. The eastern tropical Indian Ocean is a key area for the interplay of these phenomena and for reconstructing their past changes and forcing mechanisms. Here we present records of upper ocean thermal gradient, thermocline temperatures (TT) and relative abundances of planktic foraminifera in core SO 189-39KL taken off western Sumatra (0°47.400' S, 99°54.510' E) for the last 8 ka that we use as proxies for changes in upper ocean structure. The records suggest a deeper thermocline between 8 ka and ca 3 ka compared to the late Holocene. We find a shoaling of the thermocline after 3 ka, most likely indicating an increased occurrence of upwelling during the late Holocene compared to the mid-Holocene which might represent changes in the IOD-like mean state of the Indian Ocean with a more negative IOD-like mean state during the mid-Holocene and a more positive IOD-like mean state during the past 3 ka. This interpretation is supported by a transient Holocene climate model simulation in which an IOD-like mode is identified that involves an insolation-forced long-term trend of increasing anomalous surface easterlies over the equatorial eastern Indian Ocean.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 162
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    In:  Supplement to: Thiele, Stefan; Fuchs, Bernhard M; Amann, Rudolf; Iversen, Morten Hvitfeldt; Wommack, K Eric (2015): Colonization in the Photic Zone and Subsequent Changes during Sinking Determine Bacterial Community Composition in Marine Snow. Applied and Environmental Microbiology, 81(4), 1463-1471, https://doi.org/10.1128/AEM.02570-14
    Publication Date: 2023-03-03
    Description: Due to sampling difficulties, little is known about microbial communities associated with sinking marine snow in the twilight zone. A drifting sediment trap was equipped with a viscous cryogel and deployed to collect intact marine snow from depths of 100 and 400 m off Cape Blanc (Mauritania). Marine snow aggregates were fixed and washed in situ to prevent changes in microbial community composition and to enable subsequent analysis using catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH). The attached microbial communities collected at 100 m were similar to the free-living community at the depth of the fluorescence maximum (20 m) but different from those at other depths (150, 400, 550, and 700 m). Therefore, the attached microbial community seemed to be "inherited" from that at the fluorescence maximum. The attached microbial community structure at 400 m differed from that of the attached community at 100 m and from that of any free-living community at the tested depths, except that collected near the sediment at 700 m. The differences between the particle-associated communities at 400 m and 100 m appeared to be due to internal changes in the attached microbial community rather than de novo colonization, detachment, or grazing during the sinking of marine snow. The new sampling method presented here will facilitate future investigations into the mechanisms that shape the bacterial community within sinking marine snow, leading to better understanding of the mechanisms which regulate biogeochemical cycling of settling organic matter.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 163
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    In:  Supplement to: Klicpera, André; Michel, Julien; Westphal, Hildegard (2015): Facies patterns of a tropical heterozoan carbonate platform under eutrophic conditions: the Banc d'Arguin, Mauritania. Facies, 61(1), https://doi.org/10.1007/s10347-014-0421-5
    Publication Date: 2023-03-03
    Description: High-nutrient tropical carbonate systems are known to produce sediments that, in terms of skeletal composition, are reminiscent of their extra-tropical counterparts. Such carbonate systems and associated carbonate grain assemblages in the tropics are rare in the present-day world. Nonetheless, it is crucial to gain a better understanding of those ecosystems, including their drivers and players because such settings potentially represent models for ancient depositional systems as well as for predicted future environmental conditions. One of the modern occurrences of eutrophic tropical carbonate systems is the northern Mauritanian Shelf. The marine environment is characterized by an eastern boundary upwelling system that pushes cool and nutrient-rich intermediate waters onto a wide epicontinental platform (Golfe d'Arguin) where the waters warm up to tropical temperatures. The resulting facies is mixed carbonate-siliciclastic with a dominant foramol association grading into bimol and barnamol grain assemblages in the shallowest areas forming the Banc d'Arguin. Besides this cool water-related heterozoan association, the carbonate sediment is characterized by tropical molluskan species, while chlorozoan biota (e.g., corals and algal symbiont-bearing foraminifers) are entirely absent. We here present a first comprehensive facies analysis of this model example of eutrophic tropical carbonates. Furthermore, we reconstruct the loci of carbonate production and provide a conclusive depositional model of the Banc d'Arguin that received little attention to date due to its poorly accessible nature.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 164
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    In:  Supplement to: Stegmann, Sylvia; Kopf, Achim J (2014): How stable is the Nice slope? An analysis based on strength and cohesion from ring shear experiments. In: Krastel S et al. (eds.) Submarine Mass Movements and Their Consequences. Springer, Heidelberg, 189-200, https://doi.org/10.1007/978-3-319-00972-8_17
    Publication Date: 2023-03-03
    Description: The upper shelf of the landslide-prone Ligurian Margin (Western Mediterranean Sea) off Nice well-known for the 1979 Airport Landslide is a natural laboratory to study preconditioning factors and trigger mechanisms for submarine landslides. For this study low-stress ring shear experiments have been carried out on a variety of sediments from 〉50 gravity cores to characterise the velocity-dependent frictional behaviour. Mean values of the peak coefficient of friction vary from 0.46 for clay-dominated samples (53 % clay, 46 % silt, 1 %) sand up to 0.76 for coarse-grained sediments (26 % clay, 57 % silt, 17 % sand). The majority of the sediments tested show velocity strengthening regardless of the grain size distribution. For clayey sediments the peak and residual cohesive strength increases with increasing normal stress, with values from 1.3 to 10.6 kPa and up to 25 % of all strength supported by cohesive forces in the shallowmost samples. A pseudo-static slope stability analysis reveals that the different lithologies (even clay-rich material with clay content 〉=50 %) tested are stable up to slope angles 〈26° under quasi-drained conditions.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 165
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    In:  Supplement to: Schmidt, Christiane; Morard, Raphael; Almogi-Labin, Ahuva; Weinmann, A E; Titelboim, Danna; Abramovich, Sigal; Kucera, Michal (2015): Recent Invasion of the Symbiont-Bearing Foraminifera Pararotalia into the Eastern Mediterranean Facilitated by the Ongoing Warming Trend. PLoS ONE, 10(8), e0132917, https://doi.org/10.1371/journal.pone.0132917
    Publication Date: 2023-03-03
    Description: The eastern Mediterranean is a hotspot of biological invasions. Numerous species of Indo-pacific origin have colonized the Mediterranean in recent times, including tropical symbiont-bearing foraminifera. Among these is the species Pararotalia calcariformata. Unlike other invasive foraminifera, this species has been discovered only two decades ago and is restricted to the eastern Mediterranean coast. Combining ecological, genetic and physiological observations, we attempt to explain the recent invasion of this species in the Mediterranean Sea. Using morphological and genetic data, we confirm the species attribution to P. calcariformata McCulloch 1977 and identify its symbionts as a consortium of diatom species dominated by Minutocellus polymorphus. We document photosynthetic activity of its endosymbionts using Pulse Amplitude Modulated Fluorometry and test the effects of elevated temperatures on growth rates of asexual offspring. The culturing of asexual offspring for 120 days shows a 30-day period of rapid growth followed by a period of slower growth. A subsequent 48-day temperature sensitivity experiment indicates a similar developmental pathway and high growth rate at 28°C, whereas an almost complete inhibition of growth was observed at 20°C and 35°C. This indicates that the offspring of this species may have lower tolerance to cold temperatures than what would be expected for species native to the Mediterranean. We expand this hypothesis by applying a Species Distribution Model (SDM) based on modern occurrences in the Mediterranean using three environmental variables: irradiance, turbidity and yearly minimum temperature. The model reproduces the observed restricted distribution and indicates that the range of the species will drastically expand westwards under future global change scenarios. We conclude that P. calcariformata established a population in the Levant because of the recent warming in the region. In line with observations from other groups of organisms, our results indicate that continued warming of the eastern Mediterranean will facilitate the invasion of more tropical marine taxa into the Mediterranean, disturbing local biodiversity and ecosystem structure.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 166
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    In:  Supplement to: Bernhardt, Anne; Melnick, Daniel; Hebbeln, Dierk; Lückge, Andreas; Strecker, Manfred R (2015): Turbidite paleoseismology along the active continental margin of Chile – Feasible or not? Quaternary Science Reviews, 120, 71-92, https://doi.org/10.1016/j.quascirev.2015.04.001
    Publication Date: 2023-03-03
    Description: Much progress has been made in estimating recurrence intervals of great and giant subduction earthquakes using terrestrial, lacustrine, and marine paleoseismic archives. Recent detailed records suggest these earthquakes may have variable recurrence periods and magnitudes forming supercycles. Understanding seismic supercycles requires long paleoseismic archives that record timing and magnitude of such events. Turbidite paleoseismic archives may potentially extend past earthquake records to the Pleistocene and can thus complement commonly shorter-term terrestrial archives. However, in order to unambiguously establish recurring seismicity as a trigger mechanism for turbidity currents, synchronous deposition of turbidites in widely spaced, isolated depocenters has to be ascertained. Furthermore, characteristics that predispose a seismically active continental margin to turbidite paleoseismology and the correct sample site selection have to be taken into account. Here we analyze 8 marine sediment cores along 950 km of the Chile margin to test for the feasibility of compiling detailed and continuous paleoseismic records based on turbidites. Our results suggest that the deposition of areally widespread, synchronous turbidites triggered by seismicity is largely controlled by sediment supply and, hence, the climatic and geomorphic conditions of the adjacent subaerial setting. The feasibility of compiling a turbidite paleoseismic record depends on the delicate balance between sufficient sediment supply providing material to fail frequently during seismic shaking and sufficiently low sedimentation rates to allow for coeval accumulation of planktonic foraminifera for high-resolution radiocarbon dating. We conclude that offshore northern central Chile (29-32.5°S) Holocene turbidite paleoseismology is not feasible, because sediment supply from the semi-arid mainland is low and almost no Holocene turbidity-current deposits are found in the cores. In contrast, in the humid region between 36 and 38°S frequent Holocene turbidite deposition may generally correspond to paleoseismic events. However, high terrigenous sedimentation rates prevent high-resolution radiocarbon dating. The climatic transition region between 32.5 and 36°S appears to be best suited for turbidite paleoseismology.
    Keywords: BGR; Bundesanstalt für Geowissenschaften und Rohstoffe, Hannover; Center for Marine Environmental Sciences; MARUM
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    Format: application/zip, 2 datasets
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  • 167
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    In:  Supplement to: Fischer, Cornelius; Finkeldei, Sarah; Brandt, Felix; Bosbach, Dirk; Lüttge, Andreas (2015): Direct Measurement of Surface Dissolution Rates in Potential Nuclear Waste Forms: The Example of Pyrochlore. ACS Applied Materials & Interfaces, 7(32), 17857-17865, https://doi.org/10.1021/acsami.5b04281
    Publication Date: 2023-03-03
    Description: The long-term stability of ceramic materials that are considered as potential nuclear waste forms is governed by heterogeneous surface reactivity. Thus, instead of a mean rate, the identification of one or more dominant contributors to the overall dissolution rate is the key to predict the stability of waste forms quantitatively. Direct surface measurements by vertical scanning interferometry (VSI) and their analysis via material flux maps and resulting dissolution rate spectra provide data about dominant rate contributors and their variability over time. Using pyrochlore (Nd2Zr2O7) pellet dissolution under acidic conditions as an example, we demonstrate the identification and quantification of dissolution rate contributors, based on VSI data and rate spectrum analysis. Heterogeneous surface alteration of pyrochlore varies by a factor of about 5 and additional material loss by chemo-mechanical grain pull-out within the uppermost grain layer. We identified four different rate contributors that are responsible for the observed dissolution rate range of single grains. Our new concept offers the opportunity to increase our mechanistic understanding and to predict quantitatively the alteration of ceramic waste forms.
    Keywords: Center for Marine Environmental Sciences; Height; MARUM; Time in hours; Vertical scanning interferometry (VSI)
    Type: Dataset
    Format: text/tab-separated-values, 24 data points
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  • 168
    Publication Date: 2023-03-03
    Keywords: 101_CK1; 102_CK2; 103_CK3; 104_CK4; 105_CK5; 106_CK6; 107_CK7; 111_OS1; 115_DD10; 118_DD9; 119_DD8; 120_DD7; 124_DD6; 126_DD3; 127_DD2; 128_DD1; 129_DP4; 130_DP4a; 132_DD4; 135_ED4; 136_DN7; 138_Phy3; 139_Phy4; 140_Phy4a; 141_Phy2; 142_Phy1; 143_DN12; 146_DN11; 149_Phy10; 150_DN16; 152_Phy6; 153_DN14; 158_DN6; 159_Phy7; 160_Phy8; 161_Phy9; 163_ED5; 164_ED6; 165_ED7; 166_ED8; 167_DD12; 168_DP1; 169_DP2; 177_DP5; 179_OS5; 181_OS1a; 182_OS2a; 183_OS7; 184_CO1; 188_BG1; 189_BG2; 191_VA2; 192_VA3; 193_CK1a; 194_CK1b; 195_CK2a; 196_CK2b; 197_CK3a; 200_CK5a; 203_CK8a; 205_CK10; Ammonium; Black Sea; Carbon, organic, dissolved; Carbon, organic, particulate; CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Elevation of event; Event label; Latitude of event; Longitude of event; Nitrate; Nitrate and Nitrite; Nitrite; Nitrogen, organic, dissolved; Nitrogen, particulate; Nitrogen, total dissolved; Optional event label; Phosphate; Phosphorus, organic, dissolved; Phosphorus, particulate; Phosphorus, total dissolved; POS363; POS363_101-1; POS363_102-1; POS363_103-1; POS363_104-1; POS363_105-1; POS363_106-1; POS363_107-1; POS363_111-1; POS363_115-1; POS363_118-1; POS363_119-1; POS363_120-2; POS363_124-1; POS363_126-1; POS363_127-1; POS363_128-2; POS363_129-1; POS363_130-1; POS363_132-1; POS363_135-1; POS363_136-1; POS363_138-1; POS363_139-1; POS363_140-1; POS363_141-1; POS363_142-1; POS363_143-1; POS363_146-1; POS363_149-1; POS363_150-1; POS363_152-1; POS363_153-5; POS363_158-1; POS363_159-2; POS363_160-1; POS363_161-1; POS363_163-1; POS363_164-1; POS363_165-1; POS363_166-1; POS363_167-1; POS363_168-1; POS363_169-1; POS363_177-1; POS363_179-1; POS363_181-1; POS363_182-1; POS363_183-1; POS363_184-1; POS363_188-1; POS363_189-1; POS363_191-1; POS363_192-1; POS363_193-1; POS363_194-1; POS363_195-1; POS363_196-1; POS363_197-1; POS363_200-1; POS363_203-1; POS363_205-1; Poseidon; Silicate
    Type: Dataset
    Format: text/tab-separated-values, 2368 data points
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  • 169
    Publication Date: 2023-02-24
    Keywords: Base pair size; BIOACID; BIOACID 2 PNG2013; Biological Impacts of Ocean Acidification; DIVER; M.V. Chertan; Papua_New_Guinea_CO2_vent; Peak area; Sample code/label; Sampling by diver
    Type: Dataset
    Format: text/tab-separated-values, 466568 data points
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  • 170
    Publication Date: 2023-02-24
    Keywords: Accession number, genetics; BIOACID; Biological Impacts of Ocean Acidification; Name; Sample code/label
    Type: Dataset
    Format: text/tab-separated-values, 104 data points
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  • 171
    Publication Date: 2023-03-13
    Keywords: AGE; Density, wet bulk; DRILL; Drilling/drill rig; FH2; Foulden Maar, Otago, New Zealand
    Type: Dataset
    Format: text/tab-separated-values, 7925 data points
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  • 172
    Publication Date: 2023-03-13
    Keywords: AGE; Color, L*, lightness; DRILL; Drilling/drill rig; FH2; Foulden Maar, Otago, New Zealand
    Type: Dataset
    Format: text/tab-separated-values, 5566 data points
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  • 173
    Publication Date: 2023-03-07
    Description: The ingestion on ciliates and phytoplankton dataset is based on samples taken during October 2008 in Northern Aegean Sea, the area influenced by the Black Sea water outflow. A Lagrangian experiment was established and copepod ingestion was estimated from experiments performed at stations according to the different positions of drifters during the cruise. Copepods for the experiments were obtained with slow non-quantitative tows from the upper 20 m layer of the water column using 200 µm mesh size nets fitted with a large non-filtering cod end. For the grazing experiments we used the following copepod species: Clausocalanus furcatus, and Temoraa stylifera according to the relevant reference (Bamstedt et al. 2000). Copepod clearance rates on ciliates were calculated according to Frost equations (Frost 1972). Ingestion rates were calculated by multiplying clearance rates by the initial standing stocks (Bamstedt et al. 2000). The egg production dataset is based on samples taken during October 2008 in Northern Aegean Sea, the area influenced by the Black Sea water outflow. A Lagrangian experiment was established and copepod egg production was estimated from experiments performed at stations according to the different positions of drifters during the cruise. Egg production rates of the dominant calanoid copepods were determined by incubation of fertilised females (eggs female/day) collected in the 0-20m layer. Copepod egg production was measured for the copepods Clausocalanus furcatus, Temora stylifera. On board experiments for the estimation of copepod egg production were taken place. For the estimation of copepod production (mgC/m**2/day), lengths (copepods and eggs) were converted to body carbon (Hopcroft et al., 1998) and production was estimated from biomass and weight-specific egg production rates, by assuming that those rates are representative for juvenile specific growth rates (Berggreen et al., 1988).
    Keywords: 0NA1a; 0NA2b; 0NA3b; 0NA5a; 0NA6a; 0NA7c; Aegaeo; Black Srea; Clausocalanus furcatus, egg production per female as carbon; Clausocalanus furcatus, ingestion rate as carbon; Computed/Converted; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Eastern Mediterranean Sea; Event label; Latitude of event; Longitude of event; Optional event label; SES_GR2; SES_GR2-0NA1a_WP2; SES_GR2-0NA2b_WP2; SES_GR2-0NA3b_WP2; SES_GR2-0NA5a_WP2; SES_GR2-0NA6a_WP2; SES_GR2-0NA7c_WP2; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; Temora stylifera, egg production per female as carbon; Temora stylifera, ingestion rate as carbon; WP2; WP-2 towed closing plankton net
    Type: Dataset
    Format: text/tab-separated-values, 28 data points
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  • 174
    Publication Date: 2023-03-07
    Description: The SES_GR2_Copepod Ingestion on ciliates and phytoplankton dataset is based on samples taken during August-September 2008 in Ionian Sea, Libyan Sea, Southern Aegean Sea and Northern Aegean Sea. Ingestion rates were estimated from experiments performed at all the third priority stations during the cruise according to DoW of Sesame project. Copepods for the experiments were obtained with slow non-quantitative tows from the upper 100 m layer of the water column using 200 µm mesh size nets fitted with a large non-filtering cod end. For the grazing experiments we used the following copepod species: Clausocalanus furcatus, Oithona spp. Temora stylifera and Acartia spp according to the relevant reference (Bamstedt et al. 2000). Copepod clearance rates on ciliates were calculated according to Frost equations (Frost 1972). Ingestion rates were calculated by multiplying clearance rates by the initial standing stocks (Bamstedt et al. 2000).
    Keywords: 00A1b; 0A10c; 0I05d; 0L02b; Acartia negligens, ingestion rate as carbon; Aegaeo; Clausocalanus furcatus, ingestion rate as carbon; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Latitude of event; Longitude of event; Measured/Determined; Mediterranean Sea; Oithona sp., ingestion rate as carbon; Optional event label; SES_GR2; SES_GR2-00A1b_WP2; SES_GR2-0A10c_WP2; SES_GR2-0I05d_WP2; SES_GR2-0L02b_WP2; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; Temora stylifera, ingestion rate as carbon; WP2; WP-2 towed closing plankton net
    Type: Dataset
    Format: text/tab-separated-values, 26 data points
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  • 175
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    PANGAEA
    In:  Supplement to: Fox, Bethany R Storrs; Wilson, Gary S; Lee, Daphne E (2015): A unique annually laminated maar lake sediment record shows orbital control of the Southern Hemisphere mid-latitudes across the Oligocene/Miocene boundary. Geological Society of America Bulletin, https://doi.org/10.1130/B31349.1
    Publication Date: 2023-03-13
    Description: This dataset includes palaeomagnetic inclination directions and density, reflectance (CIEL*a*b*) and red intensity (RGB) measurements from 100 metres of diatomaceous lake sediments from the Oligocene/Miocene Foulden Maar, New Zealand.
    Keywords: DRILL; Drilling/drill rig; FH2; Foulden Maar, Otago, New Zealand
    Type: Dataset
    Format: application/zip, 5 datasets
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  • 176
    Publication Date: 2023-03-14
    Keywords: 58PF20110928; 58PF20110928-moor; Aragonite saturation state; Autonomous pCO2 monitoring system, Battelle; Calcite saturation state; Calculated; CTD, SEA-BIRD SBE 37; DATE/TIME; DEPTH, water; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); LATITUDE; LONGITUDE; MOOR; Mooring; pH; Pressure, atmospheric; Salinity; Station M; Temperature, water; xCO2 (water) at sea surface temperature (dry air); xCO2 (water) at sea surface temperature (wet air)
    Type: Dataset
    Format: text/tab-separated-values, 7152 data points
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  • 177
    Publication Date: 2023-03-14
    Keywords: 58PF20120706; 58PF20120706-moor; Aragonite saturation state; Autonomous pCO2 monitoring system, Battelle; Calcite saturation state; Calculated; CTD, SEA-BIRD SBE 37; DATE/TIME; DEPTH, water; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); LATITUDE; LONGITUDE; MOOR; Mooring; pH; pH sensor SAMI2-pH, Sunburst Sensors; Pressure, atmospheric; Salinity; Station M; Temperature, water; xCO2 (water) at sea surface temperature (dry air); xCO2 (water) at sea surface temperature (wet air)
    Type: Dataset
    Format: text/tab-separated-values, 17674 data points
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  • 178
    Publication Date: 2023-03-14
    Keywords: 58PF20130530; 58PF20130530-moor; Aragonite saturation state; Autonomous pCO2 monitoring system, Battelle; Calcite saturation state; Calculated; CTD, SEA-BIRD SBE 37; DATE/TIME; DEPTH, water; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); LATITUDE; LONGITUDE; MOOR; Mooring; pH; pH sensor SAMI2-pH, Sunburst Sensors; Pressure, atmospheric; Salinity; Station M; Temperature, water; xCO2 (water) at sea surface temperature (dry air); xCO2 (water) at sea surface temperature (wet air)
    Type: Dataset
    Format: text/tab-separated-values, 28655 data points
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  • 179
    Publication Date: 2023-03-14
    Keywords: 58PF20110928; 58PF20110928-moor; Aragonite saturation state; Autonomous pCO2 monitoring system, Battelle; Calcite saturation state; Calculated; CTD, SEA-BIRD SBE 37; DATE/TIME; DEPTH, water; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); LATITUDE; LONGITUDE; MOOR; Mooring; pH; Pressure, atmospheric; Salinity; Station M; Temperature, water; xCO2 (water) at sea surface temperature (dry air); xCO2 (water) at sea surface temperature (wet air)
    Type: Dataset
    Format: text/tab-separated-values, 7149 data points
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  • 180
    Publication Date: 2023-03-14
    Keywords: 58PF20130530; 58PF20130530-moor; Aragonite saturation state; Autonomous pCO2 monitoring system, Battelle; Calcite saturation state; Calculated; CTD, SEA-BIRD SBE 37; DATE/TIME; DEPTH, water; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); LATITUDE; LONGITUDE; MOOR; Mooring; pH; pH sensor SAMI2-pH, Sunburst Sensors; Pressure, atmospheric; Salinity; Station M; Temperature, water; xCO2 (water) at sea surface temperature (dry air); xCO2 (water) at sea surface temperature (wet air)
    Type: Dataset
    Format: text/tab-separated-values, 28616 data points
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  • 181
    Publication Date: 2023-03-14
    Keywords: 58PF20130531; 58PF20130531-moor; Aragonite saturation state; Calcite saturation state; Calculated; calibrated; DATE/TIME; DEPTH, water; LATITUDE; LONGITUDE; MOOR; Mooring; pH; pH sensor SAMI2-pH, Sunburst Sensors; Salinity; Station M; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 6326 data points
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  • 182
    Publication Date: 2023-03-14
    Keywords: Alkalinity, total; BIOACID; Biological Impacts of Ocean Acidification; Boknis_Eck_1957; Carbon, inorganic, dissolved; Carbon dioxide, partial pressure; CTD/Rosette; CTD-RO; DATE/TIME; DEPTH, water; Oxygen; pH; Phosphate; Salinity; Silicate; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 530 data points
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  • 183
    Publication Date: 2023-03-14
    Keywords: 58PF20120706; 58PF20120706-moor; Aragonite saturation state; Autonomous pCO2 monitoring system, Battelle; Calcite saturation state; Calculated; CTD, SEA-BIRD SBE 37; DATE/TIME; DEPTH, water; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); LATITUDE; LONGITUDE; MOOR; Mooring; pH; pH sensor SAMI2-pH, Sunburst Sensors; Pressure, atmospheric; Salinity; Station M; Temperature, water; xCO2 (water) at sea surface temperature (dry air); xCO2 (water) at sea surface temperature (wet air)
    Type: Dataset
    Format: text/tab-separated-values, 17674 data points
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  • 184
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    PANGAEA
    In:  Alfred Wegener Institute - Research Unit Potsdam
    Publication Date: 2023-03-07
    Keywords: 11-CH-06F; AWI_PerDyn; AWI Arctic Land Expedition; awixrfraw2015; Chatanga2011; Hand corer; HCOR; Permafrost Research (Periglacial Dynamics) @ AWI; RU-Land_2011_Khatanga; Taymyr peninsula, northern Siberia
    Type: Dataset
    Format: application/zip, 7.3 MBytes
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  • 185
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    PANGAEA
    In:  Supplement to: Hoff, Ulrike; Biskaborn, Boris K; Dirksen, Veronika G; Dirksen, Oleg V; Kuhn, Gerhard; Meyer, Hanno; Nazarova, Larisa B; Roth, Alexandra; Diekmann, Bernhard (2015): Holocene environment of Central Kamchatka, Russia: Implications from a multi-proxy record of Two-Yurts Lake. Global and Planetary Change, 134, 101-117, https://doi.org/10.1016/j.gloplacha.2015.07.011
    Publication Date: 2023-03-07
    Description: Within the scope of Russian-German palaeoenvironmental research, Two-Yurts Lake (TYL, Dvuh-Yurtochnoe in Russian) was chosen as the main scientific target area to decipher Holocene climate variability on Kamchatka. The 5x2 km large and 26 m deep lake is of proglacial origin and situated on the eastern flank of Sredinny Ridge at the northwestern end of the Central Kamchatka Valley, outside the direct influence of active volcanism. Here, we present results of a multi-proxy study on sediment cores, spanning about the last 7000 years. The general tenor of the TYL record is an increase in continentality and winter snow cover in conjunction with a decrease in temperature, humidity, and biological productivity after 5000-4500 cal yrs BP, inferred from pollen and diatom data and the isotopic composition of organic carbon. The TYL proxy data also show that the late Holocene was punctuated by two colder spells, roughly between 4500 and 3500 cal yrs BP and between 1000 and 200 cal yrs BP, as local expressions of the Neoglacial and Little Ice Age, respectively. These environmental changes can be regarded as direct and indirect responses to climate change, as also demonstrated by other records in the regional terrestrial and marine realm. Long-term climate deterioration was driven by decreasing insolation, while the short-term climate excursions are best explained by local climatic processes. The latter affect the configuration of atmospheric pressure systems that control the sources as well as the temperature and moisture of air masses reaching Kamchatka.
    Keywords: AWI_PerDyn; Permafrost Research (Periglacial Dynamics) @ AWI
    Type: Dataset
    Format: application/zip, 12 datasets
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  • 186
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    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-25
    Keywords: Anihue_Bay; DATE/TIME; DEPTH, water; Jade Bay; Monitoring station; MONS; Temperature, water; Temperature logger, UTBI-001 TidbiT V2, SN 10356482
    Type: Dataset
    Format: text/tab-separated-values, 35211 data points
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  • 187
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-25
    Keywords: DATE/TIME; DEPTH, water; Islotes_Alloupa; Monitoring station; MONS; Temperature, water; Temperature logger, UTBI-001 TidbiT V2, SN 10356484
    Type: Dataset
    Format: text/tab-separated-values, 20350 data points
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  • 188
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-25
    Keywords: DATE/TIME; DEPTH, water; Ensenada_de_Las_Islas; Isla Jaime; Isla Jaime, Northern Patagonian Fjord Region, Chile; Monitoring station; MONS; Temperature, water; Temperature logger, UTBI-001 TidbiT V2, SN 10311752
    Type: Dataset
    Format: text/tab-separated-values, 35721 data points
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  • 189
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-25
    Keywords: Brazo Pillan, Chile; DATE/TIME; DEPTH, water; Monitoring station; MONS; Punta_Pillan; Temperature, water; Temperature logger, UTBI-001 TidbiT V2, SN 10311750
    Type: Dataset
    Format: text/tab-separated-values, 35897 data points
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  • 190
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-25
    Keywords: DATE/TIME; DEPTH, water; Monitoring station; MONS; Palena Bay, Chile; Temperature, water; Temperature logger, UTBI-001 TidbiT V2, SN 10356481; Tres_Hermanas
    Type: Dataset
    Format: text/tab-separated-values, 35618 data points
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  • 191
    Publication Date: 2023-03-25
    Keywords: Monitoring station; MONS; Piti Palena Fjord, Chile; Raul_Marin
    Type: Dataset
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, 1.6 MBytes
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  • 192
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-25
    Keywords: Monitoring station; MONS; Palena Bay, Chile; Tres_Hermanas
    Type: Dataset
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, 1.6 MBytes
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  • 193
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    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-25
    Keywords: Anihue_Laguna; DATE/TIME; DEPTH, water; Monitoring station; MONS; Puerto Aysen, Chile; Temperature, water; Temperature logger, UTBI-001 TidbiT V2, SN 10311749
    Type: Dataset
    Format: text/tab-separated-values, 32218 data points
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  • 194
    Publication Date: 2023-03-25
    Keywords: Aurelia aurita; Aurelia aurita, biomass, wet mass; Bilim; Bilim_BlackSea_1994-04-05; Bilim_BlackSea_HNet_199404_01; Bilim_BlackSea_HNet_199404_02; Bilim_BlackSea_HNet_199404_03; Bilim_BlackSea_HNet_199404_04; Bilim_BlackSea_HNet_199404_05; Bilim_BlackSea_HNet_199404_06; Bilim_BlackSea_HNet_199404_07; Bilim_BlackSea_HNet_199404_08; Bilim_BlackSea_HNet_199404_09; Bilim_BlackSea_HNet_199404_10; Bilim_BlackSea_HNet_199404_11; Bilim_BlackSea_HNet_199404_12; Bilim_BlackSea_HNet_199404_13; Bilim_BlackSea_HNet_199404_14; Bilim_BlackSea_HNet_199404_15; Bilim_BlackSea_HNet_199404_16; Bilim_BlackSea_HNet_199404_18; Bilim_BlackSea_HNet_199404_19; Bilim_BlackSea_HNet_199404_23; Bilim_BlackSea_HNet_199404_24; Bilim_BlackSea_HNet_199404_25; Bilim_BlackSea_HNet_199404_26; Bilim_BlackSea_HNet_199404_27; Bilim_BlackSea_HNet_199404_28; Bilim_BlackSea_HNet_199404_29; Bilim_BlackSea_HNet_199404_31; Bilim_BlackSea_HNet_199404_32; Bilim_BlackSea_HNet_199404_33; Bilim_BlackSea_HNet_199404_34; Bilim_BlackSea_HNet_199404_39; Bilim_BlackSea_HNet_199404_40; Bilim_BlackSea_HNet_199404_41; Bilim_BlackSea_HNet_199404_43; Bilim_BlackSea_HNet_199404_44; Bilim_BlackSea_HNet_199404_45; Bilim_BlackSea_HNet_199404_54; Bilim_BlackSea_HNet_199404_56; Bilim_BlackSea_HNet_199404_57; Bilim_BlackSea_HNet_199405_17; Bilim_BlackSea_HNet_199405_20; Bilim_BlackSea_HNet_199405_21; Bilim_BlackSea_HNet_199405_22; Bilim_BlackSea_HNet_199405_30; Bilim_BlackSea_HNet_199405_35; Bilim_BlackSea_HNet_199405_36; Bilim_BlackSea_HNet_199405_37; Bilim_BlackSea_HNet_199405_38; Bilim_BlackSea_HNet_199405_42; Bilim_BlackSea_HNet_199405_46; Bilim_BlackSea_HNet_199405_47; Bilim_BlackSea_HNet_199405_48; Bilim_BlackSea_HNet_199405_49; Bilim_BlackSea_HNet_199405_50; Bilim_BlackSea_HNet_199405_51; Bilim_BlackSea_HNet_199405_52; Bilim_BlackSea_HNet_199405_53; Bilim_BlackSea_HNet_199405_55; Bilim_BlackSea_HNet_199405_58; Bilim_BlackSea_HNet_199405_59; Bilim_BlackSea_HNet_199405_60; Bilim_BlackSea_HNet_199405_61; Bilim_BlackSea_HNet_199405_62; Bilim_BlackSea_HNet_199405_63; Bilim_BlackSea_HNet_199405_64; Bilim_BlackSea_HNet_199405_65; Bilim_BlackSea_HNet_199405_66; Bilim_BlackSea_HNet_199405_67; Bilim_BlackSea_HNet_199405_68; Bilim_BlackSea_HNet_199405_69; Bilim_BlackSea_HNet_199405_70; Bilim_BlackSea_HNet_199405_71; Bilim_BlackSea_HNet_199405_72; Bilim_BlackSea_HNet_199405_73; Bilim_BlackSea_HNet_199405_74; Bilim_BlackSea_HNet_199405_75; Bilim_BlackSea_HNet_199405_76; Bilim_BlackSea_HNet_199405_77; Bilim_BlackSea_HNet_199405_78; Bilim_BlackSea_HNet_199405_79; Bilim_BlackSea_HNet_199405_80; Bilim_BlackSea_HNet_199405_81; Bilim_BlackSea_HNet_199405_82; Bilim_BlackSea_HNet_199405_83; Bilim_BlackSea_HNet_199405_84; Bilim_BlackSea_HNet_199405_85; Black Sea; Counting; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Hensen net; HNET; L19M55; L20L15; L20M41; L20N05; L20N15; L25L22; L26M14; L30L30; L30N15; L40L15; L48K14; L50L00; L50L15; L50L30; L50M15; L50N15; L50P20; Latitude of event; Longitude of event; M01Q05; M02K43; M05S15; M06Q05; M08R15; M09R00; M10L30; M10M15; M10N15; M10N55; M10P15; M15L10; M15Q05; M15Q45; M15R00; M15R15; M15S15; M20L50; M24N42; M30K20; M30K46; M30L15; M30L45; M30M15; M30N15; M30P15; M30R15; M30S15; M31Q04; M43N15; M50K20; M50K49; M50L19; M50M00; M50M15; M50P15; M50P40; M50Q05; M50R15; M50R45; M50S15; M59L13; Mnemiopsis leidyi; Mnemiopsis leidyi, biomass, wet mass; N00M45; N05L33; N10L49; N10N15; N10P15; N10P45; N10Q15; N22M16; N26L28; N30N45; N31L22; N37M47; N39L55; N41L10; N44L48; N50L00; N50N19; N53N32; N56L33; P10M53; P16L51; P21N38; P27L34; P31M25; P39L48; P50M00; Pleurobrachia pileus; Pleurobrachia pileus, biomass, wet mass; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; Wet weighed, hand-balance
    Type: Dataset
    Format: text/tab-separated-values, 680 data points
    Location Call Number Expected Availability
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  • 195
    Publication Date: 2023-03-25
    Keywords: Aurelia aurita; Aurelia aurita, biomass, wet mass; Beroe ovata; Beroe ovata biomass, wet mass; Bilim; Bilim_BlackSea_2006-10; Bilim_BlackSea_HNet_200610_01; Bilim_BlackSea_HNet_200610_02; Bilim_BlackSea_HNet_200610_03; Bilim_BlackSea_HNet_200610_04; Bilim_BlackSea_HNet_200610_05; Bilim_BlackSea_HNet_200610_06; Bilim_BlackSea_HNet_200610_07; Bilim_BlackSea_HNet_200610_08; Bilim_BlackSea_HNet_200610_09; Bilim_BlackSea_HNet_200610_10; Bilim_BlackSea_HNet_200610_11; Bilim_BlackSea_HNet_200610_12; Bilim_BlackSea_HNet_200610_13; Bilim_BlackSea_HNet_200610_14; Bilim_BlackSea_HNet_200610_15; Bilim_BlackSea_HNet_200610_16; Bilim_BlackSea_HNet_200610_17; Bilim_BlackSea_HNet_200610_18; Bilim_BlackSea_HNet_200610_19; Bilim_BlackSea_HNet_200610_20; Bilim_BlackSea_HNet_200610_21; Bilim_BlackSea_HNet_200610_22; Bilim_BlackSea_HNet_200610_23; Bilim_BlackSea_HNet_200610_24; Bilim_BlackSea_HNet_200610_25; Bilim_BlackSea_HNet_200610_26; Bilim_BlackSea_HNet_200610_27; Bilim_BlackSea_HNet_200610_28; Bilim_BlackSea_HNet_200610_29; Bilim_BlackSea_HNet_200610_30; Bilim_BlackSea_HNet_200610_31; Bilim_BlackSea_HNet_200610_32; Bilim_BlackSea_HNet_200610_33; Bilim_BlackSea_HNet_200610_34; Bilim_BlackSea_HNet_200610_35; Bilim_BlackSea_HNet_200610_36; Bilim_BlackSea_HNet_200610_37; Bilim_BlackSea_HNet_200610_38; Bilim_BlackSea_HNet_200610_39; Bilim_BlackSea_HNet_200610_40; Bilim_BlackSea_HNet_200610_41; Bilim_BlackSea_HNet_200610_42; Bilim_BlackSea_HNet_200610_43; Bilim_BlackSea_HNet_200610_44; Bilim_BlackSea_HNet_200610_45; Bilim_BlackSea_HNet_200610_46; Bilim_BlackSea_HNet_200610_47; Bilim_BlackSea_HNet_200610_48; Bilim_BlackSea_HNet_200610_49; Bilim_BlackSea_HNet_200610_50; Bilim_BlackSea_HNet_200610_51; Bilim_BlackSea_HNet_200610_52; Bilim_BlackSea_HNet_200610_53; Bilim_BlackSea_HNet_200610_54; Bilim_BlackSea_HNet_200610_55; Bilim_BlackSea_HNet_200610_56; Bilim_BlackSea_HNet_200610_57; Bilim_BlackSea_HNet_200610_58; Bilim_BlackSea_HNet_200610_59; Bilim_BlackSea_HNet_200610_60; Bilim_BlackSea_HNet_200610_61; Bilim_BlackSea_HNet_200610_62; Bilim_BlackSea_HNet_200610_63; Bilim_BlackSea_HNet_200610_64; Bilim_BlackSea_HNet_200610_65; Bilim_BlackSea_HNet_200610_66; Bilim_BlackSea_HNet_200610_67; Bilim_BlackSea_HNet_200610_68; Bilim_BlackSea_HNet_200610_69; Bilim_BlackSea_HNet_200610_70; Bilim_BlackSea_HNet_200610_71; Bilim_BlackSea_HNet_200610_72; Black Sea; Counting; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Hensen net; HNET; L04W11; L05W45; L05X15; L05X45; L05Y33; L06Y00; L15L45; L15N15; L15V15; L15W15; L15W45; L15X15; L15Y15; L18L15; L20M30; L28T18; L29.5N45; L30K45; L30L45; L30M45; L30N15; L30T45; L30W45; L30X45; L30Y45; L39N45; L45T18; L47P24; L50L15; L50M15; L50N15; L50P15; L50S45; L50V15; L50W15; L50X15; L50Y15; L56P45; Latitude of event; Longitude of event; M00R15; M00S15; M02Q17; M04Q44; M10K45; M10L45; M10M45; M10N15; M10N45; M10P45; M10Q15; M10S45; M10T45; M10V45; M10W45; M15R15; M17R45; M30N15; M30P15; M30Q15; M30R15; M30S15; M30T15; M50N45; M50P45; M50Q45; M50R45; M50S45; Mnemiopsis leidyi; Mnemiopsis leidyi, biomass, wet mass; N10Q15; N10R15; Pleurobrachia pileus; Pleurobrachia pileus, biomass, wet mass; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; Wet weighed, hand-balance
    Type: Dataset
    Format: text/tab-separated-values, 720 data points
    Location Call Number Expected Availability
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  • 196
    Publication Date: 2023-03-25
    Description: Cruise 1991-06 conductucted covering TEEZ with a large cruise presents a dataset of macro gelatinous biomass and abundance in the Southern Black Sea in June 1991.
    Keywords: Aurelia aurita; Aurelia aurita, biomass, wet mass; Bilim; Bilim_BlackSea_1991-06; Bilim_BlackSea_HNet_199106_01; Bilim_BlackSea_HNet_199106_02; Bilim_BlackSea_HNet_199106_03; Bilim_BlackSea_HNet_199106_04; Bilim_BlackSea_HNet_199106_05; Bilim_BlackSea_HNet_199106_06; Bilim_BlackSea_HNet_199106_07; Bilim_BlackSea_HNet_199106_08; Bilim_BlackSea_HNet_199106_09; Bilim_BlackSea_HNet_199106_10; Bilim_BlackSea_HNet_199106_11; Bilim_BlackSea_HNet_199106_12; Bilim_BlackSea_HNet_199106_13; Bilim_BlackSea_HNet_199106_14; Bilim_BlackSea_HNet_199106_15; Bilim_BlackSea_HNet_199106_16; Bilim_BlackSea_HNet_199106_17; Bilim_BlackSea_HNet_199106_18; Bilim_BlackSea_HNet_199106_19; Bilim_BlackSea_HNet_199106_20; Bilim_BlackSea_HNet_199106_21; Bilim_BlackSea_HNet_199106_22; Bilim_BlackSea_HNet_199106_23; Bilim_BlackSea_HNet_199106_24; Bilim_BlackSea_HNet_199106_25; Bilim_BlackSea_HNet_199106_26; Bilim_BlackSea_HNet_199106_27; Bilim_BlackSea_HNet_199106_28; Bilim_BlackSea_HNet_199106_29; Bilim_BlackSea_HNet_199106_30; Bilim_BlackSea_HNet_199106_31; Bilim_BlackSea_HNet_199106_32; Bilim_BlackSea_HNet_199106_33; Bilim_BlackSea_HNet_199106_34; Bilim_BlackSea_HNet_199106_35; Bilim_BlackSea_HNet_199106_36; Bilim_BlackSea_HNet_199106_37; Bilim_BlackSea_HNet_199106_38; Bilim_BlackSea_HNet_199106_39; Bilim_BlackSea_HNet_199106_40; Bilim_BlackSea_HNet_199106_41; Bilim_BlackSea_HNet_199106_42; Bilim_BlackSea_HNet_199106_43; Bilim_BlackSea_HNet_199106_44; Bilim_BlackSea_HNet_199106_45; Bilim_BlackSea_HNet_199106_46; Bilim_BlackSea_HNet_199106_47; Bilim_BlackSea_HNet_199106_48; Bilim_BlackSea_HNet_199106_49; Bilim_BlackSea_HNet_199106_50; Bilim_BlackSea_HNet_199106_51; Bilim_BlackSea_HNet_199106_52; Bilim_BlackSea_HNet_199106_53; Bilim_BlackSea_HNet_199106_54; Bilim_BlackSea_HNet_199106_55; Bilim_BlackSea_HNet_199106_56; Bilim_BlackSea_HNet_199106_57; Bilim_BlackSea_HNet_199106_58; Bilim_BlackSea_HNet_199106_59; Bilim_BlackSea_HNet_199106_60; Bilim_BlackSea_HNet_199106_61; Bilim_BlackSea_HNet_199106_62; Bilim_BlackSea_HNet_199106_63; Bilim_BlackSea_HNet_199106_64; Bilim_BlackSea_HNet_199106_65; Bilim_BlackSea_HNet_199106_66; Bilim_BlackSea_HNet_199106_67; Bilim_BlackSea_HNet_199106_68; Black Sea; Counting; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Hensen net; HNET; Latitude of event; Longitude of event; Mnemiopsis leidyi; Mnemiopsis leidyi, biomass, wet mass; Pleurobrachia pileus; Pleurobrachia pileus, biomass, wet mass; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; Wet weighed, hand-balance
    Type: Dataset
    Format: text/tab-separated-values, 544 data points
    Location Call Number Expected Availability
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  • 197
    Publication Date: 2023-03-25
    Keywords: Aurelia aurita; Aurelia aurita, biomass, wet mass; Beroe ovata; Beroe ovata biomass, wet mass; Bilim; Bilim_BlackSea_2006-06; Bilim_BlackSea_HNet_200606_01; Bilim_BlackSea_HNet_200606_02; Bilim_BlackSea_HNet_200606_03; Bilim_BlackSea_HNet_200606_04; Bilim_BlackSea_HNet_200606_05; Bilim_BlackSea_HNet_200606_06; Bilim_BlackSea_HNet_200606_07; Bilim_BlackSea_HNet_200606_08; Bilim_BlackSea_HNet_200606_09; Bilim_BlackSea_HNet_200606_10; Bilim_BlackSea_HNet_200606_11; Bilim_BlackSea_HNet_200606_12; Bilim_BlackSea_HNet_200606_13; Bilim_BlackSea_HNet_200606_14; Bilim_BlackSea_HNet_200606_15; Bilim_BlackSea_HNet_200606_16; Bilim_BlackSea_HNet_200606_17; Bilim_BlackSea_HNet_200606_18; Bilim_BlackSea_HNet_200606_19; Bilim_BlackSea_HNet_200606_20; Bilim_BlackSea_HNet_200606_21; Bilim_BlackSea_HNet_200606_22; Bilim_BlackSea_HNet_200606_23; Bilim_BlackSea_HNet_200606_24; Bilim_BlackSea_HNet_200606_25; Bilim_BlackSea_HNet_200606_26; Bilim_BlackSea_HNet_200606_27; Bilim_BlackSea_HNet_200606_28; Bilim_BlackSea_HNet_200606_29; Bilim_BlackSea_HNet_200606_30; Bilim_BlackSea_HNet_200606_31; Bilim_BlackSea_HNet_200606_32; Bilim_BlackSea_HNet_200606_33; Bilim_BlackSea_HNet_200606_34; Bilim_BlackSea_HNet_200606_35; Bilim_BlackSea_HNet_200606_36; Bilim_BlackSea_HNet_200606_37; Bilim_BlackSea_HNet_200606_38; Bilim_BlackSea_HNet_200606_39; Bilim_BlackSea_HNet_200606_40; Bilim_BlackSea_HNet_200606_41; Bilim_BlackSea_HNet_200606_42; Bilim_BlackSea_HNet_200606_43; Bilim_BlackSea_HNet_200606_44; Bilim_BlackSea_HNet_200606_45; Bilim_BlackSea_HNet_200606_46; Bilim_BlackSea_HNet_200606_47; Bilim_BlackSea_HNet_200606_48; Bilim_BlackSea_HNet_200606_49; Bilim_BlackSea_HNet_200606_50; Bilim_BlackSea_HNet_200606_51; Bilim_BlackSea_HNet_200606_52; Bilim_BlackSea_HNet_200606_53; Bilim_BlackSea_HNet_200606_54; Bilim_BlackSea_HNet_200606_55; Bilim_BlackSea_HNet_200606_56; Bilim_BlackSea_HNet_200606_57; Bilim_BlackSea_HNet_200606_58; Bilim_BlackSea_HNet_200606_59; Bilim_BlackSea_HNet_200606_60; Bilim_BlackSea_HNet_200606_61; Bilim_BlackSea_HNet_200606_62; Bilim_BlackSea_HNet_200606_63; Bilim_BlackSea_HNet_200606_64; Bilim_BlackSea_HNet_200606_65; Black Sea; Counting; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Hensen net; HNET; L04W11; L05W45; L05X15; L05X45; L05Y33; L06Y00; L15L45; L15V15; L15W15; L15X15; L15Y15; L15Y45; L18L15; L20M30(L18N00); L28T18; L30K45; L30L45; L30M45; L30N15; L30T45; L30V45; L30W45; L30X45; L30Y45; L39N45; L43S26; L50L15; L50M15; L50N15; L50P15; L50S45; L50V15; L50W15; L50X15; L50Y15; L56P45; Latitude of event; Longitude of event; M00R15; M00S15; M04Q44; M10K45; M10M45; M10N45; M10P45; M10Q15; M10S45; M10T45; M10V45; M10W45; M15Q45; M17R45; M30M15; M30N15; M30P15; M30Q15; M30R15; M30S15; M30T15; M30T45; M50N45; M50P45; M50Q45; M50R45; M50S45; Mnemiopsis leidyi; Mnemiopsis leidyi, biomass, wet mass; N10Q15; N10R15; Pleurobrachia pileus; Pleurobrachia pileus, biomass, wet mass; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; Wet weighed, hand-balance
    Type: Dataset
    Format: text/tab-separated-values, 650 data points
    Location Call Number Expected Availability
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  • 198
    Publication Date: 2023-03-25
    Keywords: Aurelia aurita; Aurelia aurita, biomass, wet mass; Bilim; Bilim_BlackSea_1992-07; Bilim_BlackSea_HNet_199207_01; Bilim_BlackSea_HNet_199207_02; Bilim_BlackSea_HNet_199207_03; Bilim_BlackSea_HNet_199207_04; Bilim_BlackSea_HNet_199207_05; Bilim_BlackSea_HNet_199207_06; Bilim_BlackSea_HNet_199207_07; Bilim_BlackSea_HNet_199207_08; Bilim_BlackSea_HNet_199207_09; Bilim_BlackSea_HNet_199207_10; Bilim_BlackSea_HNet_199207_100; Bilim_BlackSea_HNet_199207_101; Bilim_BlackSea_HNet_199207_102; Bilim_BlackSea_HNet_199207_103; Bilim_BlackSea_HNet_199207_104; Bilim_BlackSea_HNet_199207_105; Bilim_BlackSea_HNet_199207_106; Bilim_BlackSea_HNet_199207_107; Bilim_BlackSea_HNet_199207_108; Bilim_BlackSea_HNet_199207_109; Bilim_BlackSea_HNet_199207_11; Bilim_BlackSea_HNet_199207_110; Bilim_BlackSea_HNet_199207_111; Bilim_BlackSea_HNet_199207_112; Bilim_BlackSea_HNet_199207_113; Bilim_BlackSea_HNet_199207_114; Bilim_BlackSea_HNet_199207_115; Bilim_BlackSea_HNet_199207_116; Bilim_BlackSea_HNet_199207_117; Bilim_BlackSea_HNet_199207_118; Bilim_BlackSea_HNet_199207_119; Bilim_BlackSea_HNet_199207_12; Bilim_BlackSea_HNet_199207_120; Bilim_BlackSea_HNet_199207_121; Bilim_BlackSea_HNet_199207_122; Bilim_BlackSea_HNet_199207_123; Bilim_BlackSea_HNet_199207_124; Bilim_BlackSea_HNet_199207_125; Bilim_BlackSea_HNet_199207_126; Bilim_BlackSea_HNet_199207_127; Bilim_BlackSea_HNet_199207_128; Bilim_BlackSea_HNet_199207_129; Bilim_BlackSea_HNet_199207_13; Bilim_BlackSea_HNet_199207_130; Bilim_BlackSea_HNet_199207_131; Bilim_BlackSea_HNet_199207_132; Bilim_BlackSea_HNet_199207_133; Bilim_BlackSea_HNet_199207_134; Bilim_BlackSea_HNet_199207_135; Bilim_BlackSea_HNet_199207_136; Bilim_BlackSea_HNet_199207_137; Bilim_BlackSea_HNet_199207_138; Bilim_BlackSea_HNet_199207_139; Bilim_BlackSea_HNet_199207_14; Bilim_BlackSea_HNet_199207_140; Bilim_BlackSea_HNet_199207_141; Bilim_BlackSea_HNet_199207_142; Bilim_BlackSea_HNet_199207_143; Bilim_BlackSea_HNet_199207_15; Bilim_BlackSea_HNet_199207_16; Bilim_BlackSea_HNet_199207_17; Bilim_BlackSea_HNet_199207_18; Bilim_BlackSea_HNet_199207_19; Bilim_BlackSea_HNet_199207_20; Bilim_BlackSea_HNet_199207_21; Bilim_BlackSea_HNet_199207_22; Bilim_BlackSea_HNet_199207_23; Bilim_BlackSea_HNet_199207_24; Bilim_BlackSea_HNet_199207_25; Bilim_BlackSea_HNet_199207_26; Bilim_BlackSea_HNet_199207_27; Bilim_BlackSea_HNet_199207_28; Bilim_BlackSea_HNet_199207_29; Bilim_BlackSea_HNet_199207_30; Bilim_BlackSea_HNet_199207_31; Bilim_BlackSea_HNet_199207_32; Bilim_BlackSea_HNet_199207_33; Bilim_BlackSea_HNet_199207_34; Bilim_BlackSea_HNet_199207_35; Bilim_BlackSea_HNet_199207_36; Bilim_BlackSea_HNet_199207_37; Bilim_BlackSea_HNet_199207_38; Bilim_BlackSea_HNet_199207_39; Bilim_BlackSea_HNet_199207_40; Bilim_BlackSea_HNet_199207_41; Bilim_BlackSea_HNet_199207_42; Bilim_BlackSea_HNet_199207_43; Bilim_BlackSea_HNet_199207_44; Bilim_BlackSea_HNet_199207_45; Bilim_BlackSea_HNet_199207_46; Bilim_BlackSea_HNet_199207_47; Bilim_BlackSea_HNet_199207_48; Bilim_BlackSea_HNet_199207_49; Bilim_BlackSea_HNet_199207_50; Bilim_BlackSea_HNet_199207_51; Bilim_BlackSea_HNet_199207_52; Bilim_BlackSea_HNet_199207_53; Bilim_BlackSea_HNet_199207_54; Bilim_BlackSea_HNet_199207_55; Bilim_BlackSea_HNet_199207_56; Bilim_BlackSea_HNet_199207_57; Bilim_BlackSea_HNet_199207_58; Bilim_BlackSea_HNet_199207_59; Bilim_BlackSea_HNet_199207_60; Bilim_BlackSea_HNet_199207_61; Bilim_BlackSea_HNet_199207_62; Bilim_BlackSea_HNet_199207_63; Bilim_BlackSea_HNet_199207_64; Bilim_BlackSea_HNet_199207_65; Bilim_BlackSea_HNet_199207_66; Bilim_BlackSea_HNet_199207_67; Bilim_BlackSea_HNet_199207_68; Bilim_BlackSea_HNet_199207_69; Bilim_BlackSea_HNet_199207_70; Bilim_BlackSea_HNet_199207_71; Bilim_BlackSea_HNet_199207_72; Bilim_BlackSea_HNet_199207_73; Bilim_BlackSea_HNet_199207_74; Bilim_BlackSea_HNet_199207_75; Bilim_BlackSea_HNet_199207_76; Bilim_BlackSea_HNet_199207_77; Bilim_BlackSea_HNet_199207_78; Bilim_BlackSea_HNet_199207_79; Bilim_BlackSea_HNet_199207_80; Bilim_BlackSea_HNet_199207_81; Bilim_BlackSea_HNet_199207_82; Bilim_BlackSea_HNet_199207_83; Bilim_BlackSea_HNet_199207_84; Bilim_BlackSea_HNet_199207_85; Bilim_BlackSea_HNet_199207_86; Bilim_BlackSea_HNet_199207_87; Bilim_BlackSea_HNet_199207_88; Bilim_BlackSea_HNet_199207_89; Bilim_BlackSea_HNet_199207_90; Bilim_BlackSea_HNet_199207_91; Bilim_BlackSea_HNet_199207_92; Bilim_BlackSea_HNet_199207_93; Bilim_BlackSea_HNet_199207_94; Bilim_BlackSea_HNet_199207_95; Bilim_BlackSea_HNet_199207_96; Bilim_BlackSea_HNet_199207_97; Bilim_BlackSea_HNet_199207_98; Bilim_BlackSea_HNet_199207_99; Black Sea; Counting; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Hensen net; HNET; L04W30; L05W15; L05Y15; L06X15; L06Y30; L14L30; L15L45; L15V15; L15V45; L15W15; L15W45; L15X15; L15X45; L15Y15; L15Y45; L17Z00; L18L00; L18L15; L20M15; L20N15; L30K45; L30L00; L30L15; L30L30; L30L45; L30M15; L30M45; L30N00; L30N15; L30N30; L30V15; L30V45; L30W15; L30W45; L30X15; L30X45; L30Y15; L30Y45; L30Z10; L35N45; L35T20; L35T45; L40K37; L45T20; L49K15; L50K25; L50L00; L50L15; L50L30; L50L45; L50M15; L50M45; L50N00; L50N15; L50N45; L50P15; L50S45; L50T45; L50V15; L50V45; L50W15; L50W45; L50X15; L50X45; L50Y15; L50Y45; L52S20; L53K35; L55K45; Latitude of event; Longitude of event; M00L00; M00R15; M00S15; M01Q14; M08Q15; M08R15; M10K45; M10L15; M10L45; M10M15; M10M45; M10N15; M10N45; M10P15; M10P45; M10T15; M10T45; M10V15; M10V45; M10W15; M10W45; M10X15; M15Q15; M15Q45; M15R15; M17R45; M30L15; M30L45; M30M15; M30M45; M30N15; M30N45; M30P15; M30P45; M30Q15; M30Q45; M30R15; M30R45; M30S15; M30S45; M30T15; M30T45; M30V15; M30V45; M30W15; M50M15; M50M45; M50N15; M50N45; M50P15; M50P45; M50Q15; M50Q45; M50R15; M50R45; M50S15; M50S45; M50T15; M50T45; M50V15; M50V45; Mnemiopsis leidyi; Mnemiopsis leidyi, biomass, wet mass; N10N15; N10N45; N10P15; N10P45; N10Q15; N10Q45; N10R15; N10R45; N10S15; N10S45; N10T15; N10T45; N30N45; Pleurobrachia pileus; Pleurobrachia pileus, biomass, wet mass; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; Wet weighed, hand-balance
    Type: Dataset
    Format: text/tab-separated-values, 1075 data points
    Location Call Number Expected Availability
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  • 199
    Publication Date: 2023-03-25
    Keywords: Aurelia aurita; Aurelia aurita, biomass, wet mass; Bilim; Bilim_BlackSea_1995-03-04; Bilim_BlackSea_HNet_199503_01; Bilim_BlackSea_HNet_199503_02; Bilim_BlackSea_HNet_199503_03; Bilim_BlackSea_HNet_199503_04; Bilim_BlackSea_HNet_199503_05; Bilim_BlackSea_HNet_199503_06; Bilim_BlackSea_HNet_199503_07; Bilim_BlackSea_HNet_199503_08; Bilim_BlackSea_HNet_199503_09; Bilim_BlackSea_HNet_199503_10; Bilim_BlackSea_HNet_199503_11; Bilim_BlackSea_HNet_199503_12; Bilim_BlackSea_HNet_199503_13; Bilim_BlackSea_HNet_199503_14; Bilim_BlackSea_HNet_199503_15; Bilim_BlackSea_HNet_199503_16; Bilim_BlackSea_HNet_199503_17; Bilim_BlackSea_HNet_199503_18; Bilim_BlackSea_HNet_199503_19; Bilim_BlackSea_HNet_199503_20; Bilim_BlackSea_HNet_199503_21; Bilim_BlackSea_HNet_199503_22; Bilim_BlackSea_HNet_199503_23; Bilim_BlackSea_HNet_199503_25; Bilim_BlackSea_HNet_199503_26; Bilim_BlackSea_HNet_199503_27; Bilim_BlackSea_HNet_199503_28; Bilim_BlackSea_HNet_199503_29; Bilim_BlackSea_HNet_199503_30; Bilim_BlackSea_HNet_199503_31; Bilim_BlackSea_HNet_199503_32; Bilim_BlackSea_HNet_199503_33; Bilim_BlackSea_HNet_199503_34; Bilim_BlackSea_HNet_199503_35; Bilim_BlackSea_HNet_199503_36; Bilim_BlackSea_HNet_199503_37; Bilim_BlackSea_HNet_199503_38; Bilim_BlackSea_HNet_199503_39; Bilim_BlackSea_HNet_199503_40; Bilim_BlackSea_HNet_199503_41; Bilim_BlackSea_HNet_199503_42; Bilim_BlackSea_HNet_199503_43; Bilim_BlackSea_HNet_199503_44; Bilim_BlackSea_HNet_199503_45; Bilim_BlackSea_HNet_199503_46; Bilim_BlackSea_HNet_199503_47; Bilim_BlackSea_HNet_199503_48; Bilim_BlackSea_HNet_199503_49; Bilim_BlackSea_HNet_199503_50; Bilim_BlackSea_HNet_199503_51; Bilim_BlackSea_HNet_199503_52; Bilim_BlackSea_HNet_199504_100; Bilim_BlackSea_HNet_199504_101; Bilim_BlackSea_HNet_199504_102; Bilim_BlackSea_HNet_199504_103; Bilim_BlackSea_HNet_199504_104; Bilim_BlackSea_HNet_199504_105; Bilim_BlackSea_HNet_199504_106; Bilim_BlackSea_HNet_199504_107; Bilim_BlackSea_HNet_199504_108; Bilim_BlackSea_HNet_199504_53; Bilim_BlackSea_HNet_199504_54; Bilim_BlackSea_HNet_199504_55; Bilim_BlackSea_HNet_199504_56; Bilim_BlackSea_HNet_199504_57; Bilim_BlackSea_HNet_199504_59; Bilim_BlackSea_HNet_199504_60; Bilim_BlackSea_HNet_199504_61; Bilim_BlackSea_HNet_199504_62; Bilim_BlackSea_HNet_199504_63; Bilim_BlackSea_HNet_199504_64; Bilim_BlackSea_HNet_199504_65; Bilim_BlackSea_HNet_199504_66; Bilim_BlackSea_HNet_199504_67; Bilim_BlackSea_HNet_199504_68; Bilim_BlackSea_HNet_199504_69; Bilim_BlackSea_HNet_199504_70; Bilim_BlackSea_HNet_199504_71; Bilim_BlackSea_HNet_199504_72; Bilim_BlackSea_HNet_199504_73; Bilim_BlackSea_HNet_199504_74; Bilim_BlackSea_HNet_199504_75; Bilim_BlackSea_HNet_199504_76; Bilim_BlackSea_HNet_199504_77; Bilim_BlackSea_HNet_199504_78; Bilim_BlackSea_HNet_199504_79; Bilim_BlackSea_HNet_199504_80; Bilim_BlackSea_HNet_199504_81; Bilim_BlackSea_HNet_199504_82; Bilim_BlackSea_HNet_199504_83; Bilim_BlackSea_HNet_199504_84; Bilim_BlackSea_HNet_199504_85; Bilim_BlackSea_HNet_199504_86; Bilim_BlackSea_HNet_199504_87; Bilim_BlackSea_HNet_199504_88; Bilim_BlackSea_HNet_199504_89; Bilim_BlackSea_HNet_199504_90; Bilim_BlackSea_HNet_199504_91; Bilim_BlackSea_HNet_199504_92; Bilim_BlackSea_HNet_199504_93; Bilim_BlackSea_HNet_199504_94; Bilim_BlackSea_HNet_199504_95; Bilim_BlackSea_HNet_199504_96; Bilim_BlackSea_HNet_199504_97; Bilim_BlackSea_HNet_199504_98; Bilim_BlackSea_HNet_199504_99; Black Sea; Counting; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Hensen net; HNET; L15V15; L15V45; L15W15; L15W45; L15X15; L15X45; L15Y15; L15Y45; L18L15; L20L45; L20M15; L20M45; L20N15; L30L15; L30L45; L30M15; L30M45; L30N15; L30V15; L30V45; L30W15; L30W45; L30X15; L30X45; L30Y15; L30Y45; L35N45; L35T15; L35T45; L46L15; L50N45; L50P15; L50S45; L50T15; L50T45; L50V15; L50V45; L50W15; L50W45; L50X15; L50X45; L50Y15; L50Y45; L56K17; L59K35; Latitude of event; Longitude of event; M04K53; M05S15; M07W15; M07W45; M07X15; M10L15; M10P15; M10S45; M10T15; M10T45; M10V15; M10V45; M11K15; M15S15; M25V45; M25W15; M30K13; M30K42; M30L00; M30P15; M30S15; M30S45; M30T15; M30T45; M30V15; M40L15; M50S15; M50S45; M50T15; M50T45; M50V15; Mnemiopsis leidyi; Mnemiopsis leidyi, biomass, wet mass; N00K12; N00K30; N00K45; N00L15; N10S15; N10S45; N10T15; N10T45; N14K44; N22L20; N22M00; N28K57; N42L50; N55L26; N58M48; N59M21; P03L05; P07M01; P15L46; P16M35; P17L06; P22L22; P26M17; P32M49; P35M02; P42M34; P47L55; P48M18; P49L53; P53L58; Pleurobrachia pileus; Pleurobrachia pileus, biomass, wet mass; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; Wet weighed, hand-balance
    Type: Dataset
    Format: text/tab-separated-values, 848 data points
    Location Call Number Expected Availability
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  • 200
    Publication Date: 2023-03-25
    Keywords: Aurelia aurita; Aurelia aurita, biomass, wet mass; Bilim; Bilim_BlackSea_1993-04; Bilim_BlackSea_HNet_199304_01; Bilim_BlackSea_HNet_199304_02; Bilim_BlackSea_HNet_199304_03; Bilim_BlackSea_HNet_199304_04; Bilim_BlackSea_HNet_199304_05; Bilim_BlackSea_HNet_199304_06; Bilim_BlackSea_HNet_199304_07; Bilim_BlackSea_HNet_199304_08; Bilim_BlackSea_HNet_199304_09; Bilim_BlackSea_HNet_199304_10; Bilim_BlackSea_HNet_199304_11; Bilim_BlackSea_HNet_199304_12; Bilim_BlackSea_HNet_199304_13; Bilim_BlackSea_HNet_199304_14; Bilim_BlackSea_HNet_199304_15; Bilim_BlackSea_HNet_199304_16; Bilim_BlackSea_HNet_199304_17; Bilim_BlackSea_HNet_199304_18; Bilim_BlackSea_HNet_199304_19; Bilim_BlackSea_HNet_199304_20; Bilim_BlackSea_HNet_199304_22; Bilim_BlackSea_HNet_199304_23; Bilim_BlackSea_HNet_199304_24; Bilim_BlackSea_HNet_199304_26; Bilim_BlackSea_HNet_199304_27; Bilim_BlackSea_HNet_199304_28; Bilim_BlackSea_HNet_199304_29; Bilim_BlackSea_HNet_199304_30; Bilim_BlackSea_HNet_199304_31; Bilim_BlackSea_HNet_199304_32; Bilim_BlackSea_HNet_199304_33; Bilim_BlackSea_HNet_199304_34; Bilim_BlackSea_HNet_199304_35; Bilim_BlackSea_HNet_199304_37; Bilim_BlackSea_HNet_199304_39; Bilim_BlackSea_HNet_199304_41; Bilim_BlackSea_HNet_199304_43; Bilim_BlackSea_HNet_199304_44; Bilim_BlackSea_HNet_199304_45; Bilim_BlackSea_HNet_199304_46; Bilim_BlackSea_HNet_199304_47; Bilim_BlackSea_HNet_199304_49; Black Sea; Counting; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Event label; Hensen net; HNET; L20L15; L20N15; L30L15; L30M15; L30M15A; L30N15; L40K28; L40L15; L40L15a; L40L45; L50L15; L50P15; L51K38; Latitude of event; Longitude of event; M07L05; M10L15; M10N15A; M15R15; M15S15; M15S15A; M30L45; M30Q15; M50M15; M50M45; M50S15; Mnemiopsis leidyi; Mnemiopsis leidyi, biomass; N10N15; N10Q15; N10R15; N10R45; N30N45; Pleurobrachia pileus; Pleurobrachia pileus, biomass, wet mass; R16; R17; R21; R5; R7; R8; SESAME; Southern European Seas: Assessing and Modelling Ecosystem Changes; U10; U15; U7; U7A; U8; U8A; U9; Wet weighed, hand-balance
    Type: Dataset
    Format: text/tab-separated-values, 336 data points
    Location Call Number Expected Availability
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