ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • 2020-2024  (33,005)
  • 2010-2014  (22)
  • 1960-1964  (79,586)
  • 2022  (33,005)
  • 1961  (79,584)
Collection
Keywords
Publisher
Language
Years
Year
  • 1
    facet.materialart.
    Unknown
    Within- and Between-Event Variabilities of Strong-Velocity Pulses of Moderate Earthquakes within Dense Seismic Arrays (2022)
    In:  Bulletin of the Seismological Society of America
    Details
    Publication Date: 2024-07-01
    Description: Ground motion with strong‐velocity pulses can cause significant damage to buildings and structures at certain periods; hence, knowing the period and velocity amplitude of such pulses is critical for earthquake structural engineering. However, the physical factors relating the scaling of pulse periods with magnitude are poorly understood. In this study, we investigate moderate but damaging earthquakes (⁠Mw 6–7) and characterize ground‐motion pulses using the method of Shahi and Baker (2014) while considering the potential static‐offset effects. We confirm that the within‐event variability of the pulses is large. The identified pulses in this study are mostly from strike‐slip‐like earthquakes. We further perform simulations using the frequency–wavenumber algorithm to investigate the causes of the variability of the pulse periods within and between events for moderate strike‐slip earthquakes. We test the effect of fault dips, and the impact of the asperity locations and sizes. The simulations reveal that the asperity properties have a high impact on the pulse periods and amplitudes at nearby stations. Our results emphasize the importance of asperity characteristics, in addition to earthquake magnitudes for the occurrence and properties of pulses produced by the forward directivity effect. We finally quantify and discuss within‐ and between‐event variabilities of pulse properties at short distances.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OA)
  • 2
    facet.materialart.
    Unknown
    Report on modifications of ocean carbon cycle feedbacks under ocean alkalinization (2022)
    OceanNETs
    Details
    Publication Date: 2024-07-01
    Description: Ocean Alkalinization deliberately modifies the chemistry of the surface ocean to enhance the uptake of atmospheric CO2. Here we quantify, using idealized Earth system model (ESM) simulations, changes in carbon cycle feedbacks and in the seasonal cycle of the surface ocean carbonate system due to ocean alkalinization. We find that both, carbon-concentration and carbon climate feedback, are enhanced due to the increased sensitivity of the carbonate system to changes in atmospheric CO2 and changes in temperature. While the temperature effect, which decreases ocean carbon uptake, remains small in our model, the carbon concentration feedback enhances the uptake of carbon due to alkalinization by more than 20%. The seasonal cycle of air-sea CO2 fluxes is strongly enhanced due to an increased buffer capacity in an alkalinized ocean. This is independent of the seasonal cycle of pCO2, which is only slightly enhanced. The most significant change in the seasonality of the surface ocean carbonate system is an increased seasonal cycle of the aragonite saturation state, which has the potential to adversely affect ecosystem health.
    Type: Report , NonPeerReviewed , info:eu-repo/semantics/book
    Format: text
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OCEANREP)
  • 3
    facet.materialart.
    Unknown
    Assessing the availability of trace metals and rare earth elements in deep ocean waters of the Clarion-Clipperton Zone, NE Pacific: Application of an in situ DGT passive sampling method (2022)
    Elsevier
    Details
    Publication Date: 2024-07-01
    Description: Highlights • First successful in situ DGT application in the deep ocean. • DGT-lability of dissolved (〈0.2 μm) Cu, Ni, Cd, Mn, As, V, REY differs depending on chemical speciation. • REY in deep ocean water can be almost quantitatively assessed with DGT. • Low Cu availability reflects dominating organic speciation. Abstract Geochemical behaviour and bio-availability of trace metals are closely related to their physical fractionation and chemical speciation. The DGT speciation technique allows the challenging assessment of labile concentrations of Mn, Cd, Cu, Ni, V, As, and REY in ocean waters. In this first deep-water in situ study of DGT-lability, we demonstrate the approach in bottom waters of the Clarion-Clipperton Zone in the central NE Pacific. In the dissolved fraction (〈0.2 μm), 70% to 100% of Cd, Ni, V, and REY, but only 25% of Cu and less than 50% of As were determined, reflecting their prevailing dominance of organic vs. inorganic complexation. This study demonstrates the applicability and sensitivity of DGT-passive samplers for trace metals as a suitable technique in monitoring of anthropogenic activities, such as deep seabed mining, as well as for natural process studies in abyssal environments.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Format: text
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OCEANREP)
  • 4
    facet.materialart.
    Unknown
    Physical oceanography measured with Underway-CTD (UCTD) during Akademik Tryoshnikov cruise Arctic Century 2021 Expedition (AT21), Arctic Ocean (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-30
    Description: Underway-CTD (UCTD) data were collected during an August-September 2021 expedition to the Arctic Ocean aboard the RV Akademik Tryoshnikov. The underway CTD manufactured by Ocean Science is a self-contained free-falling probe measuring temperature, conductivity, depth while the ship is transiting. The UCTD was operated mostly in yoyo-mode during selected transects on the shelf of the Kara and Laptev Seas and between the shelf and the basin across the continental slope of the Eurasian Basin while the ship was transiting with 4 - 10 knots. The UCTD probe records the start time of the measurements and stores 16 samples each second internally. The exact location of each profile was subsequently found based on the time stamp from the cruise track. The unpumped conductivity sensor has a slower response time than the temperature sensor, which makes the computation of salinity from conductivity and temperature potentially spiky, especially in the pycnocline or in frontal regions. We followed the recommendation of the manufacturer to calculate salinity with Seabird processing software. The salinity is given as Practical Salinity (PSU). The raw data profiles are provided as well and can be reprocessed if desired. In shallower waters (〈300 m), the water column was profiled all the way to the seafloor, while in deeper waters, only the upper 300-600 m were sampled. The UCTD was calibrated against a Seabird 9+ CTD during the cruise. The upper 5 m of the data were discarded due to the influence of the ship. The icebreaker Akademik Tyoshnikov has a deep draft. Mixing of the water column caused by the ship can reach depths of up to about 10 m, depending on the weather conditions and the ship's speed. The data are provided by the Arctic Century Expedition, a joint initiative led by the Swiss Polar Institute (SPI), the Antarctic and Arctic Research Institute (AARI) and GEOMAR Helmholtz Centre for Ocean Research Kiel (GEOMAR) and funded by the Swiss Polar Foundation, AARI, Minobrnauki (CATS RFMEFI61619X0108) and BMBF (CATS 03F0831)
    Keywords: Akademik Tryoshnikov; ArcticCentury; Arctic Century Expedition; Arctic Ocean; AT21; AT21_015-A; AT21_016-A; AT21_016-B; AT21_017-A; AT21_017-B; AT21_020-A; AT21_025-A; AT21_025-B; AT21_025-C; AT21_025-D; AT21_026-A; AT21_027-A; AT21_028-A; AT21_029-A; AT21_030-A; AT21_037-A; AT21_042; AT21_044; AT21_046; AT21_048; AT21_052; AT21_054; AT21_070-A; AT21_070-B; AT21_070-C; AT21_070-D; AT21_070-E; AT21_070-F; AT21_079-C; AT21_079-D; AT21_079-E; AT21_079-F; AT21_079-G; AT21_079-H; AT21_079-I; AT21_079-J; AT21_079-K; AT21_079-L; AT21_079-M; AT21_079-N; AT21_079-O; AT21_079-P; AT21_079-Q; AT21_079-R; AT21_079-S; AT21_079-T; AT21_079-U; AT21_081; AT21_082; AT21_083; AT21_084; AT21_085; AT21_086; AT21_087; AT21_088; AT21_090; AT21_091; AT21_094; AT21_095; AT21_099; AT21_100; AT21_101; AT21_102; AT21_105; AT21_115; AT21_118; AT21_120; AT21_121; AT21_123; AT21_124; Barents Sea; CATS; CATS - The Changing Arctic Transpolar System; Conductivity; CTD, underway; CTD-UW; Date/Time of event; DEPTH, water; Elevation of event; Event label; Kara Sea; Laptev Sea; Latitude of event; Longitude of event; Pressure, water; Salinity; Station label; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 103960 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 5
    facet.materialart.
    Unknown
    Nutrients, oxygen, total alkalinity, pH, and physical oceanography measured on water bottle samples during Akademik Tryoshnikov cruise Arctic Century 2021 Expedition (AT21), Arctic Ocean (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-30
    Description: A standard CTD system from Sea-Bird Electronics Inc SBE911+ with duplicate temperature and conductivity sensors was used to measure temperature, conductivity and pressure at 81 stations during an expedition to the Kara and Laptev Seas and the adjacent Arctic Ocean in August-September 2021 aboard the research vessel Akademik Tryoshnikov. We followed the recommendation of the manufacturer to calculate salinity with Seabird processing software. The salinity is given as Practical Salinity (PSU). The accuracy of the conductivity sensors was verified by measurements on water samples with a salinometer. The data set published here includes only the data from the first conductivity (SN 3290) and temperature (SN 4127) sensors. Only at station 26 the data of the second sensor pair (SN 2618/Cond, SN 5115/Temp) were used. The CTD was connected to a SBE32 Carousel Water Sampler with 24 12-liter bottles. Additionally, a Benthos Altimeter and a Wetlabs ECO-AFL Fluorometer were connected to the SBE911+ system. At 69 stations, 846 seawater samples were collected for analysis of dissolved inorganic nutrients (nitrate, nitrite, phosphate, ammonium, silicate), oxygen, total alkalinity, and pH. Dissolved inorganic nutrients were analyzed using a segmented flow analyzer from Seal Analytical. Ammonium was measured manually (colorimetric method) using a spectrophotometer (Shimadzu UV-1800). Dissolved oxygen was determined by the standard Winkler titration method using a Metrohm 916 TiTouch automatic titrator and a handheld titrator (BRAND). pH and total alkalinity were measured by potentiometric titration using an automatic titrator (Metrohm 916 TiTouch). The data are provided by the Arctic Century Expedition, a joint initiative led by the Swiss Polar Institute (SPI), the Antarctic and Arctic Research Institute (AARI) and GEOMAR Helmholtz Centre for Ocean Research Kiel (GEOMAR) and funded by the Swiss Polar Foundation, AARI, Minobrnauki (CATS RFMEFI61619X0108) and BMBF (CATS 03F0831).
    Keywords: Akademik Tryoshnikov; Alkalinity, total; Ammonium; ArcticCentury; Arctic Century Expedition; Arctic Ocean; AT21; AT21_001-5; AT21_002-1; AT21_003-1; AT21_004-1; AT21_005-1; AT21_006-1; AT21_007-1; AT21_008-1; AT21_009-1; AT21_010-1; AT21_012-1; AT21_013-1; AT21_015-1; AT21_016-1; AT21_017-1; AT21_018-1; AT21_019-1; AT21_020-1; AT21_020-5; AT21_022-1; AT21_023-1; AT21_024-1; AT21_026-1; AT21_027-1; AT21_028-1; AT21_029-1; AT21_030-1; AT21_031-1; AT21_032-1; AT21_034-1; AT21_035-1; AT21_036-1; AT21_037-1; AT21_038-1; AT21_039-1; AT21_040-1; AT21_040-6; AT21_041-1; AT21_043-1; AT21_045-1; AT21_047-1; AT21_049-1; AT21_050-1; AT21_051-1; AT21_053-1; AT21_055-1; AT21_057-1; AT21_058-1; AT21_059-1; AT21_060-1; AT21_061-1; AT21_062-1; AT21_064-1; AT21_065-1; AT21_066-1; AT21_067-1; AT21_068-1; AT21_069-1; AT21_070-1; AT21_071-1; AT21_072-1; AT21_073-1; AT21_075-1; AT21_089-1; AT21_093-1; AT21_097-1; AT21_098-1; AT21_104-1; AT21_106-1; AT21_107-1; AT21_108-1; AT21_109-1; AT21_110-1; AT21_111-1; AT21_112-1; AT21_113-1; AT21_114-1; AT21_117-1; AT21_119-1; AT21_122-1; AT21_125-1; Barents Sea; Bottle number; Calculated; CATS; CATS - The Changing Arctic Transpolar System; Conductivity; CTD, Sea-Bird SBE 911plus; CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Elevation of event; Event label; Fluorescence, chlorophyll; Fluorometer, WET Labs ECO AFL/FL; Kara Sea; Laptev Sea; Latitude of event; Longitude of event; Nitrate; Nitrite; nutrients; Oxygen, dissolved; pH; Phosphate; physical oceanography; Potentiometric titration, Metrohm 916 TiTouch; Pressure, water; Salinity; Sample code/label; Segmented flow analyzer, Seal Analytical; shelf-basin transects; Silicate; Spectrophotometer Shimadzu UV-1800; St. Anna Trough; Station label; Temperature, water; Titration, Winkler
    Type: Dataset
    Format: text/tab-separated-values, 21531 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 6
    facet.materialart.
    Unknown
    Physical oceanography (CTD/Rosette) during Akademik Tryoshnikov cruise Arctic Century 2021 Expedition (AT21), Arctic Ocean (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-30
    Description: A standard CTD system from Sea-Bird Electronics Inc SBE911+ with duplicate temperature and conductivity sensors was used to measure temperature, conductivity and pressure at 86 stations during an expedition to the Kara and Laptev Seas and the adjacent Arctic Ocean in August-September 2021 aboard the research vessel “Akademik Tryoshnikov”. We followed the manufacturer's recommendation to calculate salinity with Seabird processing software. The salinity is given as Practical Salinity (PSU). Data were averaged in depth bins of 1 m. The processed, but not bin-averaged, cnv-files from each station are also part of this publication (zip file). The accuracy of the conductivity sensors was verified by measurements on water samples with a salinometer. The data set published here includes only the data from the first conductivity (SN 3290) and temperature (SN 4127) sensors. Only at station 26 the data of the second sensor pair (SN 2618/Cond, SN 5115/Temp) were used. The CTD was connected to an SBE32 carousel water sampler with 24 12-liter bottles. Additionally, a Wetlabs ECO-AFL Fluorometer was connected to the SBE911+ system. The data are provided by the Arctic Century Expedition, a joint initiative led by the Swiss Polar Institute (SPI), the Antarctic and Arctic Research Institute (AARI) and GEOMAR Helmholtz Centre for Ocean Research Kiel (GEOMAR) and funded by the Swiss Polar Foundation, AARI, Minobrnauki (CATS RFMEFI61619X0108) and BMBF (CATS 03F0831).
    Keywords: Akademik Tryoshnikov; ArcticCentury; Arctic Century Expedition; Arctic Ocean; AT21; AT21_001-1; AT21_001-5; AT21_002-1; AT21_003-1; AT21_004-1; AT21_005-1; AT21_006-1; AT21_007-1; AT21_008-1; AT21_009-1; AT21_010-1; AT21_011-1; AT21_012-1; AT21_013-1; AT21_015-1; AT21_016-1; AT21_017-1; AT21_018-1; AT21_019-1; AT21_020-1; AT21_020-5; AT21_021-1; AT21_022-1; AT21_023-1; AT21_024-1; AT21_026-1; AT21_027-1; AT21_028-1; AT21_029-1; AT21_030-1; AT21_031-1; AT21_032-1; AT21_034-1; AT21_035-1; AT21_036-1; AT21_037-1; AT21_038-1; AT21_039-1; AT21_040-1; AT21_040-6; AT21_041-1; AT21_043-1; AT21_045-1; AT21_047-1; AT21_049-1; AT21_050-1; AT21_051-1; AT21_053-1; AT21_055-1; AT21_056-1; AT21_057-1; AT21_058-1; AT21_059-1; AT21_060-1; AT21_061-1; AT21_062-1; AT21_064-1; AT21_065-1; AT21_066-1; AT21_067-1; AT21_068-1; AT21_069-1; AT21_070-1; AT21_071-1; AT21_072-1; AT21_073-1; AT21_075-1; AT21_089-1; AT21_093-1; AT21_096-1; AT21_097-1; AT21_098-1; AT21_104-1; AT21_106-1; AT21_107-1; AT21_108-1; AT21_109-1; AT21_110-1; AT21_111-1; AT21_112-1; AT21_113-1; AT21_114-1; AT21_117-1; AT21_119-1; AT21_122-1; AT21_125-1; Barents Sea; Calculated; CATS; CATS - The Changing Arctic Transpolar System; Conductivity; CTD, Sea-Bird, SBE 911plus; CTD/Rosette; CTD-RO; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Elevation of event; Event label; Fluorescence, chlorophyll; Fluorometer, WET Labs ECO AFL/FL; Kara Sea; Laptev Sea; Latitude of event; Longitude of event; Pressure, water; Salinity; shelf-basin transects; St. Anna Trough; Station label; Temperature, water; Temperature, water, potential
    Type: Dataset
    Format: text/tab-separated-values, 336264 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 7
    facet.materialart.
    Unknown
    Mitochondrial Cytochrome Oxidase Subunit 1: A Promising Molecular Marker for Species Identification in Foraminifera (2022)
    Frontiers Media SA
    In:  Frontiers in Marine Science vol. 9 no. 809659
    Details
    Publication Date: 2024-06-30
    Description: Traditional morphological methods for species identification are highly time consuming, especially for small organisms, such as Foraminifera, a group of shell-building microbial eukaryotes. To analyze large amounts of samples more efficiently, species identification methods have extended to molecular tools in the last few decades. Although a wide range of phyla have good markers available, for Foraminifera only one hypervariable marker from the ribosomal region (18S) is widely used. Recently a new mitochondrial marker cytochrome oxidase subunit 1 (COI) has been sequenced. Here we investigate whether this marker has a higher potential for species identification compared to the ribosomal marker. We explore the genetic variability of both the 18S and COI markers in 22 benthic foraminiferal morphospecies (orders Miliolida and Rotaliida). Using single-cell DNA, the genetic variability within specimens (intra) and between specimens (inter) of each species was assessed using next-generation sequencing. Amplification success rate was twice as high for COI (151/200 specimens) than for 18S (73/200 specimens). The COI marker showed greatly decreased intra- and inter-specimen variability compared to 18S in six out of seven selected species. The 18S phylogenetic reconstruction fails to adequately cluster multiple species together in contrast to COI. Additionally, the COI marker helped recognize misclassified specimens difficult to morphologically identify to the species level. Integrative taxonomy, combining morphological and molecular characteristics, provides a robust picture of the foraminiferal species diversity. Finally, we suggest the use of a set of sequences (two or more) to describe species showing intra-genomic variability additionally to using multiple markers. Our findings highlight the potential of the newly discovered mitochondrial marker for molecular species identification and metabarcoding purposes.
    Keywords: protist ; high-throughput sequencing ; metabarcoding ; intra-genomic variation ; benthic foraminifera
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OA)
  • 8
    facet.materialart.
    Unknown
    Amino acids and hexosamine in sediment trap samples from different oceanic areas collected between 1993 and 2017 from shelf seas to the deep ocean (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-29
    Description: This large set of sediment trap samples was collected in different oceanic areas between 1993 and 2017 from shelf seas to the deep ocean. The samples were compiled from previous studies and used for statistical analyses in order to better understand particle dynamics and organic matter cycling in the ocean and to test and refine amino acid (AA) and hexosamine (HA) based biogeochemical indicators. Samples were analysed for total nitrogen (N) using a Carlo Erba nitrogen analyser 1500. Total organic carbon (TOC) was measured with the same instrument after treatment of weighed samples with 1N HCl to remove carbonate. Stable nitrogen isotopes of total particulate nitrogen (δ15N-TPN) were analysed with the mass spectrometer ThermoFisher Scientific MAT 252. AA and HA contents and their individual monomers were analysed by liquid chromatography using a Biochrom 30 amino acid analyzer. Total fluxes, TOC and AA fluxes were calculated in mg m-2 d-1. Contents of AA and HA are presented in µmol/g and µg/g. AAC, AAN, HAC, HAN are presented in µg/g and as percentages of TOC (AA-C/C, HA-C/C) or TN (AA-N/N, HA-N/N). AA and HA monomers are presented in Mol% and comprise aspartic acid (ASP), glutamic acid (Glu), threonine (Thr), serine (Ser), glycine (Gly), alanine (Ala), valine (Val), methionine (Met), isoleucine (Ile), leucine (Leu), tyrosine (Tyr), phenylalanine (Phe), β-Alanine (β-Ala), γ-aminobutyric acid (γ-Aba), histidine (His), ornithine (Orn), lysine (Lys) and arginine (Arg), glucosamine (GlcN) and galactosamine (GalN), cysteic acid (CYA), taurine (TAU), methionine sulfoximine (MSO) and tryptophane (TRP) were determined only in the more recent samples. Data gaps indicate that measurements were not carried out or that they were not stored in the older data sets. The RI was calculated according to Jennerjahn and Ittekkot (1997; https://archimer.ifremer.fr/doc/00093/20403/) and the DI after Dauwe et al. (1999; doi:10.4319/lo.1999.44.7.1809). Definitions of biogeochemical indicators SDI, RTI, ox/anox and a detailed description of the methods can be found in Gaye et al. (2022; doi:org/10.5194/bg-19-807-2022).
    Keywords: Akademik Boris Petrov; Alanine; Amino acid, carbon; Amino acid, carbon of total organic carbon; Amino acid, flux; Amino acid, nitrogen; Amino acid analyser, Biochrom 30; Amino acid nitrogen of total nitrogen; amino acids; Amino acids; Amino acids/hexosamines ratio; Amino acids non-protein; Amino sugar, carbon; Amino sugar, carbon of total organic carbon; Amino sugar, nitrogen; Amino sugar, nitrogen of total nitrogen; Arabian Sea; Arginine; Aspartic acid; Aspartic acid/beta-Alanine ratio; beta-Alanine; BP00; BP00-24a-Yenisei_02; BP01; BP01-61a-Kara_02; BP02; BP02-04-Yenisei_04; BP99; BP99-01-Ob01; BP99-15-Yen01; Calculated after Dauwe et al. 1999; Calculated after Gaye et al. (2022); Calculated after Jennerjahn and Ittekkot (1997); Carbon, organic, flux; Carbon, organic, total; CAST; Central Arabian Sea Trap Station; Cysteic acid; DATE/TIME; Degradation index; degradation indicators; Deployment: BP00-24a; Recovery: BP01-02; Deployment: BP01-61a; Recovery: BP02-01A; Deployment: BP02-04; Recovery: BP03-04a; Deployment: BP99-01; Deployment: M44/1_7ST; Recovery: M44/4_ST244; Deployment: MSM17/3_223-2; Recovery: MSM17/3_258-2; DEPTH, water; EAST; Eastern Arabian Sea Trap Station; Eastern Basin; East Pakistan Trap Station; ENAT; EPT; Event label; Galactosamine; gamma-Aminobutyric acid; Gas chromatography with Carlo Erba NA1500 after treatment with HCL; Gas chromatography with Carlo Erba NA-1500 CNS elemental analyzer; Glucosamine; Glucosamine/Galactosamine ratio; Glutamic acid; Glutamic acid/gamma-Aminobutyric acid ratio; Glycine; hexosamines; Hexosamines; Histidine; INDEX2016_TRAP_01-01; INDEX2016_TRAP_03-01; Indian Ocean; Isoleucine; JAM-1; Kara Sea; Leucine; Location; Lysine; M44/1; M44/1_7-MID; Maria S. Merian; Mass spectrometer, ThermoFisher Scientific MAT 252; Meteor (1986); Methionine; Methionine sulfoximine; MOOR; Mooring; Mooring (long time); MOORY; MSM17/3; MSM17/3_222-M; MSM17/3_223-D; MSM59/2_Deployment_01-01,SO259_Recovery_01-01; MSM59/2_Deployment_03-01,SO259_Recovery_03-01; NAST; NEAST; Nitrogen, total; Northeastern Arabian Sea Trap Station; Northern Arabian Sea Trap Station; off south Java; organic matter degradability; Ornithine; Other event; Ox/Anox ratio; Phenylalanine; Reactivity index of amino acids (Jennerjahn & Ittekkot, 1997); Recovery: MSM17/3_222-4; Reference/source; Reference of data; Residence time index; Sample ID; SAST; Sediment degradation index; sediment trap samples; Serine; sinking particles; South Atlantic Ocean; Southern Arabian Sea Trap Station; Station label; Taurine; Threonine; Total mass, flux per day; Trap; TRAP; Trap, sediment; TRAPS; Tryptophan; Tyrosine; Valine; WAST; Western Arabian Sea Trap Station; West Pakistan Trap Station; WNAT; WPT; δ15N
    Type: Dataset
    Format: text/tab-separated-values, 11335 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 9
    facet.materialart.
    Unknown
    Amino acids and hexosamines in suspended matter samples collected in different oceanic areas between 1999 and 2017 from shelf seas to the deep ocean (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-29
    Description: This large set of suspended matter (SPM) samples was collected in different oceanic areas between 1999 and 2017 from shelf seas to the deep ocean. The samples were compiled from previous studies and used for statistical analyses in order to better understand particle dynamics and organic matter cycling in the ocean and to test and refine amino acid (AA) and hexosamine (HA) based biogeochemical indicators. Samples were analysed for total nitrogen (N) and total carbon (C) using a Carlo Erba nitrogen analyser 1500. Total organic carbon (TOC) was measured with the same instrument after treatment of weighed samples with 1N HCl to remove carbonate. Stable nitrogen isotopes of total particulate nitrogen (δ15N-TPN) were analysed with the mass spectrometer Thermo Finnigan MAT 252. AA and HA contents and their individual monomers were analysed by liquid chromatography using a Biochrom 30 amino acid analyzer. Contents of AA and HA are presented in nmol/g and µg/g. AAC, AAN, HAC, HAN are presented in µg/g and as percentages of TOC (AAC/C, HAC/C) or TN (AAN/N, HAN/N). AA and HA monomers are presented in Mol% and comprise aspartic acid (ASP), glutamic acid (Glu), threonine (Thr), serine (Ser), glycine (Gly), alanine (Ala), valine (Val), methionine (Met), isoleucine (Ile), leucine (Leu), tyrosine (Tyr), phenylalanine (Phe), β-Alanine (β-Ala), γ-aminobutyric acid (γ-Aba), histidine (His), ornithine (Orn), lysine (Lys) and arginine (Arg), glucosamine (Gluam) and galactosamine (Galam). Cysteic acid (CYA), taurine (TAU), methionine sulfoximine (MSO) and tryptophane (TRP) were determined only in the more recent samples. Data gaps indicate that measurements were not carried out or that they were not stored in the older data sets. The RI was calculated according to Jennerjahn and Ittekkot (1997; https://archimer.ifremer.fr/doc/00093/20403/) and the DI after Dauwe et al. (1999; doi:10.4319/lo.1999.44.7.1809). Definitions of biogeochemical indicators SDI, RTI, ox/anox and a detailed description of the methods can be found in Gaye et al. (2022).
    Keywords: Akademik Boris Petrov; Alanine; Amino acid, carbon; Amino acid, carbon of total organic carbon; Amino acid, nitrogen; Amino acid analyser, Biochrom 30; Amino acid nitrogen of total nitrogen; amino acids; Amino acids; Amino acids/hexosamines ratio; Amino acids non-protein; Amino sugar, carbon; Amino sugar, carbon of total organic carbon; Amino sugar, nitrogen; Amino sugar, nitrogen of total nitrogen; Arabian Sea; Arginine; Aspartic acid; Aspartic acid/beta-Alanine ratio; beta-Alanine; BP00; BP00-02; BP00-03; BP00-04; BP00-05; BP00-06; BP00-07; BP00-08; BP00-09; BP00-13; BP00-15; BP00-16; BP00-17; BP00-19; BP00-20; BP00-21; BP00-22; BP00-23; BP00-24; BP00-26; BP00-27; BP00-28; BP00-29; BP00-30; BP00-31; BP00-35; BP00-36; BP00-38; BP99; BP99-01; BP99-03; BP99-08; BP99-11; BP99-13; BP99-17; BP99-20; BP99-21; BP99-25; BP99-26; BP99-30; BP99-31; BP99-32; BP99-35; BP99-37; BP99-FEM; BP99-Ob-Salechard_1; BP99-Ob-Salechard_2; BP99-Soil; BUCKET; Bucket water sampling; Calculated after Dauwe et al. 1999; Calculated after Gaye et al. (2022); Calculated after Jennerjahn and Ittekkot (1997); Campaign of event; Carbon, organic, total; Carbon, total; CTD/Rosette; CTD-RO; Cysteic acid; Date/Time of event; Degradation index; degradation indicators; DEPTH, water; Dredge; DRG; Elevation of event; Event label; Galactosamine; gamma-Aminobutyric acid; Gas chromatography with Carlo Erba NA1500 after treatment with HCL; Gas chromatography with Carlo Erba NA-1500 CNS elemental analyzer; Glucosamine; Glucosamine/Galactosamine ratio; Glutamic acid; Glutamic acid/gamma-Aminobutyric acid ratio; Glycine; hexosamines; Hexosamines; Histidine; INDEX2016_2; INDEX2017; Indian Ocean; Isoleucine; Kara Sea; Latitude of event; Leucine; Location; Longitude of event; Lysine; M103/1; M103/1_10-2; M103/1_1-1; M103/1_11-2; M103/1_20-4; M103/1_2-2; M103/1_22-2; M103/1_2283-1; M103/1_2284-4; M103/1_2285-4; M103/1_2286-1; M103/1_2287-1; M103/1_2288-1; M103/1_2289-4; M103/1_2290-3; M103/1_2291-4; M103/1_28-5; M103/1_30-4; M103/1_3-1; M103/1_34-1; M103/1_4-1; M103/1_43-1; M103/1_44-2; M103/1_45-2; M103/1_46-2; M103/1_47-2; M103/1_48-5; M103/1_5-1; M103/1_53-1; M103/1_59-1; M103/1_6-2; M103/1_65-1; M103/1_67-1; M103/1_7-2; M103/1_8-4; M103/1_9-1; M74/1b; M74/1b_944-1; M74/1b_945-1; M74/1b_946-3; M74/1b_947-1; M74/1b_948-1; M74/1b_949-1; M74/1b_950-3; M74/1b_951-3; M74/1b_953-3; M74/1b_954-1; M74/1b_955-1; M74/1b_956-3; M74/1b_957-4; M74/1b_958-1; M76/2; M76/2_195_WS; M76/2_198_WS; M76/2_200_WS; M76/2_201_WS; M76/2_202_WS; M76/2_204_WS; M76/2_206_WS; M76/2_252_WS; Maria S. Merian; Mass spectrometer, ThermoFisher Scientific MAT 252; Meteor (1986); Methionine; Methionine sulfoximine; MSM59/2; MSM59/2_734-2; MSM59/2_734-3; MSM59/2_739-1; MSM59/2_739-2; MSM59/2_749-1; MSM59/2_749-2; MSM59/2_751-1; MSM59/2_769-1; MSM59/2_769-2; MSM59/2_783-1; MSM59/2_783-2; MULT; Multiple investigations; Namibia upwelling, Southeast Atlantic; Nitrogen, total; organic matter cycling; organic matter degradation; Ornithine; Ox/Anox ratio; Phenylalanine; Reactivity index of amino acids (Jennerjahn & Ittekkot, 1997); Residence time index; Sample ID; Sediment degradation index; Serine; SO259; SO259_100-1; SO259_1-1; SO259_15-1; SO259_16-1; SO259_2-1; SO259_3-1; SO259_4-1; SO259_49-1; SO259_50-1; SO259_5-1; SO259_60-1; SO259_6-1; SO259_61-1; SO259_99-1; Sonne_2; Suspended particulate matter; Taurine; Threonine; Tryptophan; Tyrosine; Valine; Water sample; WS; δ15N, total particulate nitrogen
    Type: Dataset
    Format: text/tab-separated-values, 30425 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
  • 10
    facet.materialart.
    Unknown
    Amino acids and hexosamines in water and pore water samples from different oceanic areas sampled between 2013 and 2016 (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-29
    Description: These water and pore water samples were collected in different oceanic areas between 2013 and 2016. The samples were compiled from previous studies and used for statistical analyses in order to better understand particle dynamics and organic matter cycling in the ocean and to test and refine amino acid (AA) and hexosamine (HA) based biogeochemical indicators. Dissolved organic carbon (DOC) concentrations and total dissolved nitrogen (TDN) concentrations were determined with a POC-VCSH analyzer (Shimadzu) after removal of inorganic carbon by 2M HCl. Stable nitrogen and oxygen isotopes of nitrate (δ15N-NO3, δ18O-NO3) were analysed by the denitrifier method with a Delta Plus XP mass spectrometer. AA and HA contents and their individual monomers were analysed by liquid chromatography using a Biochrom 30 amino acid analyser after acid hydrolysis of filtered sea or pore water. Contents of AA and HA are presented in µmol/L and µg/L. AAC, AAN, HAC, HAN are presented in µg/L and as percentages of DOC (AAC/C, HAC/C) or TDN (AAN/N, HAN/N). AA and HA monomers are presented in Mol% and comprise aspartic acid (ASP), glutamic acid (Glu), threonine (Thr), serine (Ser), glycine (Gly), alanine (Ala), valine (Val), methionine (Met), isoleucine (Ile), leucine (Leu), tyrosine (Tyr), phenylalanine (Phe), β-Alanine (β-Ala), γ-aminobutyric acid (γ-Aba), histidine (His), ornithine (Orn), lysine (Lys) and arginine (Arg), glucosamine (GlcN) and galactosamine (GalN). Cysteic acid (CYA), taurine (TAU), methionine sulfoximine (MSO) and tryptophane (TRP) were determined only in the more recent samples. Data gaps indicate that measurements were not carried out or that they were not stored in the older data sets. The RI was calculated according to Jennerjahn and Ittekkot (1997; https://archimer.ifremer.fr/doc/00093/20403/) and the DI after Dauwe et al. (1999; doi:10.4319/lo.1999.44.7.1809). Definitions of biogeochemical indicators SDI, RTI, ox/anox and a detailed description of the methods can be found in Gaye et al. (2022; doi:org/10.5194/bg-19-807-2022).
    Keywords: Alanine; Amino acid, carbon; Amino acid, carbon of total organic carbon; Amino acid, nitrogen; Amino acid analyser, Biochrom 30; Amino acid nitrogen of total nitrogen; amino acids; Amino acids; Amino acids/hexosamines ratio; Amino acids non-protein; Amino sugar, carbon; Amino sugar, carbon of total organic carbon; Amino sugar, nitrogen; Amino sugar, nitrogen of total nitrogen; Arginine; Aspartic acid; Aspartic acid/beta-Alanine ratio; beta-Alanine; biogeochemical indicators; Calculated after Dauwe et al. 1999; Calculated after Gaye et al. (2022); Calculated after Jennerjahn and Ittekkot (1997); Campaign of event; Carbon, organic, dissolved; Category; CTD/Rosette; CTD3; CTD4; CTD5; CTD-RO; Cysteic acid; Date/Time of event; Degradation index; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; DEPTH, water; Elevation of event; Event label; Galactosamine; gamma-Aminobutyric acid; GC; GC5; Glucosamine; Glucosamine/Galactosamine ratio; Glutamic acid; Glutamic acid/gamma-Aminobutyric acid ratio; Glycine; Gravity corer; hexosamines; Hexosamines; Histidine; INDEX2016_2; Indian Ocean; Isoleucine; JPI-OCEANS; Latitude of event; Leucine; Location; Longitude of event; Lysine; M103/1; M103/1_10-2; M103/1_14-5; M103/1_2291-1; M103/1_28-4; M103/1_48-5; Maria S. Merian; Mass spectrometer Finnigan Delta Plus XP; Meteor (1986); Methionine; Methionine sulfoximine; MSM59/2; MSM59/2_734-2; MSM59/2_734-3; MSM59/2_739-1; MSM59/2_739-2; MSM59/2_749-1; MSM59/2_749-2; MSM59/2_751-1; MSM59/2_769-1; MSM59/2_769-2; MSM59/2_783-1; MSM59/2_783-2; MUC; MultiCorer; Nitrogen, total dissolved; North Pacific Ocean; Ornithine; Ox/Anox ratio; Oxygen, dissolved; Phenylalanine; pore water samples; PUC; Push corer; Reactivity index of amino acids (Jennerjahn & Ittekkot, 1997); Reference of data; Remote operated vehicle; Residence time index; ROV; ROV12; Salinity; Sample ID; Sediment degradation index; Serine; Shimadzu TOC-V CSH total organic carbon analyzer; Size; SO239; SO239_10-1; SO239_110-1; SO239_118-1; SO239_161-1; SO239_165-1; SO239_167-1; SO239_25-1; SO239_26-1; SO242/1; SO242/1_108-1; SO242/1_108-1_MUC 26; SO242/1_56-1; SO242/1_56-1_MUC 12; SO242/1_58-1; SO242/1_58-1_CTD 4; SO242/1_80-1; SO242/1_80-1_MUC 22; SO242/2; SO242/2_166_PUC-28; SO242/2_216_PUC-65; Sonne_2; South Pacific Ocean, Peru Basin; Taurine; Temperature, water; Threonine; Tryptophan; Tyrosine; Valine; Water samples; δ15N, nitrate; δ18O, nitrate
    Type: Dataset
    Format: text/tab-separated-values, 4052 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    DATA PANGAEA
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...