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  • 1
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    PANGAEA
    In:  Supplement to: Raupach, Michael R; Malyutina, Marina; Brandt, Angelika; Wägele, Johann-Wolfgang (2007): Molecular data reveal a highly diverse species flock within the munnopsoid deep-sea isopod Betamorpha fusiformis (Barnard, 1920) (Crustacea: Isopoda: Asellota) in the Southern Ocean. Deep Sea Research Part II: Topical Studies in Oceanography, 54(16-17), 1820-1830, https://doi.org/10.1016/j.dsr2.2007.07.009
    Publication Date: 2024-06-09
    Description: Based on our current knowledge about population genetics, phylogeography and speciation, we begin to understand that the deep sea harbours more species than suggested in the past. Deep-sea soft-sediment environment in particular hosts a diverse and highly endemic invertebrate fauna. Very little is known about evolutionary processes that generate this remarkable species richness, the genetic variability and spatial distribution of deep-sea animals. In this study, phylogeographic patterns and the genetic variability among eight populations of the abundant and widespread deep-sea isopod morphospecies Betamorpha fusiformis [Barnard, K.H., 1920. Contributions to the crustacean fauna of South Africa. 6. Further additions to the list of marine isopods. Annals of the South African Museum 17, 319-438] were examined. A fragment of the mitochondrial 16S rRNA gene of 50 specimens and the complete nuclear 18S rRNA gene of 7 specimens were sequenced. The molecular data reveal high levels of genetic variability of both genes between populations, giving evidence for distinct monophyletic groups of haplotypes with average p-distances ranging from 0.0470 to 0.1440 (d-distances: 0.0592-0.2850) of the 16S rDNA, and 18S rDNA p-distances ranging between 0.0032 and 0.0174 (d-distances: 0.0033-0.0195). Intermediate values are absent. Our results show that widely distributed benthic deep-sea organisms of a homogeneous phenotype can be differentiated into genetically highly divergent populations. Sympatry of some genotypes indicates the existence of cryptic speciation. Flocks of closely related but genetically distinct species probably exist in other widespread benthic deep-sea asellotes and other Peracarida. Based on existing data we hypothesize that many widespread morphospecies are complexes of cryptic biological species (patchwork hypothesis).
    Keywords: Agassiz Trawl; AGT; ANT-XXII/3; Area/locality; Database accession number; Date/Time of event; EBS; Elevation of event; Elevation of event 2; Epibenthic sledge; Event label; Haplotype group; Individual code; Latitude of event; Latitude of event 2; Longitude of event; Longitude of event 2; Polarstern; PS67/016-10; PS67/021-7; PS67/074-6; PS67/080-9; PS67/094-11; PS67/102-13; PS67/110-8; PS67/121-10; PS67 ANDEEP 3; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 264 data points
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  • 2
    Publication Date: 2024-06-08
    Keywords: 02260100; 02281147; 03041555; 03071108; 03092330; 03112138; 03130720; 03181915; 03200715; 03281830; 09070100; 09080637; 09171830; 119-745B; AGE; Age, comment; Agulhas Basin; ANTA95-157; ANTA96-1; ANTA96-16; ANTA96-17; ANT-IV/3; ANT-IX/2; ANT-IX/4; ANT-V/4; ANT-VI/3; ANT-VIII/3; ANT-VIII/6; ANT-X/5; ANT-X/6; ANT-XI/4; ANT-XII/4; ANT-XVIII/5a; APSARA2; APSARA4; AT_II-107_71_26; AT_II-107_76_31; AT_II-107_78; AT_USA; Atka Bay; Atlantic Ridge; Atlantis (1931); Barents Sea; BC; Box corer; Burial rate of opal; Calcium carbonate; CALYPSO; Calypso Corer; Comment; Core; Core382; Cosmonauts Sea; cruise 11; CS13-2; CS13-3; CS13-6; CS13-8; CS15-2; CTD/Rosette; CTD-RO; Depth, bathymetric; DEPTH, sediment/rock; DF85; DF85.062-PC; DF85.072-PC; DF85.114-PC; DF85.119-PC; DF85.125-PC; DRILL; Drilling/drill rig; ELT05; ELT05.012-PC; ELT05.016-PC; ELT05.017-PC; ELT05.018-PC; ELT05.019-PC; ELT05.024-PC; ELT05.025-PC; ELT07; ELT07.001-PC; ELT07.007-PC; ELT07.008-PC; ELT07.009-PC; ELT07.010-PC; ELT07.011-PC; ELT07.012-PC; ELT07.013-PC; ELT07.014-PC; ELT07.015-PC; ELT07.017-PC; ELT08; ELT08.006-PC; ELT08.008-PC; ELT08.010-PC; ELT08.012-PC; ELT08.019-PC; ELT09; ELT09.013-PC; ELT09.015-TC; ELT09.016-PC; ELT10; ELT10.005-PC; ELT10.008-PC; ELT10.009-PC; ELT10.010-PC; ELT10.011-PC; ELT10.012-PC; ELT10.013-PC; ELT10.014-PC; ELT10.016-PC; ELT10.018-PC; ELT10.019-PC; ELT10.020-PC; ELT10.021-PC; ELT10.022-PC; ELT10.024-PC; ELT10.025-PC; ELT10.027-PC; ELT10.028-PC; ELT10.029-PC; ELT10.030-PC; ELT10.031-PC; ELT10.032-PC; ELT11; ELT11-001-PC; ELT11-002-PC; ELT11-003-PC; ELT11-004-PC; ELT11-006-PC; ELT11-007-PC; ELT11-008-PC; ELT11-010-PC; ELT11-012-PC; ELT11-015-PC; ELT11-018-PC; ELT11-020-PC; ELT11-021-PC; ELT11-022-PC; ELT11-023-PC; ELT11-025-TC; ELT11-026-PC; ELT11-029-PC; ELT11-031-PC; ELT11-035-PC; ELT13; ELT13.001-PC; ELT13.002-PC; ELT13.004-PC; ELT13.005-PC; ELT13.008-PC; ELT13.009-PC; ELT13.011-PC; ELT13.013-PC; ELT13.015-PC; ELT13.016-PC; ELT13.017-PC; ELT13.019-PC; ELT13.020-PC; ELT13.021-PC; ELT13.022-PC; ELT13.024-PC; ELT14; ELT14.003-PC; ELT14.004-PC; ELT14.005-PC; ELT14.006-PC; ELT14.008-PC; ELT14.010-PC; ELT14.011-PC; ELT14.012-PC; ELT14.013-PC; ELT14.015-PC; ELT14.016-PC; ELT14.017-PC; ELT15; ELT15.002-PC; ELT15.003-PC; ELT15.004-PC; ELT15.005-PC; ELT15.006-PC; ELT15.007-PC; ELT15.009-PC; ELT15.011-PC; ELT15.012-PC; ELT15.015-PC; ELT15.022-PC; ELT15.023-PC; ELT15.028-PC; ELT17; ELT17.005-PC; ELT17.007-PC; ELT17.009-PC; ELT17.011-PC; ELT17.013-PC; ELT17.014-PC; ELT17.015-PC; ELT17.016-PC; ELT17.017-PC; ELT17.018-PC; ELT17.020-PC; ELT17.021-PC; ELT17.022-PC; ELT17.023-PC; ELT17.026-PC; ELT17.028-PC; ELT17.029-PC; ELT17.030-PC; ELT17.032-PC; ELT17.033-PC; ELT18; ELT18.002-PC; ELT18.003-PC; ELT18.004-PC; ELT19; ELT19.001-PC; ELT19.004-PC; ELT19.005-PC; ELT19.006-PC; ELT19.007-PC; ELT19.008-PC; ELT19.014-PC; ELT19.015-PC; ELT19.024-PC; ELT19.026-PC; ELT19.027-PC; ELT20; ELT20.004-PC; ELT20.006-PC; ELT20.007-PC; ELT20.008-PC; ELT20.009-PC; ELT20.010-PC; ELT20.011-PC; ELT20.013-PC; ELT20.014-PC; ELT21; ELT21.016-PC; ELT21.018-PC; ELT21.020-PC; ELT21.021-PC; ELT21.023-PC; ELT22; ELT22.001-PC; ELT22.005-PC; ELT22.006-PC; ELT22.009-PC; ELT22.010-PC; ELT22.033-PC; ELT22.034-PC; ELT23; ELT23.001-PC; ELT23.004-PC; ELT23.005-PC; ELT23.006-PC; ELT23.008-PC; ELT23.009-PC; ELT23.010-PC; ELT23.011-PC; ELT23.012-PC; ELT23.013-PC; ELT23.014-PC; ELT23.016-PC; ELT23.017-PC; ELT23.018-PC; ELT23.019-PC; ELT25; ELT25.007-PC; ELT25.008-PC; ELT25.009-PC; ELT25.010-PC; ELT25.011-PC; ELT25.012-PC; ELT25.013-PC; ELT25.014-PC; ELT25.015-PC; ELT25.016-PC; ELT26; ELT26.001-PC; ELT27; ELT27.004-PC; ELT27.023-PC; ELT33; ELT33.002-PC; ELT33.004-PC; ELT33.005-PC; ELT33.006-PC; ELT33.007-PC; ELT33.010-PC; ELT33.012-PC; ELT33.014-PC; ELT33.015-PC; ELT33.017-PC; ELT33.018-PC; ELT33.019-PC; ELT33.022-PC; ELT37; ELT37.004-PC; ELT42; ELT42.004-PC; ELT42.005-PC; ELT42.007-PC; ELT42.008-PC; ELT42.009-PC; ELT42.010-PC; ELT42.011-PC; ELT42.012-PC; ELT43; ELT43.003-PC; ELT43.005-PC; ELT45; ELT45.024-PC; ELT45.027-PC; ELT45.029-PC; ELT45.032-PC; ELT45.063-PC; ELT45.064-PC; ELT45.071-PC; ELT45.074-PC; ELT45.079-PC; ELT48; ELT48.003-PC; ELT49; ELT49.006-PC; ELT49.007-PC; ELT49.008-PC; ELT49.019-PC; ELT49.029-PC; ELT50; ELT50.008-PC; ELT50.009-PC; Eltanin; Event label; Filchner Trough; GC; Giant box corer; GKG; Glacier; Gravity corer; Gravity corer (Kiel type); Halley Bay; Identification; Indian-Antarctic Ridge; Indian Ocean; IO0775; IO0775.046-PC; IO0775.047-PC; IO0775.048-PC; IO0775.050-PC; IO0775.051-PC; IO0775.052-PC; IO0775.053-PC; IO0775.054-PC; IO0775.055-PC; IO0775.057-PC; IO1176; IO1176.055-PC; IO1176.079-PC; IO1277; IO1277.010-PC; IO1578; IO1578.002-PC; IO1578.004-PC; IO1578.049-PC; IO1678; IO1678.018-PC; IO1678.019-PC; IO1678.020-PC; IO1678.021-PC; IO1678.022-PC; IO1678.023-PC; IO1678.024-PC; IO1678.025-PC; IO1678.026-PC; IO1678.027-PC; IO1678.028-PC; IO1678.029-PC; IO1678.030-PC; IO1678.032-PC; IO1678.033-PC; IO1678.034-PC; IO1678.035-PC; IO1678.036-PC; IO1678.096-PC; Islas Orcadas; Joides Resolution; Kapp Norvegia; KR87-02; KR87-07; KR88-04; KR88-08; KR88-10; KR88-15; KR88-24; KTP11; Latitude of event; Lazarev Sea; Leg119; Longitude of event; Lyddan Island; Marion Dufresne (1972); MD38; MD84-527; MD84-551; MD84-552; MD88-001; MD88-002; MD88-003; MD88-006; MD88-014; MD88-018; MD88-024; MD88-769; MD88-770; MD88-773; MD94-102; MD94-104; Meteor Rise; MIC; MiniCorer; MUC; MultiCorer; Nathaniel B. Palmer; NBP9604; NBP9604-02-2; NBP9604-03-2; NBP9604-07-1; NBP9802; NBP9802-01-4; NBP9802-02-5; NBP9802-03-9; NBP9802-04-2; NBP9802-05-12; NBP9802-06-3; NBP9802-07-4; NBP9802-08-1; NBP9802-09-2; NBP9802-10-5; NZ-80-G-10; NZ-80-G-11; NZ-80-G-12; NZ-80-G-13; NZ-80-G-6; NZ-80-G-7; Opal, biogenic silica; PC; Piston corer; Polarstern; PS08; PS08/365; PS08/366; PS10; PS10/699; PS10/711; PS10/719; PS10/818; PS12; PS12/248; PS12/302; PS12/305; PS12/310; PS12/312; PS12/319; PS12/374; PS12/380; PS12/382; PS12/458; PS12/490; PS12/536; PS1387-1; PS1388-1; PS1483-2; PS1487-1; PS1488-2; PS1507-2; PS1575-1; PS1591-2; PS1593-3; PS1595-2; PS1596-1; PS1599-1; PS16; PS16/267; PS16/271; PS16/278; PS16/284; PS16/294; PS16/306; PS16/311; PS16/321; PS16/334; PS16/342; PS16/345; PS16/351; PS16/362; PS16/534; PS1622-1; PS1625-1; PS1626-1; PS1635-2; PS1639-1; PS1648-1; PS1751-2; PS1752-5; PS1754-1; PS1754-2; PS1756-6; PS1759-1; PS1765-1; PS1768-1; PS1768-8; PS1772-6; PS1772-8; PS1775-5; PS1777-7; PS1778-1; PS1779-3; PS1782-6; PS18; PS18/048; PS18/055; PS18/058; PS18/059; PS18/063; PS18/065; PS18/067; PS18/075; PS18/080; PS18/081; PS18/082; PS18/084; PS18/086; PS18/088; PS18/092; PS18/094; PS18/096; PS18/100; PS18/238; PS18 06AQANTIX_2; PS1821-6; PS1954-1; PS1957-1; PS1960-1; PS1961-1; PS1963-1; PS1964-1; PS1965-1; PS1967-1; PS1969-1; PS1970-1; PS1971-1; PS1973-1; PS1974-1; PS1975-1; PS1977-1; PS1978-1; PS1979-1; PS1981-1; PS2082-1; PS22; PS22/690; PS22/712; PS22/721; PS22/747; PS22/751; PS22/758; PS22/769; PS22/773; PS22/776; PS22/786; PS22/797; PS22/802; PS22/803; PS22/804; PS22/805; PS22/810; PS22/812; PS22/816; PS22/818; PS22/830; PS22/833; PS22/835; PS22/838; PS22/841; PS22/852; PS22/872; PS22/876; PS22/879; PS22/886; PS22/891; PS22/899; PS22/902; PS22/908; PS22/911; PS22/917; PS22/941; PS22/947; PS22/973; PS22 06AQANTX_5; PS2254-1; PS2256-4; PS2257-1; PS2262-1; PS2269-5; PS2271-1; PS2273-2; PS2276-2; PS2278-5; PS2280-1; PS2288-1; PS2299-1; PS2304-2; PS2305-1; PS2306-1; PS2307-2; PS2312-1; PS2314-1; PS2318-1; PS2320-2; PS2331-1a; PS2334-1a; PS2336-1a; PS2339-1a; PS2342-1a; PS2353-2a; PS2361-1; PS2362-1; PS2363-1; PS2364-1; PS2365-2; PS2366-1; PS2367-1; PS2368-4; PS2369-4; PS2370-4; PS2371-1; PS2372-1; PS2376-1; PS2562-3; PS2575-4; PS2577-2; PS2578-3; PS2579-4; PS2589-2; PS2600-2; PS2602-3; PS2604-4; PS2611-3; PS2659-2; PS2661-4; PS2663-4; PS2664-4; PS2667-3; PS2684-1; PS2687-5; PS2688-4; PS2690-1; PS2691-1; PS2692-1; PS2696-4; PS2697-1; PS2699-5; PS2700-5; PS2703-2; PS2715-3; PS2716-2; PS30; PS30/038; PS30/111; PS30/113; PS30/114; PS30/
    Type: Dataset
    Format: text/tab-separated-values, 3469 data points
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  • 3
    Publication Date: 2024-06-08
    Description: These data comprise a grain character dataset (grain size, sorting and grain shape) from the topset, foreset, and bottomset deposits of four successive Miocene intrashelf clinothem sequences (m5.7, m5.4, m5.45 and m5.3). These clinothems have been mapped and described by various authors (e.g. Monteverde et al., 2008; Mountain et al., 2010; Miller et al., 2013), and were continuously cored and logged during IODP (International Ocean Discovery Program) Expedition 313 (Offshore New Jersey, USA). In total, 878 sediment samples were collected from the working half of three cores recovered during IODP Expedition 313, offshore New Jersey. The three cores, kept in cold storage at the University of Bremen, are from Sites M27, M28 and M29. The stratigraphic horizons targeted during this investigation were exclusively Miocene in age, corresponding to depths of 225 - 365 mcd (metres composite depth), 312 - 600 mcd, and 600 - 730 mcd in cores M27, M28 and M29 respectively. Collectively, a total of 560 m of core has been sampled. With reference to the seismic clinothem model presented in Miller et al. (2013), these stratigraphic depths correspond to the interval between major seismic sequence boundaries m5.7 - m5.2. Where no prominent grain size change was recorded in either the cumulative lithology presented in Miller et al. (2013) or core descriptions (Mountain et al., 2010), the strategy for sample collection was to remove 15 x 15 x 15 mm sediment slices, subsampled at ~ 500 mm intervals down-core. The sampling strategy was amended to target stratigraphic depths where grain size change was most prominent. At these intervals, highlighted by the broad patterns of down-core lithological and grain size change (Mountain et al., 2010; Browning et al., 2013; Miller et al., 2013), sampling density was increased to ~ 300 mm intervals. During the sampling process there was some deviation from this sampling configuration in order to avoid 1) horizons of cementation, (2) biscuiting disturbance, 3) key stratigraphic surfaces and 4) heavily sampled intervals. Due to the pervasive presence of biogenic material (including calcareous skeletal remains, shell fragments, and organic matter) sample pre-treatment was undertaken prior to grain character measurements, in order to remove these components. Sample pre-treatment comprised the careful manual disaggregation of the semi-lithified samples using an agate mortar and pestle (e.g., Sahu, 1964; Wilson and Pittman, 1977; Nelson, 1983; Frey and Payne, 1996; Ando et al., 2014). Hydrochloric acid (10% weight to volume) and hydrogen peroxide (30% weight to volume) were added to all samples, to ensure the removal of any calcareous and non-calcareous organic components, respectively (e.g., Battarbee, 1986; Battarbee et al., 2001; Gray et al., 2009) Grain character is defined as the grain size, sorting and grain shape (sphericity and roundness) of a sample. Grain character analysis was completed using a CamsizerXT (Retsch Technology), which is an optically based dynamic image analyser. The CamsizerXT is capable of measuring the grain-size range 1 µm - 8 mm (clay - gravel), with an accuracy of ± 1%. Grain-size fractions 〈 1 µm are lost during the process of analysis. The statistical analysis of all CamsizerXT results was completed using GRADISTAT computer software (Blott and Pye, 2001). The GRADISTAT software enables the rapid analysis of grain size statistics from multiple sediment samples and produces numerical, geometrically and logarithmically calculated values of the mean, mode, and sorting (more information on Page Two of data spreadsheet). Grain shape data were analysed using Microsoft Excel software. The data are presented in spreadsheet format. Each sample is given a 'Site' this refers to Sites M27, M28 and M29; for the site locations the user is asked to refer to the seismic clinothem model presented in Mountain et al. (2010) and Miller et al. (2013). Each sample is also given a core number and core section (e.g., 80-1) and a sample depth (given in meters composite depth; e.g., 225.55 mcd); the user is asked to refer to Mountain et al. (2010) and Browning et al. (2013) to see the sampled core numbers, sections and depths alongside sedimentary logs, completed by the Onshore Scientific Party of IODP Expedition 313. Each sample is given: i) a textural group and a sediment name; ii) an arithmetic, geometric and logarithmic value of the grain-size mean, standard deviation, skewness and kurtosis; iii) an arithmetic, geometric and logarithmic value of the sorting and iv) the percentage of each grain-size fraction present within a sample. On Page Two of the spreadsheet (entitled GRADISTAT Information); Tables One and Two outline the mathematical parameters and grain-size scale used by the GRADISTAT software (Blott and Pye, 2001) to calculate the grain character data. For more information the user is asked to refer to Blott and Pye (2001). A synthesis of the grain character results and interpretations have been published in two papers; Cosgrove et al. (2018) and Cosgrove et al. (2019). These papers document patterns of sediment dispersal and variations in grain size, sorting and grain shape, at a basin-scale (i.e. across successive clinothems) and within individual clinothem sequences (i.e. at an intra-clinothem scale). These data can be used to condition and validate process-based numerical forward models and have widespread applications in prediction of reservoir quality in both frontier and mature hydrocarbon basins.
    Keywords: 313-M0027A; 313-M0028A; 313-M0029A; CamsizerXT (Retsch Technology), statistical analysis GRADISTAT package (Blott and Pye, 2001); Character; Clinoform; Clinothem; Core; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Difference; Event label; Exp313; Grain Shape; Grain Size; Grain size, mean; Grain size description; Gravel; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; Kayd; Kurtosis; Kurtosis description; MAT-1A; MAT-2D; MAT-3A; Mode, grain size; New Jersey Shallow Shelf; Percentile 10; Percentile 50; Percentile 90; Ratio; Roundness; Sand; Section; Sediment type; Silt; Site; Size fraction 〈 0.002 mm, clay; Size fraction 0.004-0.002 mm, 8.0-9.0 phi, very fine silt; Size fraction 0.008-0.004 mm, 7.0-8.0 phi, fine silt; Size fraction 0.016-0.008 mm, 6.0-7.0 phi, medium silt; Size fraction 0.032-0.016 mm, 5.0-6.0 phi, coarse silt; Size fraction 0.063-0.032 mm, 4.0-5.0 phi, very coarse silt; Size fraction 0.125-0.063 mm, 3.0-4.0 phi, very fine sand; Size fraction 0.250-0.125 mm, 2.0-3.0 phi, fine sand; Size fraction 0.500-0.250 mm, 1.0-2.0 phi, medium sand; Size fraction 1.000-0.500 mm, 0.0-1.0 phi, coarse sand; Size fraction 16-8 mm, medium gravel; Size fraction 2.000-1.000 mm, (-1.0)-0.0 phi, very coarse sand; Size fraction 32-16 mm, coarse gravel, pebble; Size fraction 4.0-2.0 mm, very fine gravel, granule; Size fraction 64-32 mm, very coarse gravel, pebble; Size fraction 8.0-4.0 mm, fine gravel; Skewness; Skewness description; Sorting; Sorting description; Sphericity; Texture
    Type: Dataset
    Format: text/tab-separated-values, 62945 data points
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  • 4
    Publication Date: 2024-06-08
    Keywords: 303-U1304; Age model; Age model, biostratigraphy; Ageprofile Datum Description; COMPCORE; Composite Core; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; DSDP/ODP/IODP sample designation; Exp303; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; Joides Resolution; North Atlantic; North Atlantic Climate 1; Sample code/label; Sample code/label 2
    Type: Dataset
    Format: text/tab-separated-values, 24 data points
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  • 5
    Publication Date: 2024-06-08
    Keywords: AGE; Carbon, inorganic, total; Carbon, organic, total; Carbon, organic, total/Nitrogen, total ratio; DEPTH, sediment/rock; Lake Nam Co, Tibetan Plateau; NC_08/01; Nitrogen, total; PC; Piston corer; Sulfur, total
    Type: Dataset
    Format: text/tab-separated-values, 3443 data points
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  • 6
    Publication Date: 2024-06-08
    Keywords: AGE; DEPTH, sediment/rock; Lake Nam Co, Tibetan Plateau; NC_08/01; PC; Piston corer; Sedimentation rate per year
    Type: Dataset
    Format: text/tab-separated-values, 2082 data points
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  • 7
    Publication Date: 2024-06-08
    Keywords: AGE; DEPTH, sediment/rock; Grain size, mean; Lake Nam Co, Tibetan Plateau; NC_08/01; PC; Piston corer; Sand; Silt; Size fraction 〈 0.002 mm, clay
    Type: Dataset
    Format: text/tab-separated-values, 4112 data points
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  • 8
    Publication Date: 2024-06-08
    Keywords: AGE; Aluminium (peak area); Barium (peak area); Calcium (peak area); DEPTH, sediment/rock; Iron (peak area); Lake Nam Co, Tibetan Plateau; NC_08/01; Normalized by the cumulative counts per second [pa/kcps]; PC; Piston corer; Potassium (peak area); Principal component 1; Rubidium (peak area); Silicon (peak area); Strontium (peak area); Titanium (peak area)
    Type: Dataset
    Format: text/tab-separated-values, 50728 data points
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  • 9
    Publication Date: 2024-06-08
    Keywords: AGE; ChRM, Declination; ChRM, Inclination; GC; Gravity corer; TAN10-4; TangraYumco10-4; Tibetan Plateau
    Type: Dataset
    Format: text/tab-separated-values, 240 data points
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  • 10
    Publication Date: 2024-06-08
    Keywords: AGE; ChRM, Declination; ChRM, Inclination; GC; Gravity corer; TAN10-1; TangraYumco10-1; Tibetan Plateau
    Type: Dataset
    Format: text/tab-separated-values, 298 data points
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