940 resultados para Orcadian Basin


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Empirical relationships between physical properties determined non-destructively by core logging devices and calibrated by carbonate and opal measurements determined on discrete samples allow extraction of carbonate and opal records from the non-destructive measurements in biogenic settings. Contents of detrital material can be calculated as a residual. For carbonate and opal the correlation coefficients (r) are 0.954 and ?0.916 for sediment density, ?0.816 and 0.845 for compressional-wave velocity, 0.908 and ?0.942 for acoustic impedance, and 0.886 and ?0.865 for sediment color (lightness). Carbonate contents increase in concert with increasing density and acoustic impedance, decreasing velocity and lighter sediment color. The opposite is true for opal. The advantages of deriving the sediment composition quantitatively from core logging are: (i) sampling resolution is increased significantly, (ii) non-destructive data can be gathered rapidly, and (iii) laboratory work on discrete samples can be reduced. Applied to paleoceanographic problems, this method offers the opportunity of precise stratigraphic correlations and of studying processes related to biogenic sedimentation in more detail. Density is most promising because it is most strongly affected by changes in composition.

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Polybrominated diphenyl ethers (PBDEs) are considered persistent organic pollutants because of their ubiquity, persistence and bioaccumulation. Its harmful effects on human health and the environment, has led to its inclusion of the Stockholm Convention. Little information is found about PBDEs in abiotic systems of the South America in open literature. This paper reports the presence and concentration level of four PBDEs congeners in Mendoza River, Argentina. The selected PBDEs were: 2,2',4,4'-tetrabromodiphenyl ether (BDE-47), 2,2',4,4',5-pentabromodiphenyl ether (BDE-99), 2,2',4,4',6-pentabromodiphenyl ether (BDE- 100) and 2,2',4,4',5,5'-hexabromodiphenyl ether (BDE-153). The analytical methodology used was head space-solid phase micro extraction combined with gas chromatographymass spectrometry (HS-SPME-GC-MS/MS). Several variables, including pH, salting out, extraction technique type and extraction time were studied and optimized over the relative response the target analytes. The precision of HS-SPME-GC-MS/MS evaluated over five replicate, leading RSDs values <13%, detection limits (S/N=3) ranging from 0.03 pg ml-1 to 0.12 pg ml-1 and the calibration graph was linear with r2=0.9959. BDE-47 and BDE-100 were the predominant congeners found in the analyzed samples. Their concentrations ranged from not detected to 1.9 pg ml-1 and to 0.5 pg ml-1, respectively.

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The Sesame dataset contains mesozooplankton data collected during April 2008 in the Levantine Basin (between 33.20 and 36.50 N latitude and between 30.99 and 31.008 E longitude). Mesozooplankton samples were collected by using a WP-2 closing net with 200 µm mesh size during day hours (07:00-18:00). Samples were taken from 0-50, 50-100, 100-200 m layers at 5 stations in Levantine Basin The dataset includes samples analyzed for mesozooplankton species composition, abundance and total mesozooplankton biomass. Sampling volume was estimated by multiplying the mouth area with the wire length. Sampling biomass was measured by weighing filters and then determined by sampling volume. The samples were sieved sequentially through meshes of 500 and 200 micron to separate the mesozooplankton into size fractions. The entire sample (1/2) or an aliquot of the taxon-specific mesozooplankton abundance and the total abundance of the mesozooplankton were was analyzed under the binocular microscope. Minimum 500 individuals of mesozooplankton were identified and numerated at higher taxonomic level. Taxonomic identification was done at the METU- Institute of Marine Sciences by Alexandra Gubanova,Tuba Terbiyik using the relevant taxonomic literatures. Mesozooplankton abundance and biomass were estimated by Zahit Uysal and Yesim Ak.

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The Sesame dataset contains mesozooplankton data collected during October 2008 in the Levantine Basin (between 33.20 and 36.50 N latitude and between 30.99 and 31.008 E longitude). Mesozooplankton samples were collected by using a WP-2 closing net with 200 µm mesh size during day hours (07:00-18:00). Samples were taken from 0-50, 50-100, 100-200 m layer at 5 stations in Levantine Basin The dataset includes samples analyzed for mesozooplankton species composition, abundance and total mesozooplankton biomass. The entire sample (1/2) or an aliquot was analyzed under the binocular microscope. Minimum 500 individuals of mesozooplankton were identified and numerated at higher taxonomic level. Taxonomic identification was done at the METU- Institute of Marine Sciences by Alexandra Gubanova,Tuba Terbiyik using the relevant taxonomic literatures. Mesozooplankton abundance and biomass were estimated by Zahit Uysal and Yesim Ak Örek. Specification via marine planktonic copepods database (http://copepodes.obs-banyuls.fr/en/).

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The Sesame dataset contains mesozooplankton data collected during March 2008 in the Cilician Basin (between between 35.40'- 36.79 N latitude and 33.19- 36.07 E ). Mesozooplankton samples were collected by using a WP-2 closing net with 200 micron mesh size during day hours (07:00-18:00). Samples were taken in the 0-50, 50-100, 100-200 m layer at 6 stations in the Cilician Basin. The dataset includes samples analyzed for mesozooplankton species composition, abundance and total biomass (Dry weight(mg/m**3)). Taxon-specific mesozooplankton abundance: 1/2 sample or an aliquot was analyzed under the binocular microscope. Copepod species were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Taxonomic identification was done at the METU-Institute of Marine Sciences by Tuba Terbiyik using the relevant taxonomic literatures. Mesozooplankton total abundance: 1/2 sample or an aliquot was analyzed under the binocular microscope. Copepod species were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Taxonomic identification was done at the METU-Institute of Marine Sciences using the relevant taxonomic literatures

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Soft-sediment deformation structures have been analyzed at six sites of the Kathmandu valley. Microgranulometric study (this Supplement and Fig. 3B of Mugnier et al., Tectonophysics, 2011) reveals that silty levels (60 to 80% silt) favor the development of soft-sediment deformation structures, while sandy levels (60 to 80% sand) are passively deformed. Nonetheless well sorted sand levels (more than 80% sand) generate over-fluid pressure during compaction if located beneath a silty cap, leading to fluidization and dike development. 3-D geometry of seismites indicates a very strong horizontal shearing during their development. Using a physical approach based on soil liquefaction during horizontal acceleration, we show that the fluidization zone progressively grows down-section during the shaking, but does not exactly begin at the surface. The comparison of bed-thickness and strength/depth evolution indicates three cases: i) no soft-sediment deformation occurs for thin (few centimeters) silty beds; ii) the thickness of soft-sediment deformation above sandy beds is controlled by the lithological contrast; iii) the thickness of soft-sediment deformation depends on the shaking intensity for very thick silty beds. These 3 cases are evidenced in the Kathmandu basin. We use the 30 cm-thick soft-sediment deformation level formed during the 1833 earthquake as a reference: the 1833 earthquake rupture zone extended very close to Kathmandu, inducing there MMI IX-X damages. A 90 cm-thick sediment deformation has therefore to be induced by an event greater than MMI X. From a compilation of paleo and historic seismology studies, it is found that the great (M ~ 8.1) historical earthquakes are not characteristic of the greatest earthquakes of Himalaya; hence earthquakes greater than M ~ 8.6 occurred. Kathmandu is located above one of the asperities that laterally limits the extent of mega-earthquake ruptures and two successive catastrophic events already affected Kathmandu, in 1255 located to the west of this asperity and in ~ 1100 to the east.