Deciphering Co-Seismic Sedimentary Processes In The Mediterranean Sea Using Elemental, Organic Carbon, And Isotopic Data

GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS(2021)

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摘要
Identification of catastrophic events recorded as resedimented deep marine deposits can be challenging because of multiple possible triggering mechanisms. This study investigates seismo-turbidites (STs) deposited in the Ionian Sea as a consequence of major historical earthquakes related to the Calabrian Arc subduction system. Taking advantage of the available sedimentological reconstructions, we focused our analysis on high-resolution X-ray fluorescence core scanner (XRF-CS), organic carbon and isotopic data to define geochemical signatures characterizing the ST units. The relationships between geochemical and sedimentological proxies were statistically tested using Pearson correlation and principal component analysis (PCA). Up to similar to 78% of the total variance in the data set can be reduced to three principal components which identified four elemental ratio groups associated to the degree of terrestrial/coastal influence in each major depositional unit (i.e., pelagic, ST sandy stacked units, homogenites, tsunamite-seiche laminites, and tsunamite backwash). The sample score results were evaluated together with organic carbon data in order to assess geochemical variability throughout the composite turbidite structure in different basins settings. The basal parts of the ST contain coarse-grained sediment stacks whose sources can be traced back and sedimentary processes (surficial sediment erosion/massive slope failures) can be defined using geochemical data. The topmost parts of the STs exhibit a mixed compositional character suggesting basin-wide processes such as seiche oscillations and tsunami wave erosion/backwashing. The application of selected XRF-CS based elemental ratios as proxies in paleoseismological studies can help reconstruct the seismic history of a continental margin.
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关键词
seismo-turbidites, earthquake, tsunami, XRF-core scanner, statistical analyses, Calabrian Arc
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