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  • 04. Solid Earth::04.06. Seismology::04.06.08. Volcano seismology  (1)
  • Genetic variation
  • Nature Publishing Group
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  • 1
    facet.materialart.
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    Nature Publishing Group
    Publication Date: 2017-04-04
    Description: One of the key issues in forecasting volcanic eruptions is to detect signals that can track the propagation of dykes towards the surface. Continuous monitoring of active volcanoes helps significantly in achieving this goal. The seismic data presented here are unique, as they document surface faulting processes close (tens to a few hundred meters) to their source, namely the dyke tip. They originated nearby - and under - a seismic station that was subsequently destroyed by lava flows during eruptive activity at Etna volcano, Italy, in 2013. On February 20, a ~600 m-long and ~120 m wide NW-SE fracture field opened at an altitude between 2750 and 2900 m. The consequent rock dislocation caused the station to tilt and offset the seismic signal temporarily. Data acquisition continued until the arrival of the lava flow that led to the breakdown of the transmission system. Shallow ground fracturing and repeated low-frequency oscillations occurred during two stages in which the seismic signal underwent a maximum offset ~2.57 E+04 nm/s. Bridging instrumental recordings, fieldwork and conceptual modelling, these data are interpreted as the seismic footprints of a magmatic dyke intrusion that moved at speed ~0.02 m/s (first stage) and 0.46 m/s (second stage).
    Description: This work was supported by the MED-SUV project, which has received funding from the European Union’s Seventh Programme for research, technological development and demonstration under grant agreement No 308665.
    Description: Published
    Description: 11908
    Description: 2V. Dinamiche di unrest e scenari pre-eruttivi
    Description: JCR Journal
    Description: restricted
    Keywords: dyke propagation ; Etna ; seismic signals ; ground fracturing ; conceptual modelling ; 04. Solid Earth::04.06. Seismology::04.06.08. Volcano seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
    Publication Date: 2022-05-25
    Description: © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nature 499 (2013): 209–213, doi:10.1038/nature12221.
    Description: Coccolithophores have influenced the global climate for over 200 million years1. These marine phytoplankton can account for 20 per cent of total carbon fixation in some systems2. They form blooms that can occupy hundreds of thousands of square kilometres and are distinguished by their elegantly sculpted calcium carbonate exoskeletons (coccoliths), rendering them visible from space3. Although coccolithophores export carbon in the form of organic matter and calcite to the sea floor, they also release CO2 in the calcification process. Hence, they have a complex influence on the carbon cycle, driving either CO2 production or uptake, sequestration and export to the deep ocean4. Here we report the first haptophyte reference genome, from the coccolithophore Emiliania huxleyi strain CCMP1516, and sequences from 13 additional isolates. Our analyses reveal a pan genome (core genes plus genes distributed variably between strains) probably supported by an atypical complement of repetitive sequence in the genome. Comparisons across strains demonstrate that E. huxleyi, which has long been considered a single species, harbours extensive genome variability reflected in different metabolic repertoires. Genome variability within this species complex seems to underpin its capacity both to thrive in habitats ranging from the equator to the subarctic and to form large-scale episodic blooms under a wide variety of environmental conditions.
    Description: Joint Genome Institute (JGI) contributions were supported by the Office of Science of the US Department of Energy (DOE) under contract no. 7DE-AC02-05CH11231.
    Keywords: Genetic variation
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
    Format: application/vnd.ms-excel
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