ALBERT

Description: One of the most effective approaches to identifying possible precursors of eruptions is the analysis of seismicity patterns recorded at volcanoes. Accurate locations of the seismicity and the estimate of source mechanisms can resolve fault systems and track fluid migrations through volcanoes. We analysed the six main swarms recorded at Campi Flegrei since 2000, using them as a proxy of the processes involved in the long-term-unrest of this densely populated caldera. We re-located the earthquakes comprised in these swarms and estimated the focal mechanisms, which appear in agreement with the fault systems of the caldera and with tomographic images. The focal mechanisms are in agreement with the tensional stress induced by the caldera uplift. Most of the swarms and remaining seismicity delineate a highly fractured volume extending vertically below the Solfatara/ Pisciarelli vents, where gases find preferential paths to the surface triggering earthquakes. The main swarms are located below this volume where the presence of a rigid caprock is still debated. We interpreted the current unrest in term of a gradual increment in the activity of a wide hydrothermal system whose most evident manifestation is the enlargement of the fumarolic-field of Pisciarelli and the increment of the earthquakes occurrence rate.

Description: Published

Description: 2900

Description: 2V. Struttura e sistema di alimentazione dei vulcani

Description: JCR Journal

Description: The geographic distribution of earthquake effects quantified in terms of macroseismic intensities, the so-called macroseismic field, provides basic information for several applications including source characterization of pre-instrumental earthquakes and risk analysis. Macroseismic fields of past earthquakes as inferred from historical documentation may present spatial gaps, due to the incompleteness of the available information. We present a probabilistic approach aimed at integrating incomplete intensity distributions by considering the Bayesian combination of estimates provided by intensity prediction equations (IPEs) and data documented at nearby localities, accounting for the relevant uncertainties and the discrete and ordinal nature of intensity values. The performance of the proposed methodology is tested at 28 Italian localities with long and rich seismic histories and for two well-known strong earthquakes (i.e., 1980 southern Italy and 2009 central Italy events). A possible application of the approach is also illustrated relative to a 16th-century earthquake in the northern Apennines.

Description: Published

Description: 2299–2311

Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica

Description: JCR Journal

Description: Ambient noise polarizes inside fault zones, yet the spatial and temporal resolution of polarized noise on gas-bearing fluids migrating through stressed volcanic systems is unknown. Here we show that high polarization marks a transfer structure connecting the deforming centre of the caldera to open hydrothermal vents and extensional caldera-bounding faults during periods of low seismic release at Campi Flegrei caldera (Southern Italy). Fluids pressurize the Campi Flegrei hydrothermal system, migrate, and increase stress before earthquakes. The loss of polarization (depolarization) of the transfer and extensional structures maps pressurized fluids, detecting fluid migrations after seismic sequences. After recent intense seismicity (December 2019-April 2020), the transfer structure appears sealed while fluids stored in the east caldera have moved further east. Our findings show that depolarized noise has the potential to monitor fluid migrations and earthquakes at stressed volcanoes quasi-instantaneously and with minimum processing.

Description: Published

Description: 6656

Description: 4V. Processi pre-eruttivi

Description: JCR Journal

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chapman, A. S. A., Beaulieu, S. E., Colaco, A., Gebruk, A. V., Hilario, A., Kihara, T. C., Ramirez-Llodra, E., Sarrazin, J., Tunnicliffe, V., Amon, D. J., Baker, M. C., Boschen-Rose, R. E., Chen, C., Cooper, I. J., Copley, J. T., Corbari, L., Cordes, E. E., Cuvelier, D., Duperron, S., Du Preez, C., Gollner, S., Horton, T., Hourdez, S., Krylova, E. M., Linse, K., LokaBharathi, P. A., Marsh, L., Matabos, M., Mills, S. W., Mullineaux, L. S., Rapp, H. T., Reid, W. D. K., Rybakova (Goroslavskaya), E., Thomas, T. R. A., Southgate, S. J., Stohr, S., Turner, P. J., Watanabe, H. K., Yasuhara, M., & Bates, A. E. sFDvent: a global trait database for deep-sea hydrothermal-vent fauna. Global Ecology and Biogeography, 28(11), (2019): 1538-1551, doi: 10.1111/geb.12975.

Description: Motivation Traits are increasingly being used to quantify global biodiversity patterns, with trait databases growing in size and number, across diverse taxa. Despite growing interest in a trait‐based approach to the biodiversity of the deep sea, where the impacts of human activities (including seabed mining) accelerate, there is no single repository for species traits for deep‐sea chemosynthesis‐based ecosystems, including hydrothermal vents. Using an international, collaborative approach, we have compiled the first global‐scale trait database for deep‐sea hydrothermal‐vent fauna – sFDvent (sDiv‐funded trait database for the Functional Diversity of vents). We formed a funded working group to select traits appropriate to: (a) capture the performance of vent species and their influence on ecosystem processes, and (b) compare trait‐based diversity in different ecosystems. Forty contributors, representing expertise across most known hydrothermal‐vent systems and taxa, scored species traits using online collaborative tools and shared workspaces. Here, we characterise the sFDvent database, describe our approach, and evaluate its scope. Finally, we compare the sFDvent database to similar databases from shallow‐marine and terrestrial ecosystems to highlight how the sFDvent database can inform cross‐ecosystem comparisons. We also make the sFDvent database publicly available online by assigning a persistent, unique DOI. Main types of variable contained Six hundred and forty‐six vent species names, associated location information (33 regions), and scores for 13 traits (in categories: community structure, generalist/specialist, geographic distribution, habitat use, life history, mobility, species associations, symbiont, and trophic structure). Contributor IDs, certainty scores, and references are also provided. Spatial location and grain Global coverage (grain size: ocean basin), spanning eight ocean basins, including vents on 12 mid‐ocean ridges and 6 back‐arc spreading centres. Time period and grain sFDvent includes information on deep‐sea vent species, and associated taxonomic updates, since they were first discovered in 1977. Time is not recorded. The database will be updated every 5 years. Major taxa and level of measurement Deep‐sea hydrothermal‐vent fauna with species‐level identification present or in progress. Software format .csv and MS Excel (.xlsx).

Description: We would like to thank the following experts, who are not authors on this publication but made contributions to the sFDvent database: Anna Metaxas, Alexander Mironov, Jianwen Qiu (seep species contributions, to be added to a future version of the database) and Anders Warén. We would also like to thank Robert Cooke for his advice, time, and assistance in processing the raw data contributions to the sFDvent database using R. Thanks also to members of iDiv and its synthesis centre – sDiv – for much‐valued advice, support, and assistance during working‐group meetings: Doreen Brückner, Jes Hines, Borja Jiménez‐Alfaro, Ingolf Kühn and Marten Winter. We would also like to thank the following supporters of the database who contributed indirectly via early design meetings or members of their research groups: Malcolm Clark, Charles Fisher, Adrian Glover, Ashley Rowden and Cindy Lee Van Dover. Finally, thanks to the families of sFDvent working group members for their support while they were participating in meetings at iDiv in Germany. Financial support for sFDvent working group meetings was gratefully received from sDiv, the Synthesis Centre of iDiv (DFG FZT 118). ASAC was a PhD candidate funded by the SPITFIRE Doctoral Training Partnership (supported by the Natural Environmental Research Council, grant number: NE/L002531/1) and the University of Southampton at the time of submission. ASAC also thanks Dominic, Lesley, Lettice and Simon Chapman for their support throughout this project. AEB and VT are sponsored through the Canada Research Chair Programme. SEB received support from National Science Foundation Division of Environmental Biology Award #1558904 and The Joint Initiative Awards Fund from the Andrew W. Mellon Foundation. AC is supported by Program Investigador (IF/00029/2014/CP1230/CT0002) from Fundação para a Ciência e a Tecnologia (FCT). This study also had the support of Fundação para a Ciência e a Tecnologia, through the strategic project UID/MAR/04292/2013 granted to marine environmental sciences centre. Data compiled by AVG and EG were supported by Russian science foundation Grant 14‐50‐00095. AH was supported by the grant BPD/UI88/5805/2017 awarded by CESAM (UID/AMB/50017), which is financed by FCT/Ministério da Educação through national funds and co‐funded by fundo Europeu de desenvolvimento regional, within the PT2020 Partnership Agreement and Compete 2020. ERLL was partially supported by the MarMine project (247626/O30). JS was supported by Ifremer. Data on vent fauna from the East Scotia Ridge, Mid‐Cayman Spreading Centre, and Southwest Indian Ridge were obtained by UK natural environment research council Grants NE/D01249X/1, NE/F017774/1 and NE/H012087/1, respectively. REBR's contribution was supported by a Postdoctoral Fellowship at the University of Victoria, funded by the Canadian Healthy Oceans Network II Strategic Research Program (CHONe II). DC is supported by a post‐doctoral scholarship (SFRH/BPD/110278/2015) from FCT. HTR was supported by the Research Council of Norway through project number 70184227 and the KG Jebsen Centre for Deep Sea Research (University of Bergen). MY was partially supported by grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (project codes: HKU 17306014, HKU 17311316).

Description: Intermediate depth (70-300 km) and deep (〉300 km) earthquakes have always been puzzling Earth scientists: their occurrence is a paradox, since the ductile behavior of rocks and the high confining pressure with increasing depths would theoretically preclude brittle failure and frictional sliding. The mechanisms proposed to explain deep earthquakes, mainly depending on the subducting plate age and stress state, are generally expressed by single parameters, unsuitable to comprehensively account for differences among distinct subduction zones or within the same slab. We analyze the Kurile and Izu-Bonin intraslab seismicity and detail the stress state along the subducted planes using the Gutenberg-Richter b-value. We demonstrate that, despite the slabs different properties (e.g., lithospheric age, stress state, dehydration rate), in both cases deep earthquakes are restricted to depths characterized by equal age from subduction initiation and are driven by stress regimes affected by the persistence of the metastable olivine wedge.

Description: Published

Description: 12440

Description: 3T. Fisica dei terremoti e Sorgente Sismica

Description: JCR Journal

Description: The high seismic productivity of volcanic areas provides the chance to investigate the local stress conditions with great resolution, by analysing the slope of the frequency-magnitude distribution of earthquakes, namely the b-value. Here we investigated the seismicity of Mt. Etna between 2005 and 2019, focusing on one of the largest known episodes of unrest in December 2018, when most of the intruding magma aborted, rather oddly, its ascent inside the volcano. We found a possible stress concentration zone along magma pathways, which may have inhibited the occurrence of a larger eruption. If the origin of such hypothetical loaded region is related to tectonic forces, one must consider the possibility that geodynamic processes can locally result in such rapid crustal strain as to perturb the release of magma. Strong b-value time-variations occurred a few days before the unrest event, suggesting new possibilities for investigating the volcano state and impending eruptions.

Description: Published

Description: 68

Description: 1T. Struttura della Terra

Description: 1V. Storia eruttiva

Description: 2V. Struttura e sistema di alimentazione dei vulcani

Description: 4V. Processi pre-eruttivi

Description: 5V. Processi eruttivi e post-eruttivi

Description: JCR Journal

Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Davis, G. E., Baumgartner, M. F., Corkeron, P. J., Bell, J., Berchok, C., Bonnell, J. M., Thornton, J. B., Brault, S., Buchanan, G. A., Cholewiak, D. M., Clark, C. W., Delarue, J., Hatch, L. T., Klinck, H., Kraus, S. D., Martin, B., Mellinger, D. K., Moors-Murphy, H., Nieukirk, S., Nowacek, D. P., Parks, S. E., Parry, D., Pegg, N., Read, A. J., Rice, A. N., Risch, D., Scott, A., Soldevilla, M. S., Stafford, K. M., Stanistreet, J. E., Summers, E., Todd, S., & Van Parijs, S. M. Exploring movement patterns and changing distributions of baleen whales in the western North Atlantic using a decade of passive acoustic data. Global Change Biology, (2020): 1-30, doi:10.1111/gcb.15191.

Description: Six baleen whale species are found in the temperate western North Atlantic Ocean, with limited information existing on the distribution and movement patterns for most. There is mounting evidence of distributional shifts in many species, including marine mammals, likely because of climate‐driven changes in ocean temperature and circulation. Previous acoustic studies examined the occurrence of minke (Balaenoptera acutorostrata ) and North Atlantic right whales (NARW; Eubalaena glacialis ). This study assesses the acoustic presence of humpback (Megaptera novaeangliae ), sei (B. borealis ), fin (B. physalus ), and blue whales (B. musculus ) over a decade, based on daily detections of their vocalizations. Data collected from 2004 to 2014 on 281 bottom‐mounted recorders, totaling 35,033 days, were processed using automated detection software and screened for each species' presence. A published study on NARW acoustics revealed significant changes in occurrence patterns between the periods of 2004–2010 and 2011–2014; therefore, these same time periods were examined here. All four species were present from the Southeast United States to Greenland; humpback whales were also present in the Caribbean. All species occurred throughout all regions in the winter, suggesting that baleen whales are widely distributed during these months. Each of the species showed significant changes in acoustic occurrence after 2010. Similar to NARWs, sei whales had higher acoustic occurrence in mid‐Atlantic regions after 2010. Fin, blue, and sei whales were more frequently detected in the northern latitudes of the study area after 2010. Despite this general northward shift, all four species were detected less on the Scotian Shelf area after 2010, matching documented shifts in prey availability in this region. A decade of acoustic observations have shown important distributional changes over the range of baleen whales, mirroring known climatic shifts and identifying new habitats that will require further protection from anthropogenic threats like fixed fishing gear, shipping, and noise pollution.

Description: We thank Chris Pelkie, David Wiley, Michael Thompson, Chris Tessaglia‐Hymes, Eric Matzen, Chris Tremblay, Lance Garrison, Anurag Kumar, John Hildebrand, Lynne Hodge, Russell Charif, Kathleen Dudzinski, and Ann Warde for help with project planning, field work support, and data management. For all the support and advice, thanks to the NEFSC Protected Species Branch, especially the passive acoustics group, Josh Hatch, and Leah Crowe. We thank the field and crew teams on all the ships that helped in the numerous deployments and recoveries. This research was funded and supported by many organizations, specified by projects as follows: data recordings from region 1 were provided by K. Stafford (funding: National Science Foundation #NSF‐ARC 0532611). Region 2 data: D. K. Mellinger and S. Nieukirk, National Oceanic and Atmospheric Administration (NOAA) PMEL contribution #5055 (funding: NOAA and the Office of Naval Research #N00014–03–1–0099, NOAA #NA06OAR4600100, US Navy #N00244‐08‐1‐0029, N00244‐09‐1‐0079, and N00244‐10‐1‐0047). Region 3A data: D. Risch (funding: NOAA and Navy N45 programs). Region 3 data: H. Moors‐Murphy and Fisheries and Oceans Canada (2005–2014 data), and the Whitehead Lab of Dalhousie University (eastern Scotian Shelf data; logistical support by A. Cogswell, J. Bartholette, A. Hartling, and vessel CCGS Hudson crew). Emerald Basin and Roseway Basin Guardbuoy data, deployment, and funding: Akoostix Inc. Region 3 Emerald Bank and Roseway Basin 2004 data: D. K. Mellinger and S. Nieukirk, NOAA PMEL contribution #5055 (funding: NOAA). Region 4 data: S. Parks (funding: NOAA and Cornell University) and E. Summers, S. Todd, J. Bort Thornton, A. N. Rice, and C. W. Clark (funding: Maine Department of Marine Resources, NOAA #NA09NMF4520418, and #NA10NMF4520291). Region 5 data: S. M. Van Parijs, D. Cholewiak, L. Hatch, C. W. Clark, D. Risch, and D. Wiley (funding: National Oceanic Partnership Program (NOPP), NOAA, and Navy N45). Region 6 data: S. M. Van Parijs and D. Cholewiak (funding: Navy N45 and Bureau of Ocean and Energy Management (BOEM) Atlantic Marine Assessment Program for Protected Species [AMAPPS] program). Region 7 data: A. N. Rice, H. Klinck, A. Warde, B. Martin, J. Delarue, and S. Kraus (funding: New York State Department of Environmental Conservation, Massachusetts Clean Energy Center, and BOEM). Region 8 data: G. Buchanan, and K. Dudzinski (funding: New Jersey Department of Environmental Protection and the New Jersey Clean Energy Fund) and A. N. Rice, C. W. Clark, and H. Klinck (funding: Center for Conservation Bioacoustics at Cornell University and BOEM). Region 9 data: J. E. Stanistreet, J. Bell, D. P. Nowacek, A. J. Read, and S. M. Van Parijs (funding: NOAA and US Fleet Forces Command). Region 10 data: L. Garrison, M. Soldevilla, C. W. Clark, R. A. Chariff, A. N. Rice, H. Klinck, J. Bell, D. P. Nowacek, A. J. Read, J. Hildebrand, A. Kumar, L. Hodge, and J. E. Stanistreet (funding: US Fleet Forces Command, BOEM, NOAA, and NOPP). Region 11 data: C. Berchok as part of a collaborative project led by the Fundacion Dominicana de Estudios Marinos, Inc. (Dr. Idelisa Bonnelly de Calventi; funding: The Nature Conservancy [Elianny Dominguez]) and D. Risch (funding: World Wildlife Fund, NOAA, and Dutch Ministry of Economic Affairs).