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Characterization of sound scattering layers in the Bay of Biscay using broadband acoustics, nets and video acoustics and biological data
Citation
Blanluet Arthur, Doray Mathieu, Berger Laurent, Romagnan Jean-Baptiste, Le Bouffant Naig, Lehuta Sigrid, Petitgas Pierre (2016). "Characterization of sound scattering layers in the Bay of Biscay using broadband acoustics, nets and video" acoustics and biological Data. SEANOE. https://doi.org/10.17882/62440
Contact:
Availability: 
To the extent possible under law, the person who associated CC0 with this dataset has waived all copyright and related or neighboring rights to this dataset.
To the extent possible under law, the person who associated CC0 with this dataset has waived all copyright and related or neighboring rights to this dataset.Description
Sound scattering layers (SSLs) are observed over a broad range of spatio-temporal scales and geographical areas. SSLs represent a large biomass, likely involved in the biological carbon pump and the structure of marine trophic webs. Yet, the taxonomic composition remains largely unknown for many SSLs. more
To investigate the challenges of SSL sampling, we performed a survey in a small study area in the Northern Bay of Biscay (France) by combining broadband and narrowband acoustics, net sampling, imagery and video recordings. In order to identify organisms contributing to the observed SSLs, we compared measured frequency spectra to forward predicted spectra derived from biological data. This dataset comprises the echo-integrated broadband acoustic data (in Sv(f)), the nets position and depth, and the abundance and the size of the catched organisms acquired during a specific operation of SSLs sampling during (Blanluet et al.)-[https://doi.org/10.1371/journal.pone.0223618]. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications. (The acoustic data are available via the MDA archived link below the dataset citation)
To investigate the challenges of SSL sampling, we performed a survey in a small study area in the Northern Bay of Biscay (France) by combining broadband and narrowband acoustics, net sampling, imagery and video recordings. In order to identify organisms contributing to the observed SSLs, we compared measured frequency spectra to forward predicted spectra derived from biological data. This dataset comprises the echo-integrated broadband acoustic data (in Sv(f)), the nets position and depth, and the abundance and the size of the catched organisms acquired during a specific operation of SSLs sampling during (Blanluet et al.)-[https://doi.org/10.1371/journal.pone.0223618]. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications. (The acoustic data are available via the MDA archived link below the dataset citation)
Scope
Themes:
Biology > Fish, Physical > Underwater acoustics
Keywords:
EurOBIS calculated BBOX, French part of the Bay of Biscay
Geographical coverage
EurOBIS calculated BBOX Stations
Bounding Box
Coordinates: MinLong: -5,176; MinLat: 45,3661 - MaxLong: -1,9336; MaxLat: 47,5665 [WGS84]
Coordinates: MinLong: -5,176; MinLat: 45,3661 - MaxLong: -1,9336; MaxLat: 47,5665 [WGS84]
French part of the Bay of Biscay [Marine Regions]
Temporal coverage
27 May 2016 - 31 May 2016
Parameter
Length
Contributors
Romagnan, Jean-Baptiste, data producer, data creator
Related datasets
Published in:
EurOBIS: European Ocean Biodiversity Information System, more
Publication
Based on this dataset
Blanluet, A. et al. (2019). Characterization of sound scattering layers in the Bay of Biscay using broadband acoustics, nets and video. PLoS One 14(10): e0223618. https://dx.doi.org/10.1371/journal.pone.0223618
Dataset status: In Progress
Data type: Data
Data origin: Research: field survey
Metadatarecord created: 2022-10-18
Information last updated: 2023-02-02
