Literature DB >> 33239320

Mobile robotic platforms for the acoustic tracking of deep-sea demersal fishery resources.

I Masmitja1, J Navarro2, S Gomariz3, J Aguzzi2,4, B Kieft5, T O'Reilly5, K Katija5, P J Bouvet6, C Fannjiang7, M Vigo2, P Puig2, A Alcocer8, G Vallicrosa9, N Palomeras9, M Carreras9, J Del Rio3, J B Company2.   

Abstract

Knowing the displacement capacity and mobility patterns of industrially exploited (i.e., fished) marine resources is key to establishing effective conservation management strategies in human-impacted marine ecosystems. Acquiring accurate behavioral information of deep-sea fished ecosystems is necessary to establish the sizes of marine protected areas within the framework of large international societal programs (e.g., European Community H2020, as part of the Blue Growth economic strategy). However, such information is currently scarce, and high-frequency and prolonged data collection is rarely available. Here, we report the implementation of autonomous underwater vehicles and remotely operated vehicles as an aid for acoustic long-baseline localization systems for autonomous tracking of Norway lobster (Nephrops norvegicus), one of the key living resources exploited in European waters. In combination with seafloor moored acoustic receivers, we detected and tracked the movements of 33 tagged lobsters at 400-m depth for more than 3 months. We also identified the best procedures to localize both the acoustic receivers and the tagged lobsters, based on algorithms designed for off-the-shelf acoustic tags identification. Autonomous mobile platforms that deliver data on animal behavior beyond traditional fixed platform capabilities represent an advance for prolonged, in situ monitoring of deep-sea benthic animal behavior at meter spatial scales.
Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Entities:  

Year:  2020        PMID: 33239320     DOI: 10.1126/scirobotics.abc3701

Source DB:  PubMed          Journal:  Sci Robot        ISSN: 2470-9476


  2 in total

1.  Burrow emergence rhythms of Nephrops norvegicus by UWTV and surveying biases.

Authors:  Jacopo Aguzzi; Nixon Bahamon; Jennifer Doyle; Colm Lordan; Ian D Tuck; Matteo Chiarini; Michela Martinelli; Joan B Company
Journal:  Sci Rep       Date:  2021-03-11       Impact factor: 4.379

Review 2.  Toward a decade of ocean science for sustainable development through acoustic animal tracking.

Authors:  Josep Alós; Kim Aarestrup; David Abecasis; Pedro Afonso; Alexandre Alonso-Fernandez; Eneko Aspillaga; Margarida Barcelo-Serra; Jonathan Bolland; Miguel Cabanellas-Reboredo; Robert Lennox; Ross McGill; Aytaç Özgül; Jan Reubens; David Villegas-Ríos
Journal:  Glob Chang Biol       Date:  2022-08-05       Impact factor: 13.211

  2 in total

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