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

Journal: Science robotics
PMID:

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 (), 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.

Authors

  • I Masmitja
    SARTI Research Group, Electronics Department, Universitat Politècnica de Catalunya, Barcelona, Spain. ivan.masmitja@upc.edu.
  • J Navarro
    Institut de Ciències del Mar - CSIC, Barcelona, Spain.
  • S Gomariz
    SARTI Research Group, Electronics Department, Universitat Politècnica de Catalunya, Barcelona, Spain.
  • J Aguzzi
    Institut de Ciències del Mar - CSIC, Barcelona, Spain.
  • B Kieft
    Research and Development, Monterey Bay Aquarium Research Institute, Moss Landing, CA, USA.
  • T O'Reilly
    Research and Development, Monterey Bay Aquarium Research Institute, Moss Landing, CA, USA.
  • K Katija
    Research and Development, Monterey Bay Aquarium Research Institute, Moss Landing, CA, USA.
  • P J Bouvet
    L@BISEN, ISEN Brest Yncréa Ouest Brest, France.
  • C Fannjiang
    Department of Electrical Engineering and Computer Sciences, UC Berkeley, Berkeley, CA, USA.
  • M Vigo
    Institut de Ciències del Mar - CSIC, Barcelona, Spain.
  • P Puig
    Institut de Ciències del Mar - CSIC, Barcelona, Spain.
  • A Alcocer
    Department of Mechanical, Electronics and Chemical Engineering, and AI lab, Oslo Metropolitan University, Oslo, Norway.
  • G Vallicrosa
    Computer Vision and Robotics Institute (VICOROB), Universitat de Girona, Girona, Spain.
  • N Palomeras
    Computer Vision and Robotics Institute (VICOROB), Universitat de Girona, Girona, Spain.
  • M Carreras
    Computer Vision and Robotics Institute (VICOROB), Universitat de Girona, Girona, Spain.
  • J Del Rio
    SARTI Research Group, Electronics Department, Universitat Politècnica de Catalunya, Barcelona, Spain.
  • J B Company
    Institut de Ciències del Mar - CSIC, Barcelona, Spain.