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June 23, 20260 citationsOpen Access

Preliminary report on progress for advanced data processing, geolocation and export format

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JRJulie RobidartFTFletcher ThompsonPMPatrízio Mariani

Key Points

  • The report outlines the progress made in developing technologies for biodiversity monitoring in marine environments.
  • Conducted a 18-month project under the MARCO BOLO initiative focused on WP4
  • Developed technologies for in situ monitoring, including genomic sampling and automated classification systems
  • Integrated various systems such as USBL acoustics and AI-driven image processing for enhanced data collection and geolocation.
  • Established a pipeline for real-time data collection and geolocation without field testing yet
  • Developed technologies for biodiversity data mapping, species detection, and automated classification
  • Plans to demonstrate these technologies in June 2025 in the Belgian North Sea.

Abstract

Grant Agreement: 101082021Project Acronym: MARCO-BOLOProject Title: MARine COastal BiOdiversity Long-term ObservationsDeliverable Number: D4.1Work Package Number: WP4Deliverable Title: Preliminary report on progress for advanced data processing, geolocation and export formatDue Date: 01.07.2024Date of creation (cover): 31.03.2024Submission Date (Ares ref): 25.06.2024 Sustainable monitoring of organisms and their habitats is imperative during the biodiversity crisis, and is especially important in marine waters where fisheries alone feed approximately 3 billion people globally while multiple threats change ecosystem dynamics. MARCO BOLO’s WP4 aims to create a direct pipeline from non-invasive, in situ monitoring of marine life, to ocean users and managers. WP4 aims to achieve this through adoption of workflows developed in WP1, FAIR data reporting, automated classification of high-volume datasets, and geolocation of sensed data in near-real-time. The first 18 months of MARCO BOLO resulted in the development of several new deployable technologies to measure biodiversity, enabling geolocation in the field, simplicity in interacting with the software and datasets, automated classification and data processing, and enabling data flows from high-volume datasets to public repositories. While not yet field-tested, the developments described here already enable the reporting of biodiversity datasets for mapping and response, detecting ecosystems and their prey, and counting and communicating species data from the field. One publication describing these new biodiversity systems is open-access and another has been submitted. The WP4 team aims to demonstrate these developments in June 2025 in the Belgian North Sea. This report describes the progress made in the first 18 months of MARCO BOLO WP4, Task 4.1, to “develop autonomous systems to deliver georeferenced maps of biodiversity attributes including genomic, taxonomic and habitat characteristics.” Deliverable 4.1 is achieved through seven complementary technologies targeting diverse biodiversity variables, organized across four sub-objectives: Genomics: upgrading the Robotic Cartridge Sampling Instrument (RoCSI) sampler and the LAMPTRON eDNA sensor to facilitate geolocation, data delivery, and usability. Particulate and plankton imaging: integrating the UVP6 into autonomous vehicles with on-board image processing using a miniaturized AI system for real-time image classification. Fish and benthos: integrating Ultra Short Base Line (USBL) acoustics for positioning of an open-source BlueROV2 ROV with a new high-definition multi-camera system; outputs include processed large-scale seafloor images and annotations of identified animals. Bioacoustics: developing a stand-alone mooring accommodating an acoustic fish receiver, a broadband hydrophone, and a C-POD/F-POD device for long-term recording at sea, with a data pipeline for detection and classification of harbour porpoise (Phocoena phocoena) echolocation click trains and export to EMODnet Biology and EurOBIS following FAIR principles.

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Cite This Study

Robidart et al. (2024) studied this question.

synapsesocial.com/papers/6a3a223b111626ef22ab6ed3https://doi.org/10.5281/zenodo.20779637
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