Working Group on Fisheries Acoustics, Science and Technology (WGFAST)
The Working Group of Fisheries Acoustics, Science and Technology (WGFAST) focuses on the development and application of science and technology to observe the marine environment. In this report, WGFAST summarizes 38 presentations addressing the three themes: “Acoustic methods to characterize populations, ecosystems, habitat, and behaviour”, “Acoustic characterization of marine organisms”, and “Emerging technologies, methodologies, and protocols” and the discussions addressing these three themes. Common themes throughout these sessions were the increasing use of autonomous vehicles for collecting data and the increasing use of advanced statistical methodologies to process and quantitatively interpret acoustic data. Acoustical, environmental, and “ground-truthing” data are being collected beyond using traditional vessel-based surveys providing multiple data streams to characterize ecosystems. Many of the presentations highlighted “big data” statistical methodologies to fully utilize these data and improve our understanding of ecosystems.
This report also summarizes the WGFAST responses to the Working Group on International Pelagic Surveys (WGIPS) concerning potential sampling bias of shallow fish schools and to the Workshop on Atlantic chub mackerel (Scomber colias) (WKCOLIAS) concerning catchability of large chub mackerel (Scomber colias) in European waters, and WGFAST formed a group to ad-dress a methodological request from the WGIPS. WGFAST reviewed updates from the International Organization for Standardization (ISO) liaison, Topic Group on Collecting Quality Under-water Acoustic Data (TGQUAD) chair, Topic Group on Acoustic Metadata (TGMETA) chair, and Workshop on Acoustic Backscattering Models (WKABM) chair. With a goal of advancing the use of fisheries acoustic data in fisheries and ecosystem science, WGFAST continues to promote development of open-source data formats and software for interpreting acoustic data. WGFAST members are active participants in ICES’ efforts in “Big Data” (i.e. data archive and discovery; open-source software to read, process, and analyse acoustic data; open-source data formats; and applications of artificial intelligence (AI) and machine learning (ML) methods), and continue to develop new and innovative methods to inform conservation and management of ecosystems.
This report also outlines future plans for the working group, including details for the 2022 meeting and proposals for a 2023 WGFAST/ICES Symposium and two joint sessions for the 2022 ICES Annual Science Conference.
Published under the auspices of the following ICES Steering Group or Committee