Big data, sound science, lasting impact: A framework for passive acoustic monitoring

Marine passive acoustic monitoring (PAM) has produced petabytes of data that are used by researchers, resource managers, industry, and regulators to understand how marine animals use sound and the impacts of anthropogenic noise on species and ecosystems throughout the global ocean. These big data provide unprecedented opportunities to study underwater soundscapes but also enormous challenges to efficiently extract information. To address these challenges, the Sound Cooperative (SoundCoop) project built community-focused cyberinfrastructure to promote improved, scalable and sustainable processing and access of marine PAM data for management, science, industry and military applications. Driven by cross-institutional participation representing a diversity of data collection methods and conditions, SoundCoop established guidance for standardized processing of ocean sound level metrics using freeware software toolkits and developed core tools and processes that support open science. Four comparative analyses that connect PAM monitoring efforts and integrate non-acoustic data illustrate how interoperable sound level metrics support a more coherent and synoptic perspective on ocean soundscapes using methods that current and future PAM projects can leverage. Such a framework around PAM big data offers the opportunity to revolutionize large-scale marine ecology and oceanography in similar ways to other transformative approaches for understanding environmental patterns and processes at global scales.

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Publication Details

Journal
Big Earth Data
Published
2025-12-04
DOI
https://doi.org/10.1080/20964471.2025.2583505
Citations
1
Primary Topic
Marine animal studies overview
Type
article
Field-Weighted Citation Impact
1.72

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article

Big data, sound science, lasting impact: A framework for passive acoustic monitoring

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Big Earth Data
Marine animal studies overview
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article

Big data, sound science, lasting impact: A framework for passive acoustic monitoring

Leila Hatch, Samara M. Haver, Eric W. Montie, Alyssa Marian, Catherine L. Berchok, Jason Gedamke, Aaron N. Rice, Megan F. McKenna, Sofie M. Van Parijs, Charles D. Anderson, Tom Shyka, Kaitlin E. Frasier, Erica Staaterman, Peter J. Dugan, Clea Parcerisas, G. E. Davis, Jennifer Miksis‐Olds, Kyle M. Becker, Olaf Boebel, Gabrielle Canonico, Timothy J. Rowell, Adrienne Canino, Dimitri Ponirakis, Anurag Kumar, Danelle E. Cline, Niels Kinneging, Rob Bochenek, Karolin Thomisch, Matt Biddle, Carrie C. Wall, Carlos Rueda, John J. Ryan, Karina Khazmutdinova, Emily Shumchenia
article en
1 citations

Abstract

Marine passive acoustic monitoring (PAM) has produced petabytes of data that are used by researchers, resource managers, industry, and regulators to understand how marine animals use sound and the impacts of anthropogenic noise on species and ecosystems throughout the global ocean. These big data provide unprecedented opportunities to study underwater soundscapes but also enormous challenges to efficiently extract information. To address these challenges, the Sound Cooperative (SoundCoop) project built community-focused cyberinfrastructure to promote improved, scalable and sustainable processing and access of marine PAM data for management, science, industry and military applications. Driven by cross-institutional participation representing a diversity of data collection methods and conditions, SoundCoop established guidance for standardized processing of ocean sound level metrics using freeware software toolkits and developed core tools and processes that support open science. Four comparative analyses that connect PAM monitoring efforts and integrate non-acoustic data illustrate how interoperable sound level metrics support a more coherent and synoptic perspective on ocean soundscapes using methods that current and future PAM projects can leverage. Such a framework around PAM big data offers the opportunity to revolutionize large-scale marine ecology and oceanography in similar ways to other transformative approaches for understanding environmental patterns and processes at global scales.

Big Earth Data
NOAA National Marine Fisheries Service (US), Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (DE), Flanders Marine Institute (BE), Oregon Department of Fish and Wildlife (US), Oregon State University (US), Monterey Bay Aquarium Research Institute (US), Scripps Institution of Oceanography (US), University of New Hampshire (US), Cooperative Institute for Research in Environmental Sciences (US), Office of Naval Research (US), University of New Hampshire at Manchester (US), University of Colorado Boulder (US), Cornell University (US), NOAA Pacific Marine Environmental Laboratory (US), Naval Undersea Warfare Center (US), Ghent University Hospital (BE), University of Colorado System (US), Center for Environmental Health (US), United States Department of the Navy (US), Ghent University (BE), Ministry of Infrastructure and Water Management (NL), Office of Science (US), Ocean Acoustical Services and Instrumentation Systems (United States) (US), Integrated Marine Observing System (AU), NOAA National Marine Fisheries Service Alaska Fisheries Science Center (US), NOAA National Marine Fisheries Service Northeast Fisheries Science Center (US), NOAA National Marine Fisheries Service Southeast Fisheries Science Center (US), Ocean Energy (Norway) (NO), NOAA Office of National Marine Sanctuaries (US), Japan Wildlife Research Center (JP), NOAA National Centers for Environmental Information (US), Northeastern Regional Association of Coastal and Ocean Observing Systems (United States) (US), NOAA Integrated Ocean Observing System (US), University of South Carolina Beaufort (US), Tetra Tech (United States) (US)
Fonds Wetenschappelijk Onderzoek, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, LifeWatch – Niclas Öberg Foundation, Vlaamse regering, National Oceanic and Atmospheric Administration, University of Colorado Boulder, U.S. Navy, Bureau of Ocean Energy Management, Office of Naval Research, National Marine Fisheries Service, Office of National Marine Sanctuaries
Openalex Percentile: Top 12%
Marine animal studies overview
1.72
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