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

Details

• Journal Title:
  Big Earth Data
• Personal Author:
  Wall, Carrie C. ; McKenna, Megan F. ; Hatch, Leila T. ; Van Parijs, Sofie M. ; Bochenek, Rob ; Dugan, Peter ; Parcerisas, Clea ; Ryan, John ; Anderson, Charles D. ; Becker, Kyle ; Berchok, Catherine ; Biddle, Mathew ; Boebel, Olaf ; Canino, Adrienne ; Canonico, Gabrielle ; Cline, Danelle ; Davis, Genevieve E. ; Frasier, Kaitlin ; Gedamke, Jason ; Haver, Samara M. ; Khazmutdinova, Karina ; Kinneging, Niels ; Kumar, Anurag ; Marian, Alyssa ; Miksis-Olds, Jennifer L. ; Montie, Eric W. ; Ponirakis, Dimitri ; Rice, Aaron N. ; Rowell, Timothy J. ; Rueda, Carlos ; Shumchenia, Emily ; Shyka, Thomas ; Staaterman, Erica ; Thomisch, Karolin
• NOAA Program & Office:
  NESDIS (National Environmental Satellite, Data, and Information Service) ; NMFS (National Marine Fisheries Service) ; NOS (National Ocean Service) ; OAR (Oceanic and Atmospheric Research) ; AFSC (Alaska Fisheries Science Center) ; IOOS (Integrated Ocean Observing System) ; NCEI (National Centers for Environmental Information) ; NEFSC (Northeast Fisheries Science Center) ; ONMS (Office of National Marine Sanctuaries) ; PMEL (Pacific Marine Environmental Laboratory) ; SEFSC (Southeast Fisheries Science Center)
• Description:
  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.
• Source:
  Big Earth Data (2025)
• DOI:
  https://doi.org/10.1080/20964471.2025.2583505
• ISSN:
  2096-4471 ; 2574-5417
• Format:
  pdf
• Publisher:
  Informa UK Limited
• Document Type:
  Journal Article
• License:
  https://creativecommons.org/licenses/by/4.0/
• Rights Information:
  CC BY
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:beef76fc294a3bcea80deca37b02a0a5ab2eceef53bef25b36e029180a96ffbe3e5c09fd1dae31c10c716e154e315d80c2d0b6bc279ea58ea0003b6c8107fd97
• Download URL:
  https://repository.library.noaa.gov/view/noaa/72168/noaa_72168_DS1.pdf
• File Type:
  [PDF - 5.26 MB ]