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No Access Submitted: 10 October 2006 Accepted: 01 May 2007 Published Online: 05 July 2007

  • A tool for real-time acoustic species identification of delphinid whistles

The Journal of the Acoustical Society of America 122, 587 (2007); https://doi.org/10.1121/1.2743157
Julie N. Oswalda)
  • Scripps Institution of Oceanography, University of California—San Diego, San Diego, California 92038
    • Shannon Rankin and Jay Barlow
  • NOAA-NMFS Southwest Fisheries Science Center, La Jolla Shores Drive, La Jolla, California 92037
    • Marc O. Lammers
  • Hawaii Institute of Marine Biology, Kailua, Hawaii 96834
    • more...View Affiliations
    View Contributors
    • Julie N. Oswald
    • Shannon Rankin
    • Jay Barlow
    • Marc O. Lammers
    ABSTRACT
    The ability to identify delphinid vocalizations to species in real-time would be an asset during shipboard surveys. An automated system, Real-time Odontocete Call Classification Algorithm (ROCCA), is being developed to allow real-time acoustic species identification in the field. This Matlab-based tool automatically extracts ten variables (beginning, end, minimum and maximum frequencies, duration, slope of the beginning and end sweep, number of inflection points, number of steps, and presence/absence of harmonics) from whistles selected from a real-time scrolling spectrograph (ISHMAEL). It uses classification and regression tree analysis (CART) and discriminant function analysis (DFA) to identify whistles to species. Schools are classified based on running tallies of individual whistle classifications. Overall, 46% of schools were correctly classified for seven species and one genus (Tursiops truncatus, Stenella attenuata, S. longirostris, S. coeruleoalba, Steno bredanensis, Delphinus species, Pseudorca crassidens, and Globicephala macrorhynchus), with correct classification as high as 80% for some species. If classification success can be increased, this tool will provide a method for identifying schools that are difficult to approach and observe, will allow species distribution data to be collected when visual efforts are compromised, and will reduce the time necessary for post-cruise data analysis.

    ACKNOWLEDGMENTS

    We would like to gratefully acknowledge the tireless efforts of the skilled acousticians, visual observers, and cruise leaders who dedicated months to the surveys. Without them this project could not have been completed. We thank the officers and crew of the NOAA ships McArthur, McArthur II, and David Starr Jordan and the NSF/UNOLS R/V Endeavor for their patience and cooperation. Tim Gerrodette and Lisa Balance (and J.B.) were the Chief Scientists for these surveys. Special thanks to Stephanie Grassia and Theresa Weber for their assistance with data analysis. We also thank Michael Oswald and two anonymous reviewers for providing insightful comments on drafts of this manuscript.

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