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Research at St Andrews

Comparison of fin whale 20 Hz call detections by deep-water mobile autonomous and stationary recorders

Research output: Contribution to journalArticle

DOI

Author(s)

Selene Fregosi, Danielle V. Harris, Haruyoshi Matsumoto, David K. Mellinger, Christina Negretti, David J. Moretti, Stephen W. Martin, Brian Matsuyama, Peter J. Dugan, Holger Klinck

School/Research organisations

Abstract

Acoustically equipped deep-water mobile autonomous platforms can be used to survey for marine mammals over intermediate spatiotemporal scales. Direct comparisons to fixed recorders are necessary to evaluate these tools as passive acoustic monitoring platforms. One glider and two drifting deep-water floats were simultaneously deployed within a deep-water cabled hydrophone array to quantitatively assess their survey capabilities. The glider was able to follow a pre-defined track while float movement was somewhat unpredictable. Fin whale (Balaenoptera physalus) 20 Hz pulses were recorded by all hydrophones throughout the two-week deployment. Calls were identified using a template detector, which performed similarly across recorder types. The glider data contained up to 78% fewer detections per hour due to increased low-frequency flow noise present during glider descents. The glider performed comparably to the floats and fixed recorders at coarser temporal scales; hourly and daily presence of detections did not vary by recorder type. Flow noise was related to glider speed through water and dive state. Glider speeds through water of 25 cm/s or less are suggested to minimize flow noise and the importance of glider ballasting, detector characterization, and normalization by effort when interpreting glider-collected data and applying it to marine mammal density estimation are discussed.
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Details

Original languageEnglish
Pages (from-to)961-977
Number of pages17
JournalJournal of the Acoustical Society of America
Volume147
Issue number2
Early online date10 Feb 2020
DOIs
Publication statusE-pub ahead of print - 10 Feb 2020

    Research areas

  • Statistical analysis, Acoustic noise, Aquatic ecology, Animal communication, Bioacoustics of mammals, Electronic noise, Oceanography, Spectrograms, Regression analysis, Hydrophone

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