Literature DB >> 32174485

A field comparison of marine mammal detections via visual, acoustic, and infrared (IR) imaging methods offshore Atlantic Canada.

Heather R Smith1, Daniel P Zitterbart2, Thomas F Norris3, Michael Flau4, Elizabeth L Ferguson5, Colin G Jones6, Olaf Boebel7, Valerie D Moulton8.   

Abstract

Impulsive sounds generated during seismic surveys have elicited behavioral responses in marine mammals and could cause hearing impairment or injury. Mitigating exposure to seismic sound often relies on real-time marine mammal detection. Detection performance is influenced by detection method, environmental conditions, and observer experience. We conducted a field comparison of real-time detections made by marine mammal observers (MMOs), a rotating infrared (IR) camera, and via passive acoustic monitoring (PAM). Data were collected from a 38 m research vessel offshore Atlantic Canada. Our results indicate that overall detection rates increase when complementary methods are used. MMOs and PAM are likely the most effective combination during high seas and precipitation. PAM and IR can be used in darkness. In good visibility, MMOs with IR or PAM should increase detections. Our results illustrate the importance of addressing false positive IR detections, matching system capabilities to sea conditions/species of interest, and employing experienced observers.
Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Detection methods; Infrared (IR) imaging; Marine mammal; Observer experience; Passive acoustic monitoring (PAM); Seismic survey

Mesh:

Year:  2020        PMID: 32174485     DOI: 10.1016/j.marpolbul.2020.111026

Source DB:  PubMed          Journal:  Mar Pollut Bull        ISSN: 0025-326X            Impact factor:   5.553


  2 in total

1.  Convergence of emerging technologies: Development of a risk-based paradigm for marine mammal monitoring for offshore wind energy operations.

Authors:  A Michael Macrander; Louis Brzuzy; Kaustubha Raghukumar; Damian Preziosi; Craig Jones
Journal:  Integr Environ Assess Manag       Date:  2021-11-15       Impact factor: 3.084

2.  Discriminating and classifying odontocete echolocation clicks in the Hawaiian Islands using machine learning methods.

Authors:  Morgan A Ziegenhorn; Kaitlin E Frasier; John A Hildebrand; Erin M Oleson; Robin W Baird; Sean M Wiggins; Simone Baumann-Pickering
Journal:  PLoS One       Date:  2022-04-12       Impact factor: 3.240

  2 in total

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