Applications and analytical approaches using imaging sonar for quantifying behavioural interactions among aquatic organisms and their environment

Author:

Munnelly Ryan T12ORCID,Castillo Jose C3,Handegard Nils Olav4ORCID,Kimball Matthew E5,Boswell Kevin M6,Rieucau Guillaume1

Affiliation:

1. Louisiana Universities Marine Consortium , 8124 Hwy. 56, Chauvin, LA 70344 , USA

2. Coonamessett Farm Foundation, Inc. , 277 Hatchville Rd., East Falmouth, MA 02536 , USA

3. University Carlos III de Madrid, Higher Polytechnic School , 30 University Ave., Madrid 28911 , Spain

4. Institute of Marine Research , P.O. Box 1870, 5817 Nordnes, Bergen , Norway

5. Baruch Marine Field Laboratory, University of South Carolina , 2306 Crab Hall Road, Georgetown, SC 29440 , USA

6. Florida International University, Department of Biological Sciences , 3000 NE 151st St., North Miami, FL 33181 , USA

Abstract

Abstract For many aquatic animals, distributional patterns, trophodynamic relationships, and reproductive activity are driven by complex biotic and abiotic ecosystem interactions that influence behaviour. Linking behavioural information to environmental stimuli and stressors can, therefore, help to anticipate population and ecosystem responses to changing conditions and inform management. However, behavioural information is challenging to obtain because many sampling gears do not provide adequate spatial or temporal resolution, or potentially alter behaviours. Traditionally, most behavioural studies have been laboratory experiments, while behaviour in situ has often been inferred indirectly. Advancements in imaging sonar technology enable the study of in situ behaviours with the potential to address many understudied relationships. In this review we discuss applications of imaging sonar among a meta-analysis of 155 studies of aquatic organisms in their environments. We evaluate the performance of imaging sonar for studying inter- and intra-specific interactions, associations with complex and sensitive habitats and low-visibility environments, and to evaluate traditional fisheries sampling gears. We examine the data processing and analytical methods used to refine taxonomic resolution, manage time use and autocorrelation through sub-sampling, extract behavioural metrics applied to ecological processes, and for automating abundance estimates and image classification with the goal of providing a resource for researchers.

Funder

Bureau of Ocean Energy Management

Publisher

Oxford University Press (OUP)

Subject

Ecology,Aquatic Science,Ecology, Evolution, Behavior and Systematics,Oceanography

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