Using acoustic backscatter from a sidescan sonar to explain fish and invertebrate distributions: a case study in Bristol Bay, Alaska

• Published in: ICES Journal of Marine Science
• Main Authors: Yeung, Cynthia, McConnaughey, Robert A.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Oxford University Press (OUP) 2008
• Subjects: Ecology; Aquatic Science; Ecology, Evolution, Behavior and Systematics; Oceanography; Pacific; Paralithodes camtschaticus; Red king crab; Theragra chalcogramma; Alaska
• Online Access: http://dx.doi.org/10.1093/icesjms/fsn011; http://academic.oup.com/icesjms/article-pdf/65/2/242/29130092/fsn011.pdf

Abstract Yeung, C., and McConnaughey, R. A. 2008. Using acoustic backscatter from a sidescan sonar to explain fish and invertebrate distributions: a case study in Bristol Bay, Alaska. – ICES Journal of Marine Science, 65: 242–254. Environmental variables that are ecologically relevant and easily measured over large areas are useful for modelling species distributions and habitats. Continuous acoustic, sonar-backscatter data convey information about physical properties of the seabed, and hence could be a valuable addition to that suite of variables. We tested the potential utility of acoustic backscatter for improving habitat models of marine species using data from a pilot sidescan-sonar survey. Raw digital-backscatter data were processed with QTC SIDEVIEW and CLAMS software. Resultant acoustic variables—Q-values (Q1, Q2, and Q3), representing the first three principal components of the data derived from image analysis of backscatter echoes, and a complexity metric (compx) measuring the variance of Q-values in a geographic area—were used in multiple linear regression to model individual species abundance from bottom-trawl survey data. Habitat models for flathead sole (Hippoglossoides elassodon), Pacific cod (Gadus macrocephalus), walleye pollock (Theragra chalcogramma), red king crab (Paralithodes camtschaticus), basket star (Gorgonocephalus eucnemis), and sponges (Porifera) included acoustic variables as significant predictors. For these six taxa, full models explained 67–86% of variability in abundance, with 9–54% of that total contributed by the acoustic predictors, suggesting that acoustic data could advance habitat research for some bottom-associated marine species.