The acoustic multifrequency classification of two sympatric euphausiid species (Meganyctiphanes norvegica and Thysanoessa raschii), with empirical and SDWBA model validation

• Published in: ICES Journal of Marine Science
• Main Authors: McQuinn, Ian H., Dion, Maxime, St. Pierre, Jean-François
• Format: Article in Journal/Newspaper
• Language: English
• Published: Oxford University Press (OUP) 2013
• Subjects: Ecology; Aquatic Science; Ecology, Evolution, Behavior and Systematics; Oceanography; Arctic krill; Arctic; Meganyctiphanes norvegica; Northern krill; Thysanoessa raschii
• Online Access: http://dx.doi.org/10.1093/icesjms/fst004; http://academic.oup.com/icesjms/article-pdf/70/3/636/29145888/fst004.pdf

Abstract McQuinn, I. H., Dion, M., and St. Pierre, J.-F. 2013. The acoustic multifrequency classification of two sympatric euphausiid species (Meganyctiphanes norvegica and Thysanoessa raschii), with empirical and SDWBA model validation. – ICES Journal of Marine Science, 70: 636–649. The ecosystem approach to fishery management requires monitoring capabilities at all trophic levels, including pelagic organisms. However, the usefulness of active acoustics for ecosystem monitoring has been limited by ambiguities in the identification of scattering layers. Increasingly, multifrequency acoustic methods are being developed for the classification of scattering layers into species or species groups. We describe a method for distinguishing between sympatric northern and Arctic krill (Meganyctiphanes norvegica and Thysanoessa raschii) using sv amplitude ratios from 38, 120, and 200 kHz data which were pre-processed through a self-noise removal algorithm. Acoustic frequency responses of both euphausiid species were predicted from species-specific parameterizations of a SDWBA physical model using specific body forms (shape, volume, and length) for Arctic and northern krill. Classification and model validation were achieved using macrozooplankton samples collected from multiple-sampler (BIONESS) and ringnet (JackNet) hauls, both equipped with a strobe light to reduce avoidance by euphausiids. SDWBA frequency responses were calculated for a range of orientations (± 45°) and compared with observed frequency responses, solving for orientation by least squares. A tilt angle distribution of N[9°,4°] and N[12°,6°] for T. raschii and M. norvegica, respectively resulted in best fits. The models also provided species-specific TS–length relationships.