Abstract

We describe a method to allow acoustic sampling at depths not reachable by the higher frequencies of ship hull-mounted echosounders and observe the abundance and behaviour of individual organisms in front of trawls. A self-contained scientific echosounder with a 120 kHz transducer was mounted forward-facing on the headline of a macrozooplankton trawl that was obliquely towed from 0 to 1000 m depth, to investigate the mesopelagic fauna. With the use of a forward-facing echosounder, we were able to estimate organism densities in front of the trawl, the vertical profiles of organism target strength and the movement of organisms in front of the trawl. We demonstrate that a forward-facing trawl-mounted echosounder is a simple and useful method to investigate the distribution of mesopelagic fauna at depth.

Highlights

  • The mesopelagic zone is broadly defined as the part of the ocean located between 200 and 1000 m depth (Sutton, 2013), recently it has been suggested that light intensity could be a better definition (Kaartvedt et al, 2019)

  • This paper describes a method to allow acoustic sampling at depths that are not accessible to the higher frequencies of hull-mounted echosounders, and to observe the behaviour of individuals in front of the trawl

  • Our results demonstrate that a trawl-mounted echosounder is a useful tool to investigate the vertical and spatial distribution of meso­ pelagic organisms

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Summary

Introduction

The mesopelagic zone is broadly defined as the part of the ocean located between 200 and 1000 m depth (Sutton, 2013), recently it has been suggested that light intensity (ranging from 10− 9 to 10− 1 μmol quanta m− 2s− 1) could be a better definition (Kaartvedt et al, 2019). The global mesopelagic fish biomass (primarily using net catch data) was estimated to be around 109 t wet mass (Gjøsæter and Kawaguchi, 1980; Lam and Pauly, 2005). Knowledge of the composition and acoustic properties of the mesopelagic community is most likely necessary to accurately estimate mesopelagic fish biomass (Davison et al, 2015)

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