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bioRxiv · 10.1101/2023.04.16.537064

An open and lightweight method to analyze the vertical distribution of pelagic organisms using echogram screenshots

Bahlburg, D.·Boehrer, T.·Hueppe, L.
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Abstract

Multifrequency echosounders are versatile devices commonly used in commercial fisheries, fisheries science and biological oceanography for the detection, quantification and even identification of organisms suspended in the underlying water column. They produce data that is rich in information, but can be tedious to process, often relying on expensive commercial software. The aim of our overarching research project was to analyze the vertical distribution of Antarctic krill swarms (Euphausia superba) in different seasons and regions in order to learn more about their behavioral ecology and ecophysiological adaptation. Therefore, we only required visual information on the distribution of krill swarms as well as metrics that characterize their vertical position. Instead of using storageintensive raw acoustic data, we developed a simple method to extract the relevant information from screenshots taken automatically on board a commercial krill fishing vessel during its operations. Using screenshots instead of raw data reduced the amount of data by a factor of >1000 (3 TB of raw data vs. 2.8 GB of screenshots for 8 months of observations) while preserving the information needed to carry out our seasonal behavioral analyses. In this study, we present the workflow and demonstrate that our method produces qualitatively and quantitatively similar results to using raw data, while being much less demanding in terms of computation and data storage. The code for the data processing is written in the open source programming language R, publicly accessible and therefore, provides a useful resource for other scientists interested in the dynamics of vertical biomass distributions from echosounder data.

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Bahlburg, D., Boehrer, T., Hueppe, L.. 2023-04-18. An open and lightweight method to analyze the vertical distribution of pelagic organisms using echogram screenshots. https://doi.org/10.1101/2023.04.16.537064

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