Abstract
AEI Aquaculture Environment Interactions Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections AEI 4:81-90 (2013) - DOI: https://doi.org/10.3354/aei00075 Three-dimensional trajectories of cultivated Pacific bluefin tuna Thunnus orientalis in an aquaculture net cage Kazuyoshi Komeyama1,*, Minoru Kadota2,3,*, Shinsuke Torisawa2, Tsutomu Takagi2,** 1Faculty of Fishery, Kagoshima University, 4-50-20 Shimoarata, Kagoshima 890-0056, Japan 2Department of Fisheries, Faculty of Agriculture, Kinki University, 3327-204 Naka-machi, Nara 631-8505, Japan 3Temple University, 4-1-27 Mita, Minato-ku, Tokyo 109-0073, Japan *These authors contributed equally to this work**Corresponding author. Email: tutakagi@nara.kindai.ac.jp ABSTRACT: Swimming trajectories of aquatic animals that are estimated using the dead-reckoning technique below the sea surface tend to have very large associated observational errors. Therefore, the aim of the present study was to develop a technique for removing accumulated errors from such trajectories for Pacific bluefin tuna Thunnus orientalis. Horizontal and vertical speeds and heading angle were measured in an aquaculture net cage using 2 types of data loggers, and current velocity was recorded at a depth of 12 m to measure the tidal current speed around the net cage. Fourier analysis indicated that the primary source of error in trajectory estimates was the effect of ocean currents, which resulted in drift, and further analysis revealed that the frequency contributing to drift was consistent with the low-frequency signal in a spectrum analysis of horizontal speed. Therefore, a high-pass filter was applied to horizontal speed data to remove any frequencies lower than the cut-off frequency (0.0015 Hz), following which these data were back-transformed into a time domain that no longer included the drift effect caused by the current. The reconstructed trajectories fit within the inner diameters of the net cage, indicating that they were realistic. To confirm the validity of the resultant swimming trajectories, a flume tank experiment was conducted, which demonstrated that the high-pass filter effectively removed current drift from the estimated trajectory. Furthermore, since the method was estimated to have a precision of approximately 0.20 m, it not only allows the 3-dimensional trajectories of circling tuna to be estimated but can also be applied to the behavior of fish in the wild. KEY WORDS: Dead reckoning · Behaviour · Submerged net cage Full text in pdf format PreviousCite this article as: Komeyama K, Kadota M, Torisawa S, Takagi T (2013) Three-dimensional trajectories of cultivated Pacific bluefin tuna Thunnus orientalis in an aquaculture net cage. Aquacult Environ Interact 4:81-90. https://doi.org/10.3354/aei00075 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in AEI Vol. 4, No. 1. Online publication date: June 26, 2013 Print ISSN: 1869-215X; Online ISSN: 1869-7534 Copyright © 2013 Inter-Research.
Highlights
Aquaculture net cages for Pacific bluefin tuna Thunnus orientalis are currently designed to withstand rough conditions from ocean currents and waves (Suzuki et al 2009) but do not meet the biological requirements of this species
Two techniques are currently available for examining the movements of aquatic animals below the sea surface: acoustic telemetry (e.g. Hindell et al 2002) and dead reckoning (Wilson & Wilson 1988, Shiomi et al 2008, Komeyama et al 2011)
It should be noted that ocean currents fluctuate over short periods, but this high-frequency fluctuation was ignored as noise for the purpose of reconstructing the 3D tuna trajectories in the present study, as we were only concerned with a time scale of a few minutes to a few hours
Summary
Aquaculture net cages for Pacific bluefin tuna Thunnus orientalis are currently designed to withstand rough conditions from ocean currents and waves (Suzuki et al 2009) but do not meet the biological requirements of this species. Harcourt et al 2000, Hindell et al 2002, Bégout Anras & Lagardère 2004) This method has several drawbacks, including that a receiver must be located within a few hundred meters of the target fish, making it difficult to obtain data for species with extensive ranges (Wilson et al 2007); it is difficult to affix acoustic receivers in offshore areas; ocean waves and oscillations of the hydrophones by waves generate acoustic noise; changes in water temperature in the thermocline strongly affect the acoustic velocity; it is difficult to continuously detect the signal at a fine scale (i.e. a few seconds) to estimate high-resolution fish trajectories. Acoustic telemetry has the advantage of directly measuring the position of fish, it may be difficult to measure fish behavior with a high accuracy and over a fine time scale in offshore areas
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