Literature DB >> 25013109

Use of a gyroscope/accelerometer data logger to identify alternative feeding behaviours in fish.

Yuuki Kawabata1, Takuji Noda2, Yuuki Nakashima3, Atsushi Nanami4, Taku Sato4, Takayuki Takebe4, Hiromichi Mitamura2, Nobuaki Arai2, Tomofumi Yamaguchi5, Kiyoshi Soyano3.   

Abstract

We examined whether we could identify the feeding behaviours of the trophic generalist fish Epinephelus ongus on different prey types (crabs and fish) using a data logger that incorporated a three-axis gyroscope and a three-axis accelerometer. Feeding behaviours and other burst behaviours, including escape responses, intraspecific interactions and routine movements, were recorded from six E. ongus individuals using data loggers sampling at 200 Hz, and were validated by simultaneously recorded video images. For each data-logger record, we extracted 5 s of data when any of the three-axis accelerations exceeded absolute 2.0 g, to capture all feeding behaviours and other burst behaviours. Each feeding behaviour was then identified using a combination of parameters that were derived from the extracted data. Using decision trees with the parameters, high true identification rates (87.5% for both feeding behaviours) with low false identification rates (5% for crab-eating and 6.3% for fish-eating) were achieved for both feeding behaviours.
© 2014. Published by The Company of Biologists Ltd.

Entities:  

Keywords:  Accelerometer; Angular velocity; Biologging; Forage; Inertial sensor; Telemetry

Mesh:

Year:  2014        PMID: 25013109     DOI: 10.1242/jeb.108001

Source DB:  PubMed          Journal:  J Exp Biol        ISSN: 0022-0949            Impact factor:   3.312


  4 in total

1.  Using tri-axial accelerometer loggers to identify spawning behaviours of large pelagic fish.

Authors:  Thomas M Clarke; Sasha K Whitmarsh; Jenna L Hounslow; Adrian C Gleiss; Nicholas L Payne; Charlie Huveneers
Journal:  Mov Ecol       Date:  2021-05-24       Impact factor: 3.600

2.  Development and application of a machine learning algorithm for classification of elasmobranch behaviour from accelerometry data.

Authors:  L R Brewster; J J Dale; T L Guttridge; S H Gruber; A C Hansell; M Elliott; I G Cowx; N M Whitney; A C Gleiss
Journal:  Mar Biol       Date:  2018-03-08       Impact factor: 2.573

3.  Calibrating Accelerometer Tags with Oxygen Consumption Rate of Rainbow Trout (Oncorhynchus mykiss) and Their Use in Aquaculture Facility: A Case Study.

Authors:  Walter Zupa; Sébastien Alfonso; Francesco Gai; Laura Gasco; Maria Teresa Spedicato; Giuseppe Lembo; Pierluigi Carbonara
Journal:  Animals (Basel)       Date:  2021-05-21       Impact factor: 2.752

4.  Interpreting behaviors from accelerometry: a method combining simplicity and objectivity.

Authors:  Philip M Collins; Jonathan A Green; Victoria Warwick-Evans; Stephen Dodd; Peter J A Shaw; John P Y Arnould; Lewis G Halsey
Journal:  Ecol Evol       Date:  2015-10-02       Impact factor: 2.912

  4 in total

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