Journal Article
The use of machine learning to detect foraging behaviour in whale sharks: a new tool in conservation
Darren A. Whitehead; Felipe G. Magaña; James T. Ketchum; Edgar M. Hoyos; Rogelio G. Armas; Francesca Pancaldi; Damien Olivier
Journal of Fish Biology · Vol. 98, Issue 3 · pp. 865-869 · 2021
Abstract
In this study we present the first attempt at modelling the feeding behaviour of whale sharks using a machine learning analytical method. A total of eight sharks were monitored with tri‐axial accelerometers and their foraging behaviours were visually observed. Our results highlight that the random forest model is a valid and robust approach to predict the feeding behaviour of the whale shark. In conclusion this novel approach exposes the practicality of this method to serve as a conservation tool and the capability it offers in monitoring potential disturbances of the species.
Bibliographic Information
| Journal | Journal of Fish Biology |
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| Publisher | Wiley |
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| Publication Date | 2021-03-01 |
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| Publication Year | 2021 |
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| Volume | 98 |
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| Issue | 3 |
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| Pages | 865-869 |
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| Document Type | Journal Article |
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| Print ISSN | 0022-1112 |
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| eISSN | 1095-8649 |
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| DOI | 10.1111/jfb.14589 |
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| Subject | General Aquaculture, Fisheries & Fish Science |
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