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Hide and seek shark teeth in Random Forests: Machine learning applied to Scyliorhinus canicula populations

  • Shark populations that are distributed alongside a latitudinal gradient often display body size differences at sexual maturity and vicariance patterns related to their number of tooth files. Previous works have demonstrated that Scyliorhinus canicula exhibits distinct genetic structures, life history traits, and body size differences between populations inhabiting the North Atlantic Ocean and the Mediterranean Sea. In this work, we sample more than 3,000 S. canicula teeth from 56 specimens and provide and use a dataset containing their shape coordinates. We investigate tooth shape and form differences between a Mediterranean and an Atlantic S. canicula population using two approaches. Classification results show that the classical geometric morphometric framework is outperformed by an original Random Forests-based framework. Visually, both S. canicula populations share similar ontogenetic trends and timing of gynandric heterodonty emergence but the Atlantic population has bigger, blunter teeth, and less numerous accessory cusps than the Mediterranean population. According to the models, the populations are best differentiated based on their lateral tooth edges, which bear accessory cusps, and the tooth centroid sizes significantly improve classification performances. The differences observed are discussed in light of dietary and behavioural habits of the populations considered. The method proposed in this study could be further adapted to complement DNA analyses to identify shark species or populations based on tooth morphologies. This process would be of particular interest for fisheries management and identification of shark fossils.

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Author:Fidji Berio, Yann Bayle, Daniel BaumORCiD, Nicolas Goudemand, Mélanie Debiais-Thibaud
Document Type:Article
Parent Title (English):PeerJ - Aquatic Biology
First Page:10:e13575
Date of first Publication:2022/07/04
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