An app as a tool for detecting migrant females of Anguilla anguilla to support the wild population

Authors

  • Antonio Casalini University of Bologna
  • Laura Gentile
  • Pietro Emmanuele
  • Riccardo Brusa
  • Chiara Fusaroli
  • Matteo Lucchi
  • Tiberio Tonetti
  • Oliviero Mordenti

DOI:

https://doi.org/10.21014/actaimeko.v12i4.1696

Keywords:

european eel, machine learning, conservation, silver index

Abstract

The eel (Anguilla anguilla) population in Europe has declined dramatically since the 1980s and shows no signs of recovery. There are several threats to this species: migratory barriers, loss of habitats, hydroelectric dams, overfishing, and illegal trade. As a result, the eel has become part of the ICUN endangered species and is protected by various institutions. Information data on the maturation stage is needed to monitor silver eel escapement and assess population trends. In the sampling activities spanning from 2012 to 2022 silver index was calculated on 1852 eels in the northern Adriatic Sea. With the help of machine learning technology, we trained an algorithm in pupil recognition and the calculation of horizontal eye diameter in eels. This study allowed us: a) to identify a single parameter to discriminate the sexual maturity of the eel and thus to know the female with a migratory instinct; b) to use this parameter as a proxy to develop an easy and user-friendly app for all management operators.

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Published

2023-12-12

Issue

Vol. 12 No. 4 (2023)

Section

Research Papers

License

Copyright (c) 2023 Antonio Casalini, Laura Gentile, Pietro Emmanuele, Riccardo Brusa, Chiara Fusaroli, Matteo Lucchi, Tiberio Tonetti, Oliviero Mordenti

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