Whistle characteristics and species classification algorithm for delphinids in the Southwestern Atlantic Ocean

Authors

  • Diogo D. Barcellos Laboratório de Biologia da Conservação de Mamíferos Aquáticos - Instituto Oceanográfico - Universidade de São Paulo (São Paulo - Praça do Oceanográfico, 191, sala 145 - 05508-120 - SP - Brazil).
  • Marcos C. de O. Santos Laboratório de Biologia da Conservação de Mamíferos Aquáticos - Instituto Oceanográfico - Universidade de São Paulo (São Paulo - Praça do Oceanográfico, 191, sala 145 - 05508-120 - SP - Brazil).

DOI:

https://doi.org/10.1590/2675-2824074.25171

Keywords:

Dolphins, Species identification, Whistle repertoire, Passive acoustic monitoring

Abstract

This study investigates the whistle characteristics of six delphinid species in the Southwestern Atlantic Ocean and develops a classification algorithm to distinguish among them. Acoustic recordings were collected along the coast of São Paulo for common dolphins (Delphinus delphis), orcas (Orcinus orca), Atlantic spotted dolphins (Stenella frontalis), and common bottlenose dolphins (Tursiops truncatus). Recordings of spinner dolphins (Stenella longirostris) were obtained from the Fernando de Noronha Archipelago, while Guiana dolphins (Sotalia guianensis) were recorded in the Cananéia Estuary, in southern São Paulo. A total of 1,797 whistles were analyzed using seven acoustic parameters: duration (ms), and minimum, maximum, delta, center, initial, and final frequencies (kHz). These acoustic features were classified using a Random Forest algorithm, which achieved an overall classification accuracy of 55%. The highest accuracy was observed for D. delphis (73.6%), followed by S. guianensis (65%) and S. frontalis (55%). These findings represent a meaningful step toward the development of whistle classification tools and support the potential use of passive acoustic monitoring for long-term studies of delphinid populations in the Southwestern Atlantic Ocean.

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Published

31.07.2026

How to Cite

Whistle characteristics and species classification algorithm for delphinids in the Southwestern Atlantic Ocean. (2026). Ocean and Coastal Research, 74. https://doi.org/10.1590/2675-2824074.25171