Tracking 4 years in the life of a female whale shark shows consistent migrations in the Gulf of Mexico and Caribbean

Abstract

Context: Satellite telemetry has revolutionised the study of animal movement, particularly for mobile marine animals, whose movements and habitat make consistent, long-Term observation difficult. Aims: Summarise the movements of Rio Lady, a mature female whale shark (Rhincodon typus), to characterise these movements, and to predict expected behaviour throughout the Gulf of Mexico (GOM). Methods: Rio Lady was tracked using satellite telemetry for over 1600 days, generating over 1400 locations and travelling over 40,000 km. State-space and move persistence modelling enabled characterisation of behaviour, and machine learning (ML) enabled the development of habitat-suitability models to predict habitat utilisation, on the basis of location transmissions and their environmental covariates. Key results: Rio Lady exhibited annually consistent patterns of movements among three regions within the GOM. Final ML models produced seasonally dynamic predictions of habitat use throughout the GOM. Conclusions: The application of these methods to long-Term location data exemplifies how long-Term movement patterns and core areas can be discovered and predicted for marine animals. Implications: Despite our limited dataset, our integrative approach advances methods to summarise and predict behaviour of mobile species and improve understanding of their ecology.