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A HMM-based model to geolocate pelagic fish from high-resolution individual temperature and depth histories: European sea bass as a case study ArchiMer
Woillez, Mathieu; Fablet, Ronan; Tran-thanh Ngo,; Lalire, Maxime; Lazure, Pascal; De Pontual, Helene.
Numerous methods have been developed to geolocate fish from data storage tags. Whereas demersal species have been tracked using tide-driven geolocation models, pelagic species which undertake extensive migrations have been mainly tracked using light-based models. Here, we present a new HMM-based model that infers pelagic fish positions from the sole use of high-resolution temperature and depth histories. A key contribution of our framework lies in model parameter inference (diffusion coefficient and noise parameters with respect to the reference geophysical fields—satellite SST and temperatures derived from the MARS3D hydrodynamic model), which improves model robustness. As a case study, we consider long time series of data storage tags (DSTs) deployed on...
Tipo: Text Palavras-chave: Fish movement; Archival tagging; Migration; Population structure; Hidden Markov Model (HMM); State-space model.
Ano: 2016 URL:
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