| Summary: | International audience The reconstruction of individual life histories from chemical otolith measures was stated as an unsupervised signal processing issue embedded in a Bayesian framework. This computational methodology was applied to a set of 192 eel (Anguilla anguilla) otoliths. It provided a robust and unsupervised analysis of the individual chronologies of habitat use (either river, estuary or coastal) from Sr:Ca measures acquired along an otolith growth axis. Links between Sr:Ca values and habitat, age and season, and the likelihood of the transitions from one habitat type to another were modelled. Major movement characteristics such as age at transition between habitats and time spent in each habitat were estimated. As a straightforward output, an unsupervised classification of habitat use patterns showed a great variability. Using a hidden Markov model, 37 patterns of habitat use were found, with 20 different patterns accounting for 90% of the sample. In accordance with literature, residence behaviour was observed (28% of the eels). However, about 72% changed habitat once or of several times, mainly before age four. The potential application of this method to any other measures taken along an otolith growth axis to reconstruct individual chronologies gives a new insight in life history tactics analysis. La reconstruction des histoires de vies s'appuyant sur des mesures chimiques d'otolithes a été traitée comme un problème de traitement du signal non supervisé dans un cadre Bayésien. Cette méthode numérique a été appliquée à un jeu de 192 données d'otolithes d'anguille (Anguilla anguilla). Une analyse robuste et non supervisée des chronologies d'utilisation des habitats (soit de rivière, d'estuaire ou côtiers) a été obtenue à partir des mesures Sr :Ca acquises le long d'un axe de croissance de l'otolithe. Les liens entre les valeurs Sr :Ca, les habitats, l'âge, la saison et les probabilités de transition d'un habitat à un autre ont été modélisés. Des caractéristiques importantes telles que l'âge à la ...
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