Sources de variation intra-populationelle de la morphologie des otolithes: asymétrie directionnelle et régime alimentaire

Otoliths are calcified structures located in Osteichthyes’ inner ear that are involved in audition and balance. Their morphology is used as an indicator of various ecological processes or properties. This application requires identifying the endogenous and exogenous factors that act simultaneously as sources of shape variation. This thesis aims at detecting and quantifying the relative contributions of directional asymmetry and diet to otolith shape variation at the intra-population level. Directional asymmetry between left and right otoliths was found in flat-fishes, the blind-side otolith being always longer and larger, whereas it was negligible in round-fishes. However, asymmetry amplitude never exceeded 18 %, which suggests evolutionary canalization of otolith shape symmetry. A correlation between global diet and otolith was detected in 4 species studied in situ. Diet composition contributed more than food amount to morphological variation and affected otolith shape both globally and locally. An experimental study on sea bass (Dicentrarchus larbrax) showed that diet composition in terms of essential polyunsaturated fatty acids at larval stage affects otolith morphogenesis during juvenile stage without impacting on individuals’ somatic growth. This result suggests a direct effect of diet on otolith shape and not an indirect one through the somatic-otolith growth relationship. This effect disappeared at later stages, morphogenetic trajectories converging back to a similar shape, which suggests ontogenetic canalization of otolith shape.

Explaining dinophysis cf. acuminata abundance in Antifer (Normandy, France) using dynamic linear regression

Classical regression analysis can be used to model time series. However, the assumption that model parameters are constant over time is not necessarily adapted to the data. In phytoplankton ecology, the relevance of time-varying parameter values has been shown using a dynamic linear regression model (DLRM). DLRMs, belonging to the class of Bayesian dynamic models, assume the existence of a non-observable time series of model parameters, which are estimated on-line, i.e. after each observation. The aim of this paper was to show how DLRM results could be used to explain variation of a time series of phytoplankton abundance. We applied DLRM to daily concentrations of Dinophysis cf. acuminata, determined in Antifer harbour (French coast of the English Channel), along with physical and chemical covariates (e.g. wind velocity, nutrient concentrations). A single model was built using 1989 and 1990 data, and then applied separately to each year. Equivalent static regression models were investigated for the purpose of comparison. Results showed that most of the Dinophysis cf. acuminata concentration variability was explained by the configuration of the sampling site, the wind regime and tide residual flow. Moreover, the relationships of these factors with the concentration of the microalga varied with time, a fact that could not be detected with static regression. Application of dynamic models to phytoplankton time series, especially in a monitoring context, is discussed.