Biophysical modelling for recruitment prediction

Exploited fish populations are dependent on recruitment (i.e. size of the new year class) to sustain their abundance. Recruitment variations are related to hydroclimatic variations and may accentuate the detrimental effects of fishing. Recruitment prediction requires accurate fisheries oceanographic tools, which are expected to be more reliable than large-scale correlation analyses between fish abundance and climate variables. Recruitment is the result of the integration over a season and large oceanic areas of processes affecting larval survival, which are dependent on small-scale mechanisms. Hydrodynamic models are a tool to perform this integration. This thesis aims at exploring and modelling physical-biological interaction mechanisms in order to provide recruitment predictions usable for fisheries management. This thesis integrates into general scientific problematics in ecology, variability analysis and spacetime scale integration. It is applied to the case of Anchovy (Engraulis encrasicolus) in the Bay of Biscay, an important social and economic resource for Spain and France. Due to the short life of the species, the fishery mainly relies on the success of annual recruitment. The methodology developed proceeds in three stages : 1. Exploration of biophysical interactions and modelling of growth and survival at the individual scale. To tackle larval survival mechanisms, the main data available are past growth (otolith) records of individuals sampled at sea. The drift history of these individuals is reconstructed by a back-tracking procedure using hydrodynamic simulations. Along the individual trajectories obtained, the relationships between real growth variation and variations in physical parameters (estimated by hydrodynamic simulations) are explored. These relationships are then used to build and adjust individual-based growth and survival models. 2. Simulation and integration from individual to population scale, leading to recruitment prediction. Thousands of virtual buoys are released in the hydrodynamic model in order to reproduce the space-time spawning dynamics. Along the buoy trajectories (representative of micro-cohorts), the biophysical model is run to simulate growth and survival as a function of environment encountered. The survival rate after three months of drift is estimated for each micro-cohort. The sum of all these survival rates over the season constitutes an annual recruitment index. This index is successfully validated over a series of recruitment estimations. 3. Biophysical simulation analyses. Space-time survival windows are first localised and analysed, which highlights the main mechanisms responsible for recruitment variability at the different scales: retention of larvae and juveniles in favourable habitats over the shelf margins and turbulence effects. These mechanisms are related to the variations of wind direction and intensity during spring and summer. The biophysical simulator is then used to study the properties of the interaction between the population (influence on spawning) and its environment (influence on survival). The differences between the real spawning distribution (according to field surveys) and the spawning distribution that would maximise survival (according to the biophysical model) reveal the effects of the abundance and spawning behaviour of the different age classes. The simulator shows the influence of spawning strategies (i.e. of the stock demography) on recruitment on a multiannual scale and its theoretical implications on the mid-term dynamics of the population interacting with a variable environment.