An individual-based model study of anchovy early life history in the northern Humboldt Current system

We used an individual-based model of anchovy (Engraulis ringens) early life history coupled with hydrodynamic outputs from the regional oceanic modeling system (ROMS) to investigate the factors driving variability in egg and larval survival rates in the northern Humboldt upwelling region off Peru. Individuals were released within a coastal area and followed for a period of 30 days. Those that were still in the coastal area at that time were considered as retained. We investigated the spatial and temporal variability in the release locations of the individuals retained, and compared these to observed egg concentration patterns reconstructed from a 40-year period of monitoring. A first set of simulations using passive particles to represent anchovy eggs and larvae revealed a large sensitivity of the results to the initial vertical distribution of particles. We then conducted two additional sets of simulations that included the effect of egg buoyancy, larval vertical swimming behavior and lethal temperature. We obtained (1) maximal coastal retention close to the surface in winter and in deeper layers in summer, (2) a large influence of egg buoyancy and of larval vertical behavior on coastal retention in all seasons, (3) a partial match between dates and locations of enhanced retention and observed egg concentration patterns and (4) a low effect of lethal temperature on survival except when associated with high egg density. The model suggests that an optimal temporal spawning pattern for maximizing coastal retention would have two maximums, the most significant in austral winter and the second in summer. This pattern agrees roughly with observed spawning seasonality, but with temporal discrepancy of about two months in the peaks of both series. Spatially, we obtained higher retention from 10 S to 20 S, whereas the observed maximum egg concentration was located between 6°S and 14°S. Among the three sets of simulations, the one taking into account larval vertical swimming behavior lead to the best match with the data.