Incorporating environmental variability in a spatially-explicit individual-based model of European sea bass✰

The northern stock of European sea bass (Dicentrarchus labrax) is a large, high value, slow growing and late maturing fish that an important target species for both commercial recreational fisheries. Around the UK, scientific assessments have shown rapid eight-year decline in spawning biomass since 2010 attributed to poor recruitment; this was likely driven by environmental factors fishing mortality. Management informed which population model fitted available data used forecast possible consequences various catch options. However, currently cannot represent spatial distribution or any effects variability. One approach may be temporal variation drivers with Individual based models (IBMs). In IBMs populations are represented their constituent individuals interact environment each other. mechanistic nature often advantageous as management tool complex systems including Here we add existing IBM produce spatio-temporally explicit individual respond local food supply surface temperature. All life stages (i.e., pelagic stages, juvenile mature fish) modelled own realistic energy budgets observed dynamic maps phytoplankton density calibrated using Approximate Bayesian Computation (ABC). After calibration ABC gives good fits key parameters biomass. provides link between supplies temperatures overall dynamics. Plots show how uses budget predict change response Our results indicate promising could support assessment scope testing range spatially temporally scenarios addition responses novel change.