Adult-mediated connectivity affects inferences on population dynamics and stock assessment of nursery-dependent fish populations

We explore how alternative hypotheses on the degree of mixing among local subpopulations affect statistical inferences on the dynamics and stock assessmentof a harvested flatfishpopulation, namely, the common solepopulation in the Eastern Channel (ICES area VIId). The current paradigm considers a single, well-mixed, spatially homogeneous population with juveniles from all coastal nursery grounds along the French and UK coasts that contribute to a single adult population and one pool of eggs. Based on the available data and ecological knowledge, we developed a spatial Bayesian integrated life-cycle model that consists of three subpopulations (one near the UK coast and two near the French coast, denoted UK, West FR and East FR, respectively) supported by their respective local nurseries, with the connectivity among the three components limited to low exchanges during larval drift. Considering the population dynamics among three subpopulations (instead of a single homogeneous one) drastically changes our inferences on the productivity of nursery sectors and their relative contribution to total recruitment. Estimates of the East FR subpopulation’s contribution to total recruitment increase (29% in the single population model; 48% in the three subpopulation model), balanced by a decrease in the UK subpopulation’s contribution (53%; 34%). Whereas an assessment based on the hypothesis of a single spatially homogeneous population in the EC indicates exploitation far above MSY (current F/FMSY = 1.8), an assessment that considers a metapopulationwith three loosely connected subpopulations revealed a different status, with the UK and East FR subpopulations being exploited above MSY (current F/FMSY = 1.9 and 2, respectively) and the West FR subpopulation approaching full exploitation (current F/FMSY = 1.05). This approach contributes to the quantitative assessment of spatial fishery and coastal habitat management plans.