Modeling environmentally driven uncertainties in Baltic cod (Gadus morhua) management by Bayesian influence diagrams

Abstract

The large variability in Baltic cod (Gadus morhua) recruitment has been attributed both to environmental factors dependent on the inflow of saline water (oxygen and salinity in spawning deeps) and to the size of the spawning stock. Due to the complex interactions between hydrographic and biological processes, future recruitment levels of cod will remain highly uncertain and increase uncertainties in stock predictions and management advice. We assessed the effects of the exploitation level and mesh size used by a trawl fishery on some variables of management interest under different environmental conditions. The modeling consisted of three separate steps: (i) modeling of selectivity, (ii) estimation of uncertainties by Monte Carlo simulations, and (iii) decision analysis by Bayesian influence diagrams, focusing on the structural uncertainties and model selection. Realistic assumptions of environmental conditions and present fishing mortality rates suggest that the current Baltic cod fishery is unsustainable. We use our approach to identify robust management measures that reduce the risk of overfishing and the sensitivity to management information. The value of information analysis demonstrates the advantages of a larger mesh size as a management measure.