Combining exploratory scenarios and Bayesian belief networks to model social-ecological systems - case study on Baltic herring and salmon fisheries

We developed exploratory scenarios for the future state of the Baltic herring and salmon fisheries in 2040. The main focus was on fisheries management and their contributions to food security and safety objectives. We compiled four alternative storylines for the future states based on how identified societal (social, technological, environmental, economic, political, and value-based) drivers, and related pressures, states, impacts and responses behave under different combinations of selected key uncertainties, which were 1) integrated vs. fragmented governance, and 2) extend of human impact. The aim of this paper is to combine the exploratory scenarios and Bayesian belief network (BBN) to structure and examine quantitatively the implications of changes in the societal driving forces to the social-ecological system (SES) and ultimately to the fisheries management objectives. For this purpose, we created a BBN scenario synthesis model, which covers all possible combinations of the states of the scenario-forming factors and visualizes the assumed causalities between them. In this model, co-occurrence of certain states are more likely than some other combinations, and the model – when populated with probabilities – weighs the scenarios based on their realization probabilities. The results unravel synergies and trade-offs between the management objectives under multiple alternative scenarios given certain societal conditions in 2040. We conclude that combining exploratory scenarios and BBN can provide useful information for the long-term sustainable management of environmental resources by improving understanding of the SES dynamics and especially of the societal drivers that could potentially bring about change.