  We review a success story regarding Bayesian inference in fisheries
management in the Baltic Sea. The management of salmon fisheries is currently
based on the results of a complex Bayesian population dynamic model, and
managers and stakeholders use the probabilities in their discussions. We also
discuss the technical and human challenges in using Bayesian modeling to give
practical advice to the public and to government officials and suggest future
areas in which it can be applied. In particular, large databases in fisheries
science offer flexible ways to use hierarchical models to learn the population
dynamics parameters for those by-catch species that do not have similar large
stock-specific data sets like those that exist for many target species. This
information is required if we are to understand the future ecosystem risks of
fisheries.
