Behavior Change Interventions to Reduce Illegal Fishing

Illegal fishing is a serious problem that threatens the sustainability of fisheries around the world. Policy makers and fishery managers often rely on the imposition of strict sanctions and relatively intensive monitoring and enforcement programs to increase the costs of illegal behavior and thus deter it. However, while this can be successful in fisheries with sufficient resources to support high levels of surveillance and effective systems for imposing penalties, many fisheries lack the resources and requisite governance to successfully deter illegal fishing. Other types of governance systems, such as customary marine tenure and co-management, rely more on mechanisms such as norms, trust, and the perceived legitimacy of regulations for compliance. More generally, the absence of such social and psychological factors that encourage compliance in any fishery can undermine the efficacy of an otherwise effective and well-designed fishery management system. Here we describe insights from behavioral science that may be helpful in augmenting and securing the effectiveness of conventional deterrence strategies as well as in developing alternative means of deterring illegal fishing in fisheries in which high levels of surveillance and enforcement are not feasible. We draw on the behavioral science literature to describe a process for designing interventions for changing specific illegal fishing behaviors. The process begins with stakeholder characterization to capture existing norms, beliefs, and modes of thinking about illegal fishing as well as descriptions of specific illegal fishing behaviors. Potential interventions that may disrupt the beliefs, norms, and thought modes that give rise to these behaviors, along with those that encourage desirable behaviors, can be developed by applying principles gleaned from the behavioral science literature. These potential interventions can then be tested in artefactual experiments, piloted with small groups of actual stakeholders and, finally, implemented at scale.