A multi-criteria decision analysis model for ship biofouling management in the Baltic Sea.

Biofouling of ship hulls form a vector for the introduction of non-indigenous organisms worldwide. Through increasing friction, the organisms attached to ships' hulls increase the fuel consumption, leading to both higher fuel costs and air emissions. At the same time, ship biofouling management causes both ecological risks and monetary costs. All these aspects should be considered case-specifically in the search of sustainable management strategies. Applying Bayesian networks, we developed a multi-criteria decision analysis model to compare biofouling management strategies in the Baltic Sea, given the characteristics of a ship, its operating profile and operational environment, considering the comprehensive environmental impact and the monetary costs. The model is demonstrated for three scenarios (SC1-3) and sub-scenarios (A-C), comparing the alternative biofouling management strategies in relation to NIS (non-indigenous species) introduction risk, eco-toxicological risk due to biocidal coating, carbon dioxide emissions and costs related to fuel consumption, in-water cleaning and hull coating. The scenarios demonstrate that by the careful consideration of the hull fouling management strategy, both money and environment can be saved. We suggest biocidal-free coating with a regular in-water cleaning using a capture system is generally the lowest-risk option. The best biocidal-free coating type and the optimal in-water cleaning interval should be evaluated case-specifically, though. In some cases, however, biocidal coating remains a justifiable option.

Incorporating stakeholders' values into environmental decision support: A Bayesian Belief Network approach.

Participatory modelling increases the transparency of environmental planning and management processes and enhances the mutual understanding among different parties. We present a sequential probabilistic approach to involve stakeholders' views in the formal decision support process. A continuous Bayesian Belief Network (BBN) model is used to estimate population parameters for stakeholder groups, based on samples of individual value judgements. The approach allows quantification and visualization of the variability in views among and within stakeholder groups. Discrete BBN is populated with these parameters, to summarize and visualize the information and to link it to a larger decision analytic influence diagram (ID). As part of ID, the resulting discrete BBN element serves as a distribution-form decision criteria in probabilistic evaluation of alternative management strategies, to help find a solution that represents the optimal compromise in the presence of potentially conflicting objectives. We demonstrate our idea using example data from the field of marine spatial planning. However, this approach is applicable to many types of management cases. We suggest that by advancing the mutual understanding and concrete participation this approach can further facilitate the stakeholder involvement also during the various stages of the environmental management process.