a b s t r a c tBiodiversity is globally recognised as a cornerstone of healthy ecosystems, and biodiversity conservation is increasingly becoming one of the important aims of environmental management. Evaluating the tradeoffs of alternative management strategies requires quantitative estimates of the costs and benefits of their outcomes, including the value of biodiversity lost or preserved. This paper takes a decision-analytic standpoint, and reviews and discusses the alternative aspects of biodiversity valuation by dividing them into three categories: socio-cultural, economic, and ecological indicator approaches. We discuss the interplay between these three perspectives and suggest integrating them into an ecosystem-based management (EBM) framework, which permits us to acknowledge ecological systems as a rich mixture of interactive elements along with their social and economic aspects. In this holistic framework, socio-cultural preferences can serve as a tool to identify the ecosystem services most relevant to society, whereas monetary valuation offers more globally comparative and understandable values. Biodiversity indicators provide clear quantitative measures and information about the role of biodiversity in the functioning and health of ecosystems. In the multi-objective EBM approach proposed in the paper, biodiversity indicators serve to define threshold values (i.e., the minimum level required to maintain a healthy environment). An appropriate set of decision-making criteria and the best method for conducting the decision analysis depend on the context and the management problem in question. Therefore, we propose a sequence of steps to follow when quantitatively evaluating environmental management against biodiversity.

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. Large-scale oil spills can have adverse eff ects on biodiversity in coastal areas where maritime oil transportation is intense. In this article we conducted a spatial risk assessment to study the risk that potential tanker accidents pose to threatened habitat types and species living in the northern Baltic Sea, which has witnessed a rapid increase in maritime oil transportation within the past two decades. We applied a probabilistic method, which combines three components: a Bayesian network describing tanker accidents and uncertainties related to them, probabilistic maps showing the movement of oil, and a database of threatened species and habitats in the area. The results suggest that spatial risk posed by oil spills varies across the area, and does not correspond, for example, to the frequency of accidents in a given area. The relative risk is highest for seashore meadows, which is important to take into account when managing these habitats. Our analysis underlines the importance of a thorough risk assessment, which is not only based solely on one or two specifi c factors such as accident probabilities or the trajectories of spilled oil but also contains as broad a view of the consequences as possible. We believe that the probabilistic methodology applied in the study will be of high interest to people who have to cope with uncertainties typical for environmental risk assessment and management.