No abstract

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.

This article is part of the special series "Applications of Bayesian Networks for Environmental Risk Assessment and Management" and was generated from a session on the use of Bayesian networks (BNs) in environmental modeling and assessment in 1 of 3 recent conferences: SETAC North America 2018 (Sacramento), SETAC Europe 2019 (Helsinki), and European Geosciences Union 2019 (Vienna). The 3 sessions aimed at showing the state-of-the art and new directions in the use of BN models in environmental assessment, focusing on ecotoxicology and water quality modeling. This series aims at reflecting the broad applicability of BN methodology in environmental assessment across a range of ecosystem types and scales, and discusses the relevance for environmental management.

 Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  You may not further distribute the material or use it for any profit-making activity or commercial gain  You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Oil transport has greatly increased in the Gulf of Finland over the years, and risks of an oil accident occurring have risen. Thus, an effective oil combating strategy is needed. We developed a Bayesian Network (BN) to examine the recovery efficiency and optimal disposition of the Finnish oil combating vessels in the Gulf of Finland (GoF), Eastern Baltic Sea. Four alternative home harbors, five accident points, and ten oil combating vessels were included in the model to find the optimal disposition policy that would maximize the recovery efficiency. With this composition, the placement of the oil combating vessels seems not to have a significant effect on the recovery efficiency. The process seems to be strongly controlled by certain random factors independent of human action, e.g. wave height and stranding time of the oil. Therefore, the success of oil combating is rather uncertain, so it is also important to develop activities that aim for preventing accidents. We found that the model developed is suitable for this type of multidecision optimization. The methodology, results, and practices are further discussed.

a b s t r a c tA rapid increase in maritime traffic together with challenging navigation conditions and a vulnerable ecosystem has evoked calls for improving maritime safety in the Gulf of Finland, the Baltic Sea. It is suggested that these improvements will be the result of adopting a regionally effective proactive approach to safety policy formulation and management. A proactive approach is grounded on a formal process of identifying, assessing and evaluating accident risks, and adjusting policies or management practices before accidents happen. Currently, maritime safety is globally regulated by internationally agreed prescriptive rules, which are usually revised in reaction to accidents. The proactive Formal Safety Assessment (FSA) is applied to risks common to a ship type or to a particular hazard, when deemed necessary, whereas regional FSA applications are rare. An extensive literature review was conducted in order to examine the opportunities for developing a framework for the GoF for handling regional risks at regional level. Best practices were sought from nuclear safety management and fisheries management, and from a particular case related to maritime risk management. A regional approach that sees maritime safety as a holistic system, and manages it by combining a scientific risk assessment with stakeholder input to identify risks and risk control options, and to evaluate risks is proposed. A regional risk governance framework can improve safety by focusing on actual regional risks, designing tailor-made safety measures to control them, enhancing a positive safety culture in the shipping industry, and by increasing trust among all involved.

The highly globalized and competitive nature of the shipping industry poses serious governance challenges. Recently, the use of voluntary measures, such as corporate social responsibility (CSR) initiatives, has been explored in terms of moving towards environmentally and socially responsible as well as safe shipping industry practices. Limited attention has been paid on the role of stakeholders such as consumers, employees, NGOs, and academia in pressuring the shipping industry towards greater environmental and social responsibility. Here, by applying stakeholder theory and drawing on examples of already materialized stakeholder actions and multistakeholder initiatives, we study the potential ways that stakeholders can promote CSR in the shipping industry: we explore the resource dependencies between stakeholders, the stakeholder influence strategies, and the importance of multi-stakeholder pressure. We show that stakeholders can gain more power by using indirect strategies such as working via and/or in alliances with NGOs, trade unions, banks and financers, and/or different national or international regulatory bodies, as well as with the industry itself. Our results reveal the potential of multi-stakeholder pressure and action to promote the adoption of CSR activities, support the transparency, legitimacy, and enforcement of the practices, as well as widen the scope and focus of CSR initiatives and practices by focusing on a broad range of social and environmental issues. Finally, stakeholder pressure can push towards improved regulations. The study suggests that increased attention needs to be paid on the multi-stakeholder demands, especially considering the accentuated importance of effective maritime governance in the future.

The growth of maritime oil transportation in the Gulf of Finland (GoF), North-Eastern Baltic Sea, increases environmental risks by increasing the probability of oil accidents. By integrating the work of a multidisciplinary research team and information from several sources, we have developed a probabilistic risk assessment application that considers the likely future development of maritime traffic and oil transportation in the area and the resulting risk of environmental pollution. This metamodel is used to compare the effects of two preventative management actions on the tanker collision probabilities and the consequent risk. The resulting risk is evaluated from four different perspectives. Bayesian networks enable large amounts of information about causalities to be integrated and utilized in probabilistic inference. Compared with the baseline period of 2007-2008, the worst-case scenario is that the risk level increases 4-fold by the year 2015. The management measures are evaluated and found to decrease the risk by 4-13%, but the utility gained by their joint implementation would be less than the sum of their independent effects. In addition to the results concerning the varying risk levels, the application provides interesting information about the relationships between the different elements of the system.