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Abstract
Interactions between scientific assessments and management decision-making are key determinants for the efficiency of environmental risk governance. This applies particularly to marine ecosystems like the Baltic Sea, where fisheries and eutrophication pose serious threats connected to environmental, social and economic aspects of sustainability. Using contemporary science-policy theory, this paper investigates structures, challenges and prospects of science-policy interfaces connected to fisheries and eutrophication governance in the Baltic Sea. We analyse and compare the two cases with respect to two aspects: first the design and organisational structures of the institutional frameworks and second the management of uncertainties and stakeholder disagreements in the two risk cases. The analyses reveal how conventional natural science-based policy-making is insufficient for the requirements of complex environmental governance arenas like fisheries and eutrophication. Both cases show a high, almost exclusive, dependence on science-based advice regarding the organisational and institutional structures of their science-policy interfaces. They also expose remarkable differences with respect to stakeholder disagreements about the interplay between science, other knowledge and policy decisions. In the eutrophication case, consensual science-based advice shaped policy decisions in a comparatively uncomplicated manner. In fisheries by contrast, stakeholder disagreements and different interpretations of scientific uncertainties created serious confusions about the basic role of science in policy. We identify and discuss factors contributing to the observed differences in the science-policy interplay of fisheries and eutrophication management. Our results highlight a misleading conceptual understanding of science-policy interfaces between the normative idea of objective, science-based policy-making and the political challenges of dealing with the social aspects of uncertainty and stakeholder disagreements in environmental risk governance.
Acknowledgements
The research leading to these results was funded by the European Community’s Seventh Framework Programme (2007–2013) under grant agreement no. 217246 made with the joint Baltic Sea research and development programme BONUS, as well as from the Swedish Environmental Protection Agency, the Swedish Research Council FORMAS and the Foundation for Baltic and East European Studies. SL also acknowledges funding from the Swedish Research Council and Riksbankens Jubileumsfond.
Notes
1. The term and discussions about ‘risk governance’ are delineated in van Asselt and Renn (Citation2011).
2. Overfishing and eutrophication are today defined as two major environmental risks to the Baltic Sea ecosystem in key regional policy documents like the Baltic Sea Action Plan (BSAP; HELCOM Citation2007) and the EU Strategy for the Baltic Sea Region (EC Citation2009).
3. This means for example when a specific management aspect (e.g. a fishing quota or a nutrient reduction target) becomes of key relevance for decision-making, the epistemic criteria of how to deal with and express scientific uncertainty are not stable but influenced by the actual social stakes at hand.
4. It has to be noted here, that we are aware of the tensions between and shortcomings with the two approaches for an application to science-policy analyses, not least due to their basically different epistemological and ontological points of departure. The objectivism/constructivism tension yet roots in the fact that the constructivist orientation to risk has been developed mainly as a critique of objectivism (Hellström and Jacob Citation2001, 33). We regard the distinction proposed by Hellström and Jacob as a useful tool for analysing the different aspects of science-policy interfaces in fisheries and eutrophication addressed in this paper.
5. This was done as part of the research project Environmental Risk Governance of the Baltic Sea (RISKGOV; www.sh.se/riskgov). The interviews were conducted between February and November 2010.
6. Russia, as the only riparian Baltic state today not part of the CFP, has bilateral agreements with the EU to regulate fisheries jointly.
7. Five RACs cover specific geographical regions of EU waters and two RACs address specific fisheries types (pelagic and high seas/long distance fleet) see http://ec.europa.eu/fisheries/partners/regional_advisory_councils/index_en.htm.
8. For example via ICES/HELCOM’s Working Group on Integrated Assessments of the Baltic Sea and ICES’ Working Group on Integrated Assessments in the North Sea.
9. The decision-making on quota management today (2012) still lies exclusively with the Council of Ministers.
10. MARE stands for Marine Research on Eutrophication, a Scientific Base for Cost-Effective Measures for the Baltic Sea. The project lasted from 1999 to 2006; for a description of NEST see: http://nest.su.se/nest.
11. Examples of such EU Directives are: the Water Framework Directive (WFD), the Marine Strategy Framework Directive (MSFD), the Nitrates Directive and the Urban Wastewater Directive.
12. Despite successful regional cooperation through HELCOM and BSAP serving as pilots for a number of EU policies and directives (Backer et al. Citation2010), this policy obviously develops according to other logics.
13. The effectiveness of the national plans will be evaluated at a HELCOM Ministerial meeting in October 2013 (http://www.helcom.fi/Ministerial2013/en_GB/MM2013intro/).
14. The observer list is published at: http://www.helcom.fi/helcom/observers/en_GB/observers/.
15. Examples of recently established stakeholder forums are: the HELCOM Fisheries and Environmental Authorities Forum and the HELCOM Agriculture and Environmental Authorities Forum.
16. For example Gray and Hatchard (Citation2003) criticise that RACs might be ‘more rhetorical than real’ and just another ‘lip-service’ paid by the EU Commission to take up new concepts of ‘good governance’.
17. The policy objectives changed from general 50% nutrient reductions everywhere towards a system of most cost-effective measures to be undertaken in the different sub-regions of the Baltic Sea (Wulff et al. Citation2007).
18. Also recent research on eutrophication tries to take account of these uncertainty challenges, e.g. through a quantification of model uncertainties, simulations and scenario building (cf. Meier and Andersson Citation2012).
19. An important aim for this policy’s reform in 2013 is to bring it better in line with the WFD and MSFD (Lundberg Citationforthcoming).