Integrated Modelling Tools to Support Risk-Based Decision-Making in Marine Spatial Management

Journal Article

Title: Integrated Modelling Tools to Support Risk-Based Decision-Making in Marine Spatial Management
Publication Date:
November 15, 2011
Journal: Marine Ecology Progress Series
Volume: 441
Pages: 197-212
Publisher: Inter-Research
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Document Access

Website: External Link

Citation

Stelzenmüller, V.; Schulze, T.; Fock, H.; Berkenhagen, J. (2011). Integrated Modelling Tools to Support Risk-Based Decision-Making in Marine Spatial Management. Marine Ecology Progress Series, 441, 197-212.
Abstract: 

The implementation of an ecosystem approach to marine spatial management requires practical tools to support risk-based decision-making. We combined a Bayesian Belief Network with a Geographical Information System (GIS) for the spatially explicit quantification of the ecological and economic risks of spatial management options. As an example we assessed the German exclusive economic zone (EEZ) in the North Sea to determine the potential effects of 2 scenarios on the vulnerability of plaice Pleuronectes platessa to fishing, fishing fleets and their revenues. In the first scenario we simulated a shift in plaice distribution due to changes in bottom temperatures to assess spatial management options. Then we imitated an expansion of offshore wind energy development with an associated reallocation of international fishing effort to assess the ecological and economic consequences. We predicted that an increase of 0.5 degrees C in the average bottom temperature would require a significant reduction in fishing effort to maintain the current relative level of the vulnerability of plaice to fishing. The likely consequences of the second scenario were a homogenous increase in plaice catches around the areas closed for fishing, together with a decrease in the vulnerability of plaice to fishing within 17% of the study area. Our results showed the great potential of this framework to integrate the spatially explicit assessment of the economic and ecological risks of spatial management options. We conclude that this modelling framework can support the implementation of an ecosystem approach to marine spatial management, as it enables the derivation of probabilistic estimates which can be used directly in risk-based decision-making.

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