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ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on August 8, 2009
ICES Journal of Marine Science: Journal du Conseil 2009 66(10):2278-2283; doi:10.1093/icesjms/fsp206
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

The value of information in fisheries management: North Sea herring as an example

Samu Mäntyniemi1, Sakari Kuikka1, Mika Rahikainen2, Laurence T. Kell3 and Veijo Kaitala2

1 Fisheries and Environmental Management Group, Department of Biological and Environmental Sciences, University of Helsinki, PO Box 65, FIN-00014 Helsinki, Finland
2 Integrative Ecology Unit, Department of Biological and Environmental Sciences, University of Helsinki, PO Box 65, FIN-00014 Helsinki, Finland
3 formerly Cefas, UK, now ICCAT Secretariat, Corazón de María 8, 28002 Madrid, Spain

Correspondence to S. Mäntyniemi: tel: +358 9 191 58710; fax: +358 9 191 58257; e-mail: samu.mantyniemi{at}helsinki.fi

Mäntyniemi, S., Kuikka, S., Rahikainen, M., Kell, L. T., and Kaitala, V. 2009. The value of information in fisheries management: North Sea herring as an example. – ICES Journal of Marine Science, 66: 2278–2283.

We take a decision theoretical approach to fisheries management, using a Bayesian approach to integrate the uncertainty about stock dynamics and current stock status, and express management objectives in the form of a utility function. The value of new information, potentially resulting in new control measures, is high if the information is expected to help in differentiating between the expected consequences of alternative management actions. Conversely, the value of new information is low if there is already great certainty about the state and dynamics of the stock and/or if there is only a small difference between the utility attached to different potential outcomes of the alternative management action. The approach can, therefore, help when deciding on the allocation of resources between obtaining new information and improving management actions. In our example, we evaluate the value of obtaining hypothetically perfect knowledge of the type of stock–recruitment function of the North Sea herring (Clupea harengus) population.

Keywords: Bayesian statistics, bioeconomics, decision analysis, stock–recruitment, uncertainty

Received 6 February 2009; accepted 25 June 2009; advance access publication 8 August 2009.


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