IMIS | Flanders Marine Institute

Flanders Marine Institute

Platform for marine research


Publications | Institutes | Persons | Datasets | Projects | Maps
[ report an error in this record ]basket (0): add | show Printer-friendly version

‘Cheap and dirty’ fisheries science and management in the North Atlantic
Kelly, C.J.; Codling, E.A. (2006). ‘Cheap and dirty’ fisheries science and management in the North Atlantic. Fish. Res. 79(3): 233-238
In: Fisheries Research. Elsevier: Amsterdam. ISSN 0165-7836, more
Peer reviewed article  

Available in  Authors 

    Fishery management; Indicators; Stock assessment; AN, North Atlantic [Marine Regions]; Marine

Authors  Top 
  • Kelly, C.J.
  • Codling, E.A.

    The current system of managing fish stocks in the North Atlantic is failing: many key stocks are at historically low levels and fishing effort is being restricted while capacity remains high. The traditional scientific approach used by International Council for the Exploration of the Sea (ICES) to provide advice on fish stocks is based on complex analytical models of the fishery that require detailed, accurate and high contrast data to predict the future state of fish stocks. However, when data are unreliable or unavailable, these complex models are of limited use, as illustrated by the failure of recent assessments for important ICES stocks. Borrowing ideas from the field of process management, we suggest an alternative approach where fish stocks are managed using harvest rules based on simple empirical indicators. Such an approach is essential for ‘data-poor’ stocks (where analytic assessments traditionally cannot be completed due to lack of data), but we argue that they could also be adopted for other stocks, particularly where data have become ‘poor’. This alternative approach using empirical indicators would fit into the current political framework of the North Atlantic where stocks are managed on a single-species basis. The approach is appropriate not only to the North-eastern Atlantic area, and we discuss its use and relevance in other fisheries around the world.

All data in IMIS is subject to the VLIZ privacy policy Top | Authors