Unpublished conference/Abstract (Scientific congresses and symposiums)
FLR: an open source fisheries library or framework for the evaluation of management strategies
Kell, Laurence; Grosjean, Philippe; Mosqueria, I. et al.
2006ICES Symposium on Management Strategies
 

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Keywords :
[en] open source; [en] R statistical language; [en] risk; [en] bioeconomic; [en] uncertainty; [en] management; [en] evaluation
Abstract :
[en] Four major challenges facing fisheries scientists and managers were identified by Peterman (2004), i.e. 1. Uncertainties and the associated risks they create. 2. Difficulties in estimating probabilities within stock assessments. 3. Provision of advice that comprehensively takes into account uncertainties and risks. 4. Effective communication of complex and technical results by scientists to decision makers and the public. The FLR initiative attempts to address all of these by allowing a variety of fishery, biological and economic models and algortihms to be implemented in a common framework. In this way, contrasting management strategies and procedures can be compared and evaluated for their respective effectiveness and robustness to uncertainty before implementation. The paper describes the philosophy behind FLR and its design, and illustrates its use within a variety of EU projects. The importance of open source is also discussed in promoting transparency and allowing technology transfer between disciplines and researchers.
Disciplines :
Phytobiology (plant sciences, forestry, mycology...)
Mathematics
Author, co-author :
Kell, Laurence
Grosjean, Philippe  ;  Université de Mons > Faculté des Sciences > Service d'Ecologie numérique
Mosqueria, I.
Fromentin, J-M.
Jardim, E.
Hillary, R.
Mardle, S.
Poos, J.J.
Scott, R.
Language :
English
Title :
FLR: an open source fisheries library or framework for the evaluation of management strategies
Publication date :
27 June 2006
Number of pages :
1
Event name :
ICES Symposium on Management Strategies
Event place :
Galway, Ireland
Event date :
2006
Research unit :
S807 - Ecologie numérique
Research institute :
R150 - Institut de Recherche sur les Systèmes Complexes
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