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FLR: an open-source framework for the evaluation and development of management strategies
Kell, L.T.; Mosqueira, I.; Grosjean, P.; Fromentin, J.-M.; Garcia, D.; Hillary, R.; Jardim, E.; Mardle, S.; Pastoors, M.A.; Poos, J.-J.; Scott, F.; Scott, R.D. (2007). FLR: an open-source framework for the evaluation and development of management strategies. ICES J. Mar. Sci./J. Cons. int. Explor. Mer 64(4): 640-646. dx.doi.org/10.1093/icesjms/fsm012
In: ICES Journal of Marine Science. Academic Press: London. ISSN 1054-3139; e-ISSN 1095-9289, more
Peer reviewed article  

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Keywords
    Characteristics > Uncertainty
    Fishery sciences > Economics > Fishery economics
    Software
    Software
    Software
    Stock assessment
    Uncertainty
    Uncertainty
    Uncertainty analysis
    Marine/Coastal
Author keywords
    bio-economic modelling; management strategy evaluation; open source; precautionary approach; simulation framework; software; stock assessment; uncertainty

Authors  Top 
  • Kell, L.T.
  • Mosqueira, I.
  • Grosjean, P., more
  • Fromentin, J.-M.
  • Garcia, D.
  • Hillary, R.
  • Jardim, E.
  • Mardle, S.
  • Pastoors, M.A., more
  • Poos, J.-J., more
  • Scott, F.
  • Scott, R.D.

Abstract
    The FLR framework (Fisheries Library for R) is a development effort directed towards the evaluation of fisheries management strategies. The overall goal is to develop a common framework to facilitate collaboration within and across disciplines (e.g. biological, ecological, statistical, mathematical, economic, and social) and, in particular, to ensure that new modelling methods and software are more easily validated and evaluated, as well as becoming widely available once developed. Specifically, the framework details how to implement and link a variety of fishery, biological, and economic software packages so that alternative management strategies and procedures can be evaluated for their robustness to uncertainty before implementation. The design of the framework, including the adoption of object-orientated programming, its feasibility to be extended to new processes, and its application to new management approaches (e.g. ecosystem affects of fishing), is discussed. The importance of open source for promoting transparency and allowing technology transfer between disciplines and researchers is stressed.

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