Journal Article

FLR: an open-source framework for the evaluation and development of management strategies

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

in ICES Journal of Marine Science

Published on behalf of ICES/CIEM

Volume 64, issue 4, pages 640-646
Published in print May 2007 | ISSN: 1054-3139
Published online March 2007 | e-ISSN: 1095-9289 | DOI: http://dx.doi.org/10.1093/icesjms/fsm012
FLR: an open-source framework for the evaluation and development of management strategies

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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., and Scott, R. D. 2007. FLR: an open-source framework for the evaluation and development of management strategies. – ICES Journal of Marine Science, 64: 640–646.

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.

Keywords: bio-economic modelling; management strategy evaluation; open source; precautionary approach; simulation framework; software; stock assessment; uncertainty

Journal Article.  5486 words.  Illustrated.

Subjects: Environmental Science ; Marine and Estuarine Biology

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