Keywords: Quantitative Fisheries Science, Common Fisheries Policy, Management Strategy Evaluation, advice, simulation
Webpages:
https://flr-project.org,
https://github.com/flr The management of the activities of fishing fleets aims at ensuring the sustainable exploitation of the ocean’s living resources, the provision of important food resources to humankind, and the profitability of an industry that is an important economic and social activity in many areas of Europe and elsewhere. These are the principles of the European Union Common Fisheries Policy (CFP), which has driven the management of Europe’s fisheries resources since 1983.
Quantitative scientific advice is at the heart of fisheries management regulations, providing estimates of the likely current and future status of fish stocks through statistical population models, termed stock assessments, but also probabilistic comparisons of the expected effects of alternative management procedures. Management Strategy Evaluation (MSE) uses stochastic simulation to incorporate both the inherent variability of natural systems, and our limited ability to model their dynamics, into analyses of the expected effects of a given management intervention on the sustainability of both fish stocks and fleets.
The Fishery Library in R (
FLR) project has been for the last ten years building an extensible toolset of statistical and simulation methods for quantitative fisheries science (Kell et al. 2007), with the overarching objective of enabling fisheries scientists to carry out analyses of management procedures in a simplified and robust manner through the MSE approach.
FLR has become widely used in many of the scientific bodies providing fisheries management advice, both in Europe and elsewhere. The evaluation of the effects of some elements of the revised CFP, the analysis of the proposed fisheries management plans for the North Sea, or the comparison of management strategies for Atlantic tuna stocks, among others, have used the
FLR tools to advice managers of the possible courses of action to favour the sustainable use of many marine fish stocks.
The
FLR toolset is currently composed of 20 packages, covering the various steps in the fisheries advice and simulation workflow. They include a large number of S4 classes, and more recently Reference Classes, to model the data structures that represent each of the elements in the fisheries system. Class inheritance and method overloading are essential tools that have allowed the
FLR packages to interact, complement and enrich each other, while still limiting the number of functions an user needs to be aware of. Methods also exist that make use of R’s parallelization facilities and of compiled code to deal with complex computations. Statistical models have also been implemented, making use of both
R’s capabilities and external libraries for Automatic Differentiation.
We present the current status of
FLR, the new developments taking place, and the challenges faced in the development of a collection of packages based on S4 classes and methods.
References Kell, L. T., I. Mosqueira, P. Grosjean, J.-M. Fromentin, D. Garcia, R. Hillary, E. Jardim, et al. 2007. “FLR: An Open-Source Framework for the Evaluation and Development of Management Strategies.”
ICES Journal of Marine Science 64 (4).
http://dx.doi.org/10.1093/icesjms/fsm012.
