Technical University of Denmark Danish Institute for Fisheries Research MODSIM Conference 10/13 December 2007 Christchurch, New Zealand Evaluation of management.

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Presentation transcript:

Technical University of Denmark Danish Institute for Fisheries Research MODSIM Conference 10/13 December 2007 Christchurch, New Zealand Evaluation of management strategies for the mixed North Sea roundfish fisheries with the FLR framework Katell Hamon, Clara Ulrich, Ayoe Hoff and Laurence Kell

Technical University of Denmark Danish Institute for Fisheries Research Why Use Management Strategy Evaluations? Failure of current European management –Decreasing stocks  objectives not reached –Short term, single species management –Credibility crisis in European scientific community Most European stocks managed via quotas –2 years delay –real F ≠ target F –Not accounting for technical interactions Complex management system ICES, STECF, European Commission, numerous uncertainties in the system Alternative to traditional projections  MSE

Technical University of Denmark Danish Institute for Fisheries Research Stocks Operating Model = “at sea” Assessment Management ? ? ? ? ? Management procedure = “at land” Fleets Implementation

Technical University of Denmark Danish Institute for Fisheries Research Models vs. toolbox Up to now : development of various models more or less generic –User ≠ developer –Developed for a given approach –Interface user-friendly and/or computing speed more than code transparency –Models easily used by managers BUT in practice always run by scientists FLR toolbox: common language rather than model –User = Developer (of his model / of tools) –Open Source. Access, transparency, control, exchange between institutes –Use of R statistical and graphical tools –Balance between user-friendliness and flexibility

Technical University of Denmark Danish Institute for Fisheries Research FLR - Basics OOP: inheritance, polymorphism and encapsulation S4 classes FLQuant 6 dimensional array + character string for units –dim1: age, length, life history stage, etc –dim2: year –dim3: unit (sex or other extra dimension needed) –dim4: season –dim5: area –dim6: iter Methods and functions: dims, summary, show, plot, xyplot, bwplot, dotplot, barchart, stripplot, histogram, bubbles, [], as.data.frame, apply, window, trim, propagate, dim[Sums, Means, Vars]

Technical University of Denmark Danish Institute for Fisheries Research FLR – Complex objects FLStock exploited stock data (biology and catch) FLFleet fleet data at different level (metier, stock) FLIndex abundance index data name desc range catch catch.n catch.wt discards discards.n discards.wt landings landings.n landings.wt stock stock.n stock.wt m mat harvest harvest.spwn m.spwn

Technical University of Denmark Danish Institute for Fisheries Research FLR Lego blocks MANAGEMENT PROCEDURE Assess status of stock and set management options depending upon perceived status of fishery stock(s) Management decision stage Biological reference points (e.g. MSY) FLBRP Management procedure FLHCR OPERATING MODEL Represents the “true” dynamics of the system against which performance will be measured Fleet dynamics FLFleet MODEL CONDITIONING INITIAL CONDITIONS IMPLEMENTATION MODEL FLEcon Assessment procedure Assessment assumptions Auxiliary information (e.g. tuning indices) FLIndices Perceived stock FLStock Stock assessment (e.g. VPA) FLAssess Population biology Stock dynamics FLBiol Stock processes e.g. Recruitment FLSR SUMMARY STATISTICS Used to evaluate performance of management procedures against objectives. OBSERVATION ERROR MODEL Generation of data on fishery and stocks. FLOEM Kell et al, 2007

Technical University of Denmark Danish Institute for Fisheries Research Case study North Sea Roundfish - Presentation Mix-fisheries, multispecies: 2 species, cod and haddock 11 fleets (5 pays) + 1 fleet (NN) / 49 metiers Operating Model: –Estimation of recruitment by Stock-Recruitment model –Effort of the fleets estimated effort needed to catch to max or min quota –Model of entry/exit of vessels in the fishery driven by economics Management Procedure: –Stock assessment based on XSA (Darby and Flatman, 1994) –Harvest Control Rules (HCR): based on EU-Norway agreements Accounting for uncertainty –Measurement error : tuning fleet CPUE –Process error : recruitment –Estimation error : use of XSA to estimate N and F –Implementation error: EU-Norway HCR Stop fishing at first/last quota reached Basé sur les définitions de Rosenberg et Restrepo, 1994

Technical University of Denmark Danish Institute for Fisheries Research Case study North Sea Roundfish - Results Real stock in black; Perceived stock in green; Reference points in red stop at 1st quota reached fish until the last quota

Technical University of Denmark Danish Institute for Fisheries Research Pros vs Cons Open Source: free access, transparency, exchange Toolbox: Adaptability, flexibility, diversity Largely used in Europe: ICES WG, European projects, STECF Interactivity with stakeholders: hypothesis / outputs User = Developer Open source: never stable, dependant on R steep learning curve slowness of R /FLR Not a model!!  development of 1 MSE takes time User = Developer

Technical University of Denmark Danish Institute for Fisheries Research More about FLR : Wiki: Paper: 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 FLR: an open-source framework for the evaluation and development of management strategies. – ICES Journal of Marine Science, 64: 640–646. More about EFIMAS THANK YOU