Towards standardization of MSE algorithms - Is there a minimum MSE ?
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Towards standardization of MSE algorithms - Is there a minimum MSE ?
- 1. Towards standardization of MSE algorithms Is there a minimum MSE ? Ernesto Jardim* Colin Millar Iago Mosqueira Finlay Scott Chato Osio JRC Unit of Maritime Affairs Fishreg * ernesto.jardim@jrc.ec.europa.eu
- 2. Why ? ➔ Growing demand to set up long term management plans (LTMP) for commercial stocks. ➔ Growing number of data moderate stocks that require LTMP type of analysis. ➔ Management Strategy Evaluation (MSE) is a powerful tool to test how uncertainty, decision making and implementation of management actions impact LTMP objectives. a4a Init
- 3. However ... a4a Init MSEs are extremely complex and require: ➔ Long time to develop ➔ Human resources with strong statistical and coding background Furthermore, MSE results are difficult to communicate
- 4. a4a a4a Init The Joint Research Center “assessment for all” initiative (a4a) started in 2012, with the aim of: ➔ Develop, test and distribute the necessary methods to assess a large numbers of stocks in an operational time frame. ➔ Build the necessary capacity on stock assessment and advice provision.
- 5. a4a a4a Init ➔ Core team: group of fisheries scientists from the EC JRC responsible for development. ➔ Members: small but global network of scientists from different fisheries research and advice institutions. ➔ Supporting group: network of scientists
- 6. ➔ Stock assessment: [N], [F] ➔ Short term forecast: [Ny+] | [F], [R] ➔ Medium term forecast: [Ny++] | [F], [S/R], error(s) ➔ MSE: [Ny++] | [F], [S/R], error(s) + decision making, implementation error, obs. error a4a Init From stock assessment to MSE
- 7. a4a Init MSE
- 8. a4a Init Standardization 1. Identify the most important processes within the MSE framework e.g. OM (partially done). 2. Implement methods in R/FLR to deal with uncertainty in each process in a transparent way (partially done). 3. Identify a limited number of models for each process based on groups of species or sea basins (to be done).
- 9. a4a Init Components of a standard MSE ➔ Operating model natural mortality, growth, S/R, exploitation pattern ➔ Management procedure indicator to inform HCR, HCR shape ➔ Observation error model error in catch, error in the abundance index ➔ Implementation error model error in effective F, overcatch
- 10. a4a Init Example standard management procedure ➔ Three HCR ➔ Model-free (no assessment) ➔ Relative (based on relative stock status) ➔ Absolute (ICES MSY rule) ➔ Four indicators ➔ Commercial catch ➔ Survey biomass ➔ Biomass dynamic SSB/Bmsy & F/Fmsy ➔ SC@A SSB & F
- 11. a4a Init (loosely based on S.aurita in Northwest Africa)
- 13. Wrapping up a4a Init ➔ Important advantages in making MSE widely used: ➔ Engage stakeholders in designing management plans/actions. ➔ Makes available sophisticated algorithms. ➔ Improves awareness of uncertainty and impacts on management goals. ➔ Standard MSE for moderate data stocks has to include the most important processes.