Hake Management Strategy Evaluation: Performance Metrics and Tentative Results

1. MSE Performance Metrics, Tentative Results and Summary Joint Technical Committee Northwest Fisheries Science Center, NOAA Pacific Biological Station, DFO School of Resource and Environmental Management, SFU

2. Outline • Summarize the hake MSE • Example simulations • Performance metrics • Summary figures

3. Objectives of the MSE • Use the 2012 base case as the operating model. • As defined in May 2012 • Evaluate the performance of the harvest control rule • Evaluate the performance of annual, relative to biennial survey frequency.

4. Performance Statistics • Conservation objectives • Yield objectives • Stability objectives • Operating Model • Stock dynamics • Fishery dynamics • True population Feedback Loop Data Catch • Management Strategy • Data choices • Stock Assessment • Harvest control rule Organization of MSE Simulations Use the MPD (not posterior medians, or other quantiles) for applying the harvest control rule

6. Cases Considered • No fishing • Perfect Information Case • Annual Survey • Biennial Survey

7. Perfect Information Case • We created a reference, perfect information case where we simulated data with no error • The purpose of the perfect information case was as follows: • To separate observation vs process error i.e. variable data don’t affect management procedure performance • to provide a standard relative to which a comparison of the test (biennial and annual) cases could be made

8. Perfect information case • Every year operating model simulates dynamics of the stock (i.e. recruitments, stock size etc) • No assessment model is fit, simulated catches come from the application of the control rule to the true stock

9. Biennial Survey Case • Every year operating model simulates dynamics of the stock (i.e. recruitments, stock size etc) • Every odd year operating model simulates and assessment model fits: • catch • survey age composition data • commercial age composition data • survey biomass • In even years operating model simulates and assessment model fits • catch • commercial age composition data

10. Annual Survey Case • Every year operating model simulates dynamics of the stock (i.e. recruitments, stock size etc) • Every year operating model simulates and assessment model fits: • catch • survey age composition data • commercial age composition data • survey biomass

12. But remember – starting points are not the same for each MSE run

16. Measuring Performance • Choose metrics that capture the tradeoffs between conservation, variability in catch and total yield for specific time periods. • Define short, medium and long time periods as Short=2013-2015, Medium=2016-2020, Long=2021-2030. • The main conservation metric is the proportion of years depletion is below 10% • The main variability in catch metric is the Average Annual Variability in catch for a given time period. • For yield we used the median average catch • We’ve chosen what we think are the top six. We’d like to discuss if others are needed.

17. Key Performance Statistics

18. Other available options • First quartile depletion • Third quartile depletion • Median final depletion • Median of lowest depletion • Median of lowest perceived depletion • First quartile of lowest depletion • Third quartile of lowest depletion • First quartile of AAV in catch • Third quartile of AAV in catch • First quartile of average catch • Third quartile of average catch • Median of lowest catch levels • First quartile of lowest catch levels • Third quartile of lowest catch levels • Proportion with any depletion below SB10% • Proportion perceived to have any depletion below SB10%

19. Statistics Break - Medians vs Means

20. Average Annual Variability in Catch (illustration)

21. Comparisons of Depletion, Catch and AAV for All Cases

24. Summary for long-term depletion

25. Summary for long term AAV

26. Summary for long-term catch

27. Discussion • Next steps

28. Alternative Analyses

29. Analysis of alternative target harvest rates • The hake treaty doesn't specify a target depletion level, only a target harvest rate (F40%) and a control rule (40-10). • This makes it difficult to evaluate the efficacy of the control rule (i.e. relative to what?) • One additional curiosity that we considered was what would the target harvest rate have to be in order to achieve a range of target depletion levels • The MSE can be used to explore how changes to the target harvest rate might affect depletion, AAV, and average catch. • This is an exploration of trade-offs, not a proposal to change the hake treaty.

30. Alternative target harvest rates

33. Discussion • Does the groups want alternative performance statistics considered • Progress and next steps