1. A retrospective investigation of selectivity for Pacific halibut CAPAM Selectivity workshop 14 March, 2013 Ian Stewart & Steve Martell

2. Overview 1) History 2) Contributing factors 3) 2012 Assessment investigation 4) Path forward

3. YearsModelIssues Pre-1977 Yield, yield-per-recruit, simple stock-production modelsNo growth or recruitment variability 1978-1981 Cohort analysis, coastwide, natural mortality (M)=0.2Unstable estimates 1982-1983 Catch-AGE-ANalysis (CAGEAN; age-based availability), coastwide, M=0.2 Migratory dynamics not accounted for 1984-1988 CAGEAN, area-specific, migratory and coastwide, M=0.2Trends differ by area 1989-1994 CAGEAN, area-specific, M=0.2, age-based selectivityRetrospective pattern 1995-1997 Statistical Catch-Age (SCA), area-specific, length-based selectivity, M=0.2 M estimate imprecise 1998-1999 SCA, area-specific, length-based selectivity, M=0.15Poor fit to data 2000-2002 New SCA, area-specific, constant age-based selectivity, M=0.15 Retrospective pattern 2003-2006 SCA, area-specific, constant length-based selectivity, M=0.15 Migratory dynamics created bias 2006-2011 SCA, coastwide, constant length-based selectivity, M=0.15 Retrospective pattern Assessment model evolution

4. Retrospective I: Age-based selectivity

5. Interim: Length-based selectivity Figure from: Clark and Hare, 2002 3A

6. Retrospective II: Age-based selectivity Figure from: Clark and Hare, 2002 3A

7. Interim II: Length-based selectivity 3A Exploitable biomass (M lb) Figure from: Clark and Hare, 2004

8. Retrospective III: Length-based selectivity

9. Overview 1) History 2) Contributing factors 3) 2012 Assessment investigation 4) Path forward

10. Factors contributing to selectivity: - Highly dimorphic growth - Size-at-age: temporal trends and differences by area - Fishery minimum size limit - Hook-size effects – few small fish observed

11. Regulatory areas

12. Growth curves by area Age (years) Length (cm) Dimorphic and spatial variability

13. Historical weight-at-age (Ageing methods, sampling locations, selectivity itself, etc. may bias these trends)

14. Trends in size-at-age Minimum size limit

15. Trends in size-at-age 1997 2012 (Age-11 male halibut) Minimum size limit

16. Directly observed gear selectivity (vulnerability) Based on Didson acoustic camera observations (S. Kaimmer; In prep)

17. Figures from: Clark and Hare, 2003 & 2004 Selectivity by area may differ ~40% Fishery Survey Fishery

18. Abundance by area has changed

19. Length-based selectivity: area (vulnerability) vs. coast-wide (vulnerability + availability) Changes in proportional abundance + Differences in: - Biology (age, length, length-at-age) - Vulnerability

20. Length-based selectivity: area (vulnerability) vs. coast-wide (vulnerability + availability)  Coast-wide “average” selectivity changes over time

21. Spatial approaches: Separate stocks < 2006 J.D. Herder 2008 Fishery J.D. Herder 2008 Survey J.D. Herder 2008 Survey J.D. Herder 2008 Fishery J.D. Herder 2008 Fishery J.D. Herder 2008 Survey J.D. Herder 2008 Survey J.D. Herder 2008 Fishery

22. Spatial approaches: coastwide dynamics 2006+ J.D. Herder 2008 Fishery J.D. Herder 2008 Survey Population

23. Overview 1) History 2) Contributing factors 3) 2012 Assessment investigation 4) Path forward

24. Non-parametric length-based selectivity Inputs: Minimum size bin Bin at which selectivity = 1.0 Maximum size bin Type switch SD size SD time (added this year) Specifications: Operates on 10cm bins Sex-specific Type: Asymptotic, ‘Ramp’, or domed above size bin = 1.0 Smoother for second difference b/w adjacent sizes within year Smoother for second difference b/w adjacent years within size bin Years for which to estimate separate curves Scaled by sex-specific catchability (so values above 1.0 are ok, since that bin is fixed) Catchability (q) can also vary among years

25. Crux: There is no underlying growth model, nor distribution of lengths for a given age. The approach uses ‘true’ observed survey length-at-age to translate size- to age-based selectivity. This is done via interpolating the values at age from the values at each bin. Non-parametric length-based selectivity

26. Retrospective within the 2011 assessment (Sequentially removing data)

27. Retrospective: Symptoms Age-8 Recruits (millions)

28. Increasing penalty on large recruitment estimates

29. SSQs Increasing initial recruitment penalty  Males Females Total

30. Secondary exploration:  Investigate increasing the relative survey weight  Explore process error in selectivity (time-varying)

31. Increased survey index weighting

32. Three tests: similar results

33. Selectivity – implementations

34. Time-varying selectivity

35. Selectivity SD time : Base-case: 0.025 (50% of smoothing over length) 0.050.001

36. Selectivity SD time :

37. Retrospective: Solution

38. (Data only through 2011)

39. Retrospective: Contributing factors 1)Transition from area-specific to coastwide model in 2006 (and retaining the assumption of constant availability) 2)Changes in the coastwide population distribution 3)Too much emphasis on the age data (and not the survey trend) 4) Short time-series

40. Looking forward: Comparison of spatial modeling approaches: - Coast-wide: time-varying selectivity - Implicitly spatial: fleets-as-time-periods fleets-as-areas - Explicitly spatial: Multi-area assessment  Once selectivity is treated as time-varying, either length- or age-based formulations can capture the process.

41. Questions?