Status of the darkblotched rockfish resource off the continental U.S. Pacific Coast in 2013

1. Status of the darkblotched rockfish resource off the continental U.S. Pacific Coast in 2013 • Vladlena Gertseva • James Thorson • Northwest Fisheries Science Center • May 13, 2013

2. Found from the Bering Sea to southern California; Most abundant from off British Columbia to Central California; Slope species (with majority between 100m and 600m).

3. General information about the species Adults are observed near cobble and boulders. Co-occurs with POP, splitnose, yellowmouth and sharpchinrockfish;

4. General information about the species Among the longest lived rockfish ( 100 years); Sexual dimorphism in growth; Larvae and juveniles are pelagic; settle at 4 to 6 cm in length in about 55 to 200 m; Ontogenetic movement to deeper waters.

5. Spatial distribution of darkblotched rockfish

8. Previous assessments Declared overfished

9. Description of fishery

10. Recent management performance IFQfishery

11. Previous assessments Declared overfished

13. Landings (mt)

14. Catch reconstruction

15. Fleet structure used in the assessment

17. Discard data

18. Discard data

21. AKSHLF (AFSC shelf survey)

22. Methods to construct abundance indices • Delta-GLMM: • Probability of occurrence: logit-link, binomial response Pr(D>0) • Density: linear-link, different possible responses Pr(D|D>0) • Purposes: • Include vessel-effect as random • Necessary because contract vessel is chosen in an open-bid • Account for overdispersion • Design-based estimators for variance assume normality and homoskedasticity

24. More on GLMM, ECE Strata were chosen a priori Model assumes that tows are identically distributed within a strata Extreme catches frequently violate distributional assumptions Variance estimates of only reliable when distributional assumptions are met “Extreme catch event” (ECE) distributions are necessary to have model expectations of catch distributions match true distribution

25. AKSHLF AKSLP NWSLP NWCBO

27. Length composition data

29. Concerns with age data Generated two ageing error matrices Criteria for estimating ages might have changed; A bias may have existed in early ages.

30. Ageing impression of early and late age estimates

31. Age composition data TWL females TWL males

32. Model general specifications Stock Synthesis Model starts in 1915; Two fishing fleets; Four surveys; Sexes treated separately.

33. 1.205260E-05 3.135120 3.109580 1.109933E-05 Weight-length relationships

34. Female maturity at age m∞ is the asymptotic maturity for an old female; α is the age at which maturity is 50% of m∞ β controls the slope rate of maturity as a function of age

35. 101100 44800 Female fecundity • - number of eggs W – female weight a, b - coefficients

36. 0.05 Natural mortality Hoenig (1983) Z- total mortality Tmax – max age

37. 0.779 Stock-recruit relationship Bias correction: Estimated using Methot and Taylor (2012) bias-ramp methods; : selected using Methot and Taylor (2012) formula;

38. Recruitment estimates

39. Growth LA is length (cm) at age A, kis the growth coefficient, L∞ is asymptotic length, L1is the size associated with a minimal reference age A1.

40. Selectivity assumptions

41. Selectivity for all fleets

42. Blocking scheme used

43. Fit to TWL discard data TWL discard length compositions

44. Estimate of discard amount by fleet

45. AKSHLF AKSLP NWSLP NWCBO

46. Fit to length composition data TWL males TWL females

47. Fit to length composition data Males Females

48. Fit to age composition data TWL females TWL males TWL discard

49. Fit to age composition data AKSHLF AKSLP NWSLP

50. Fit to age composition data NWCBO