Draft Status of the U.S. petrale sole resource in 2012 STAR Panel

1. Draft Status of the U.S. petrale sole resource in 2012 STAR Panel Melissa Haltuch1, Kotaro Ono2, Juan Valero3 1NWFSC, Seattle 2UW, SAFS, Seattle 3CAPAM, La Jolla 13 May 2013

2. Outline • Introduction • Data • Fishery Independent • Biological • Fishery Dependent • Previous Modeling • Responses to 2011 STAR panel • General Model Description • Base Case Model • Sensitivity Analysis • Retrospective Analysis • Historical Assessment Analysis • Likelihood Profile • Harvest Projections

3. Introduction - Biology • Right eyed flounder • Gulf of Alaska to Baja California • Soft bottoms • 550 m depth • No genetic work • Adults migrate seasonally • No strong indication of multiple stocks

4. Introduction - Fishery • 1876 off of San Francisco, CA • 1884-1885, established by 1937 in OR • Began about 1932, established by 1936 in WA • Early concerns about stock depletion in the 1950s • Targeting of winter spawning aggregations developed through the 1950s and 1960s • By 1980s winter catches exceeded summer catches in many years

5. Introduction - Management • Management actions since the late 1990s • Area closures • Trip limits • Gear modifications • IFQ

6. Triennial survey 1977 (excluded) Depth: 91-457 meters 1980-1992 Depth: 55-366 meters 1995-2004 Depth: 55-500 meters Run by RACE until 2004 when run by FRAM Random trawls on systematic line transects

7. Triennial Survey Timing

8. NWFSC survey 1999-2002 surveyed 183-1280 meters Did not always go as far south 2003 through 2008 55-1280 meters 32.5° to 48.17° Random trawl locations Random vessels chosen each year

9. Survey differences

10. Surveys Triennial Two time series: 1980-1992 and 1995-2004 Excluded the Conception area (S of 36°) Biomass and length frequencies NWFSC One time series: 2003-2012 All areas Biomass, lengths, and age-at-length

11. Catch rates: Triennial

12. Catch rates: NWFSC

13. Density: NWFSC

14. Survey post-stratification Post-stratify depth using fish length Ontogenetic movement to deeper water Lai et al (2005) used Bayesian change-point analysis Haltuch et al (2009) used a frequentist approach and came to same result Significant split just greater than 100 m

15. Mean fish length vs depth

16. Survey stratification for GLMM/GLM Strata collapsed to satisfy condition of at least 3 positive observations in each year/area/depth stratum Depths Triennial (Early and Late): 55-100 meters and 100+ m NWFSC: 55-100 m, 100-183 m, 183+ m Areas Triennial Early Shallow: Vancouver/Columbia, Eureka, Monterey/Conception Deep: Vancouver/Columbia/Eureka, Monterey/Conception Late: Shallow: Vancouver/Columbia, Eureka, Monterey/Conception Deep: Vancouver/Columbia, Eureka, Monterey, Conception NWFSC Shallow/Middle – Vancouver/Columbia, Eureka, Monterey, Conception Deep – Combined Eureka-Columbia/Vancouver

17. Model based biomass estimates • Delta-GLMM • NWFSC: random year:vessel effects • Triennial: NO random vessel effects • Fixed effects: year, strata, depth, year:strata • Lognormal errors • MCMC’s to determine variability

18. Model selection – residual deviance

19. Model fit - lognormal

20. Survey biomass estimates

21. Triennial length frequencies

22. NWFSC length frequencies

23. NWFSCagefrequency

24. NWFSC survey length at age

25. Summary of survey data • NWFSC survey has higher catch rates than the triennial survey, resulting in larger biomass estimates • 2004 triennial survey catch rates are on average higher than rest of triennial series • Trend in NWFSC survey peaks in 2004, declines through 2008, and increases after 2009 • Smaller and younger fish observed in 2008-2010

26. Biological Data - Weight-Length • NWFSC Survey

27. Biological Data – Maturity at length • Oregon • Washington • 2002

28. Biological Data – Natural Mortality • 1940s Catch Curve • M: 0.18-0.26 • F: 0.19-0.21 • Hoenig’s Method • 0.15 max age of 30 • (female petrale sole live at least 30 years) • Hamel prior • M median: 0.206, SD: 0.16 • F median: 0.151, SD: 0.206

29. Ageing Precision and Bias • 3 Labs • Cooperative Ageing Lab • OR and CA commercial (1986-present), NWFSC Survey • WDFW • CDFG (only samples pre ~1980s) • Surface ages • pre 1980s • OR 2001-2004 • Combo method • OR 1981-1984, 1987-1988, 1991-1997 (reader issues) • WA ~1990 – 2009 • Break and Burn • NWFSC survey • OR (1985-1986, 1989-1990, 1998-1999, 2007-present) • WA (2009-present) • CA (1986-present)

30. Ageing Error Methods • Punt et al. 2008; simulation tested • Estimate ageing error assuming one reader is unbiased • based on bomb radiocarbon age validation • Data pooled across reader • Early surface age error estimate for pre-1990s samples • Sample sizes – 100’s of double and triple reads • Model selection – AIC • Shape of bias, shape of error, minus age, and plus age

31. Ageing Error - Results

32. Pikitch Discard Data

33. WCGOPObserverLengths Summer Winter

34. WCGOP Observer Data 2002-2010– SummerSpatial distribution of observed catch

35. WCGOP Observer Data 2002-2010 – WinterSpatial distribution of observed catch

36. Fraction DiscardedDiscard/Total Catch

37. Commercial Length Comps – North Summer Winter

38. Commercial Age Comps Summer Winter

39. Landings

40. 2011 v. 2013Landings

41. CPUE standardization steps: Data filtering Identify the covariates to use/test Build a regression model that best fits the data Create an index of abundance with some credibility interval

42. 1. Data Filtering Spatial Spatially defined fishing grounds • 2003-2008 • Summer – May-October • Shoreward of 75fm • remove tows with flatfish catch rates in lower 10% • Winter – Nov-Feb • Seaward of 150fm • Remove tows with petrale catch rate in lower 10% Data quality Remove • Tows outside EEZ • mid-water trawls • Tow duration ≤0.2 hours • Difference between map and logbook depths > 70 fm • Tows ≥ 300 fm (S); ≥ 400 fm (W) • Tow duration ≥ 4 hours (S); ≥ 6 hours (W) • Vessels < 5 years in fishery (sensitivity test) • Winter Nov-Dec data Output: average CPUE (lbs/hr) by fishing trip

43. 1. Data Filtering

44. 2. Covariates to test • Models for each fleet separately: • North winter, North summer, South winter, South summer • Time: year, bimonth • Space: spatial grid • Vessel effects: port, vessel ID, gear, targeting

45. 2013 model stratification

46. 3. Model building • Build a regression model • Data contains a lot of zero in addition to the positive data  delta (hurdle) model • Mixed effect model with vessel as random effect • Choose covariates through model selection (AIC) • Check model assumptions

47. Changes from 2011 • Summer data filtering corrected • Changed the “reference level” of the covariates during the index standardization to be the mean (continuous) or most frequently observed (categorical) • index of abundance can be interpreted as index per “reference” unit • calculate a confidence interval • Finer spatial stratification • Aggregate tow level data to trip level data • Greater independence • fishing tactics covariates • Sensitivity to random vessel effects • WA and OR aggregated into North fleet

48. The 2011 best main effect models (determined after model selection) Explained deviance

49. The 2011 best main effect models + removed tows outside EEZ Explained deviance

50. The 2011 best main effect models + removed tows outside EEZ + change “reference” levels Explained deviance