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

STAR Panel

Melissa Haltuch1, Kotaro Ono2, Juan Valero3

1NWFSC, Seattle2UW, SAFS, Seattle

3CAPAM, La Jolla

13 May 2013

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

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

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

Introduction - Management

Assessment

Status Year(s) OFL ACL

1984-1999

Near Target 1983-2006

3200-2762

3200-2762

2005 Precautionary

2007-2009

3025-2811

2499-2433

2009-2011

Overfished 2010-2012

2751-1279

1200-1160 Management actions since the late 1990s

– Area closures– Trip limits– Gear modifications– IFQ

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

Triennial Survey Timing

June 15

August 15

July 15

September 15

140

160

180

200

220

240

260

1979 1984 1989 1994 1999 2004 2009

Year

Ju

lian

da

y

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

Survey differences

Triennial NWFSCSystematic random stations on equally spaced transects

Randomly selected within stratified random block

AK class commercial trawlers65-147 feet

WC commercial trawlers65-92 feet

High opening Nor’Eastern trawl

4 panel Aberdeen style trawl

250 feet net to doors 205 feet net to doors

Roller gear (121’ footrope) Continuous disk footrope (104’)

Bare wire bottom bridles 8” disks in wings

6’ X 9’ V-Door 5’ X 7’ V-Door

5” mesh, 3.5” codend, 1.25” liner

5.5” mesh, 5” cod end, 2” liner

30 minute tow 15 minute tow

3.0 knot towing speed 2.2 knot towing speed

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

Catch rates: Triennial

Catch rates: NWFSC

Density: NWFSC

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

Mean fish length vs depth

50 100 150 200 250 300 350 400

1520

2530

3540

45

Triennal

Females

100 200 300 400

2030

4050

60

Males

100 200 300 400 500

2030

4050

NWFSC

Females

100 200 300 400 500

1520

2530

3540

45

Males

Depth (m)

Me

an

len

gth

(cm

)

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

-128 -126 -124 -122 -120 -118

3540

45

PSMFC areas

Longitude (°)

Latit

ude

(°)

1A

1B

1C

2A

2B

2C

3A

3S

-128 -126 -124 -122 -120 -11835

4045

INPFC areas

Longitude (°)

Latit

ude

(°)

CP

MT

EK

CL

VN

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

Model selection – residual deviance

Survey Model Mean

Tri_early Gamma-Strata:YearFixed 7814.3

Tri_early Lognormal-Strata:YearFixed 7655.1

Tri_late Gamma-Strata:YearFixed 6903.1

Tri_late Lognormal-Strata:YearFixed 6840.5

NWFSC Gamma-Strata:YearFixed 19885.2

NWFSC Lognormal-Strata:YearFixed 19723.7

Model fit - lognormal

Survey biomass estimates

Triennial length frequencies

NWFSC length frequencies

NWFSCagefrequency

NWFSC survey length at age

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

Biological Data - Weight-Length

NWFSC Survey

Biological Data – Maturity at length

Oregon Washington 2002

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

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)

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

Ageing Error - Results

Pikitch Discard Data

WCGOPObserverLengths

Su

mm

er

Win

ter

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

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

Fraction DiscardedDiscard/Total Catch

Fishing North winter North summer South winter South summerYear Mean SD Mean SD Mean SD Mean SD1985 0.0222 0.1103 0.0346 0.04191986 0.0215 0.1162 0.0343 0.04321987 0.027 0.1186 0.0315 0.045

2002 0.0077 0.0034 0.1856 0.0253 0.03720.024

4 0.0569 0.0158

2003 0.01 0.0064 0.1111 0.0252 0.00620.002

6 0.0325 0.0126

2004 0.0019 0.0008 0.0843 0.0244 0.05260.052

1 0.0343 0.0153

2005 0.0013 0.0009 0.0421 0.0112 0.00690.007

1 0.0122 0.0035

2006 0.0131 0.0073 0.078 0.0171 0.05980.044

6 0.036 0.0157

2007 0.0037 0.0015 0.1138 0.0232 0.01940.013

9 0.061 0.0209

2008 0.0275 0.0146 0.0502 0.0167 0.00990.005

6 0.0259 0.0147

2009 0.0253 0.0151 0.2018 0.0673 0.02210.014

7 0.0233 0.0082

2010 0.1971 0.0444 0.1037 0.0308 0.25840.071

7 0.0554 0.01192011 0.0017 0 0.037 0 0.0009 0 0.0411 02012 0.0006 0 0 0 0.0046 0 0 0

Commercial Length Comps – North

Sum

mer

Win

ter

Commercial Age Comps

Sum

mer

W

inte

r

Landings

2011 v. 2013Landings

CPUE standardization steps:

1. Data filtering

2. Identify the covariates to use/test

3. Build a regression model that best fits the

data

4. Create an index of abundance with some

credibility interval

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

1. Data Filtering

Tow by tow data

Trip by trip data

SummerNorth 79752 18627

South 16405 6645

WinterNorth 10936 3984

South 2841 1307

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

2013 model stratificatio

n

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

Changes from 2011

1. Summer data filtering corrected

2. 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

3. Finer spatial stratification

4. Aggregate tow level data to trip level data

• Greater independence

5. fishing tactics covariates

6. Sensitivity to random vessel effects

7. WA and OR aggregated into North fleet

The 2011 best main effect models (determined after model selection)

Winter Summer

WA 43% 30%

OR 34% 52%

CA 40% 40%

Explained deviance

The 2011 best main effect models

+ removed tows outside EEZ

Winter Summer

WA 43% 27%

OR 34% 42%

CA 40% 40%

Explained deviance

The 2011 best main effect models

+ removed tows outside EEZ

+ change “reference” levels

Winter Summer

WA 43% 27%

OR 34% 42%

CA 40% 40%

Explained deviance

The 2011 best main effect models

+ removed tows outside EEZ

+ change “reference” levels

+ standardized the index by its geometric mean (change of scale)

Winter Summer

WA 43% 27%

OR 34% 42%

CA 40% 40%

Explained deviance

2011 best main effect models

+ removed tows outside EEZ

+ change “reference” levels

+ standardized the index by its geometric mean (change of scale)

2011 best main effect models

+ trip level data

Winter Summe

r

WA 34% 32%

OR 35% 47%

CA 34% 42%

Explained deviance

2011 best main effects models

+ trip level data

2013 best main effects models

+ trip level data

Winter Summer

WA 34% 35%

OR 34% 48%

CA 38% 44%

Explained deviance

2013 best main effects models

+ trip level data

The 2013 best main effects models

+ trip level data

+targeting covariates

Winter Summer

WA 66% 66%

OR 74% 71%

CA 72% 65%

Explained deviance

The 2013 best main effects models

+ trip level data

+targeting covariates

The 2013 best main effects models

+ trip level data

+targeting covariates

+ mixed effect model

Winter Summer

WA 44% 67%

OR 68% 71%

CA 74% 65%

Explained deviance

Model fits

Lognormal componentSummer OR Winter OR

Final index of abundance

2013 assessment has a different spatial set-up:North fishery (WA+OR) and the South fishery (CA)

Graphs are scaled so that the 2004 index = 1.

WinterSumme

r

North 78% 74%

South 74% 65%

Explained deviance

Final index of abundance with prediction interval

Conclusions

- New CPUE methods didn’t radically change the index of abundance

- Advantages of 2013 approach1. Data are more independent (compared to the tow

by tow data)

2. The spatial stratification is finer

3. Calculate the prediction interval around the standardized index of abundance

4. Some vessel behavior is taken into account through the use of targeting covariates

5. Model fit improved by including targeting covariates

DataSummary

Responses to 2011 STAR panel recommendations

Establish a formal framework and to conduct petrale sole assessments jointly with Canada. • A formal framework for joint stock assessment and management of

U.S-Canadian transboundary groundfish stocks does not exist. This stock assessment follows the PFMC terms of reference for groundfish stock assessments.

 Conduct a formal review of all historical catch reconstructions and if possible stratify by month and area.• The PFMC is responsible for such reviews, resources not available. Document and review WCGOP discard estimates outside of the STAR panel process. • The WCGOP data have been documented but have not been reviewed

by the PFMC.  Combine Washington and Oregon fleets in future assessments within a coast-wide model.• Washington and Oregon fleets have been combined, landings are

summarized by port. Update maturity and fecundity information.• Not updated.

Responses to 2011 STAR panel recommendations

SS3, investigate simpler, less structured models, to compare and contrast results.• Simple model comparisons show similar results to SS3 (J. Cope , pers.

comm). The length binning structure in the stock assessment should be evaluated.• The impact of changing the bin size from 2 cm to 1 cm bins was

explored.  The residual patterns in the age-conditioned, length compositions from the surveys should be investigated and the potential for including time-varying growth, selectivity changes, or other possible solutions should be examined.• Options for better fitting all of the length and age data have been

explored via selectivity and fleet/model structure. A NMFS Fisheries and the Environment (FATE) funded project to investigate and conduct a meta-analysis of time-varying growth for California Current groundfish in underway.

 MSE is recommended to examine the likely performance of new flatfish control rules.• The NWFSC has not had the resources available to conduct an MSE for

the PFMC flatfish control rule.

Changes from 2011 Model

SS-V3.24o

Landings summarized by port of landing rather than area of catch.

Combining the Washington and Oregon fleets into a single northern fleet.

Use of the Oregon historical landings reconstruction.

Specification of the male growth parameters to be directly estimated rather than estimated as an offset to the female growth parameters.

Use of an early, pre-1990s, age error matrix for surface ages.

Addition of data for 2011 and 2012.

Base model

Coast-wide model 12-month model with seasonal fleet structure 4 fleets Sex-specific Asymptotic selectivity Blocks on selectivity and retention Estimate growth Estimate sex-specific natural mortality

– Diffuse prior on M Estimate steepness with R. Myer’s prior Composition effective sample sizes tuned

Estimated parameters

ParameterNumber

estimatedNatural mortality (M, female) 1Natural mortality (M, male) 1

Stock and recruitmentLn(R0) 1Steepness (h) 1Ln(Early Recruitment Deviations): 1845-1958 114Ln(Main Recruitment Deviations): 1959-2009 51

IndicesLn(q) – NWFSC survey -Ln(q) – Triennial survey (early and late) -Ln (q) – North winter commercial CPUE 1Ln (q) – South winter commercial CPUE 1Beta (power) – North winter commercial CPUE 1Beta (power) – South winter commercial CPUE 1Extra SD – NWFSC survey 1Extra SD – Early Triennial 1Extra SD – Late Triennial 1Extra SD – North winter commercial CPUE 1Extra SD – South winter commercial CPUE 1

Estimated parametersParameter Number estimated

Fisheries Selectivity (asymptotic, sex specific, with retention curves)

Length at peak selectivity 4

Ascending width 4

Male parameters 1 and 2 8

Retention parameters 1, 2, and 3 12

Selectivity time block parameters (Peak) 20Retention time block parameters (Inflection, Slope, Asymptote)

36

Surveys Selectivity (asymptotic, sex specific) Length at peak selectivity 3

Ascending width 3

Male 1 parameters 1 and 2 6Individual growth

Length at age min 2

Length at age max 2

von Bertalanffy K 2

CV of length at age min 2

CV of length at age max 2

Total: 119 + 180 recruitment deviations =299 estimated parameters

Growth

Parameter Value

Females:  

Length at Linf 60.32

von Bertalanffy K 0.13

CV of length at age min 0.18

CV of length at age max 0.03

Males:  

Length at Linf 46.79

von Bertalanffy K 0.21

CV of length at age min 0.13

CV of length at age max 0.05

Survey and Productivity parameters

Parameter Value

Catchability, Power, Extra SD: 

NWFSC survey catchability (q) 2.95

Triennial survey catchability (q) early, late 0.52; 0.73North winter commercial CPUE (Beta) 0.63 (0.15, 1.11)South winter commercial CPUE (Beta) -0.13 (-0.56, 0.3)Q_extraSD North Winter 0.082Q_extraSD South Winter 0.112Q_extraSD Triennial survey early 0.130Q_extraSD Triennial survey late 0.175Q_extraSD NWFSC -0.050 (-0.094, -0.006)

Productivity: 

R0 9.82

Steepness (h) 0.84

Female natural mortality (M) 0.16

Male natural mortality (M) 0.18

Survey abundance

q=0.52 q=0.73 q=2.95

Survey selectivity

Survey lengths

Survey lengths

NWFSC survey agesFemale Male

NWFSC female survey age-at-length

NWFSC male survey age-at-length

Commercial CPUE

Time varying selectivity

Time varying retention

North fleet end year selectivity and retention

South fleet end year selectivity and retention

Commercial lengthsFemale Male

Commercial lengthsFemale Male

Commercial agesFemale Male

Commercial agesFemale Male

Discard fraction (Discard/Total catch)

Discard mean weight

Discard lengths

Discard lengths

Discard length residuals

Discard length residuals

Tuning: Sigma R and Lengths

Sigma R in = 0.40 Sigma R out = 0.35

Lengths Ages

Fleet

Variance Adjustmen

t MeaneffNMeaninputN

Variance Adjustment

MeaneffN

MeaninputN

Winter north 2.0 1.1 7 1.0Summer north 1.4 1.0 1.7 1.0Winter south 1.6 1.1 1.9 0.9Summer south 1.2 1.0 1.4 1.1Early Triennial 1.3 1.1Late Triennial 1.0 1.1NWFSC 1.0 0.9 0.3 0.7

Biomass trajectory

Spawning Biomass Depletion

Recruitment deviations

Fishing mortality

Spawning potential ratio

Management performance

Retrospectives

Model Retrospectives

Assessment Year Base 2011 2010 2009 2008 2007

SSB Unfished 31,998 31,809 32,007 32,433 31,828 32,196

2007 Depletion 0.143 0.144 0.146 0.153 0.151 0.160

2008 Depletion 0.134 0.135 0.138 0.148 0.147 0.162

2009 Depletion 0.129 0.130 0.135 0.148 0.150 0.172

2010 Depletion 0.126 0.127 0.132 0.150 0.162 0.183

2011 Depletion 0.156 0.157 0.164 0.189 0.209 0.219

2012 Depletion 0.206 0.209 0.220 0.246 0.261 0.254

2013 Depletion 0.275 0.280 0.287 0.305 0.302 0.280

Sensitivities

Red-4 fleets w/ North comps

Mirrored

Green-6 fleets

Sensitivities:Removal of 2012 survey data

Green-index

Yellow-Ages Red-Lengths

LikelihoodProfiles

LikelihoodProfiles

BetweenAssessmentModelComparison

1999 – Red 2005 – Green 2009 – Blue 2011 – Light Blue 2013 - Black

Decision Table      State of nature      Low Base case High      M = 0.14 M = 0.16 M = 0.18

Relative probability 0.25 0.5 0.25

Management decision Year Catch

(mt) SB(mt) Depl SB (mt) Depl SB(mt) Depl

OFL

2015 3,944 11,546 0.334 11,921 0.373 12,361 0.4142016 3,914 11,568 0.335 11,847 0.370 12,198 0.4092017 3,722 11,063 0.320 11,241 0.351 11,492 0.3852018 3,485 10,422 0.302 10,526 0.329 10,702 0.3592019 3,279 9,862 0.286 9,934 0.310 10,070 0.3372020 3,133 9,446 0.274 9,523 0.298 9,651 0.3232021 3,043 9,161 0.265 9,264 0.290 9,407 0.3152022 2,990 8,967 0.260 9,108 0.285 9,273 0.3112023 2,958 8,828 0.256 9,007 0.281 9,197 0.3082024 2,935 8,721 0.253 8,934 0.279 9,142 0.306

Status quocatches

2015 2,592 11,546 0.334 11,921 0.373 12,361 0.4142016 2,592 12,336 0.357 12,611 0.394 12,946 0.4342017 2,592 12,661 0.367 12,814 0.400 13,021 0.4362018 2,592 12,750 0.369 12,791 0.400 12,884 0.4322019 2,592 12,744 0.369 12,700 0.397 12,709 0.4262020 2,592 12,705 0.368 12,605 0.394 12,559 0.4212021 2,592 12,659 0.367 12,527 0.391 12,451 0.4172022 2,592 12,616 0.365 12,469 0.390 12,379 0.4152023 2,592 12,579 0.364 12,428 0.388 12,332 0.4132024 2,592 12,547 0.363 12,397 0.387 12,300 0.412