Population analysis of coastal pelagic species off the USA Pacific coast using age-structured statistical

catch-at-age/length models

K. T. Hill and P. R. Crone NOAA Fisheries

Southwest Fisheries Science Center8604 La Jolla Shores DriveLa Jolla, CA 92037, USA

Stock assessments for CPS in 2011

Presentation outline•Overview of stock assessment model development

o From field to lab to analysis to management advice

•Pertinent differences between current Pacific sardine and Pacific mackerel modelso Data (time series) included in the modelo Parameterization (stock parameter) considerations

•P. mackerel and P. sardine stock assessments (overviews)

•Management procedureso Pacific sardine as example

•Future considerationso Model development for P. sardine and P. mackerel o International-based collaborative sampling/laboratory/modeling efforts for CPS

Stock assessments for CPS in 2011

Overview of stock assessment model development•Historical review of available data and modeling approaches over time

•Fishery-dependent sample data largely collected by state (and international) agencies

•Research survey data collected primarily by federal-based programs

•Laboratory work conducted by state and federal research efforts

•Formal population analysis conducted/coordinated by federal research programs

•Management processes are addressed annually through regional Council activities

Stock assessments for CPS in 2011

Pertinent differences between current sardine and mackerel models•Data (time series)

o Age/length distribution time series … length- vs. age-basedo Index of abundance time series … research survey- vs. fishery-based

•Parameterization (stock parameter)o Use of age and length data for evaluating selectivity, growth, etc.o Spawning stock—recruitment relationship

Distribution

Spawning Area

Fisheries

San Pedro

BahiaMagdalena

Ensenada

OR-WA

Monterey

San Diego

Pacific Mackerel Stock Assessment (2011)

Pacific Mackerel Stock Assessment (2011)

Data• Landings — USA from PacFIN/RecFIN and available at a fine scale

o International landings availability … much improved over time

• Biology — from state/federal sampling/laboratory programs and available at a fine scale, but …oLength … recreational fishery length information prior to 1992 (and you could even

argue 2004) caveatsoAge … no recreational fishery age informationoWeight … see Length aboveoMaturity … ‘long in the tooth’ caveats

• Indices of abundance — from state sampling programs and available at a fine scale, but …oCPFV logbook sampling program … future ‘applicability’ of this data source needs

further reviewoCRFS program … long-term funding concerns

Landings

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

29 32 35 38 41 44 47 50 53 56 59 62 65 68 71 74 77 80 83 86 89 92 95 98 01 04 07 10

Landings (mt)

Fishing year

CA Commercial

Mexico Commercial

CA Recreational (CPFV)

CA Recreational (non-CPFV)

Figure ES-1. Commercial and recreational landings (mt) of Pacific mackerel in the USA (CA commercial, recreational-CPFV, and recreational-non-CPFV) and Mexico (commercial), (1929-10).

Age Distribution Time Series (1983-10)Commercial Fishery – Model XA fits

Length Distribution Time Series (1985-10, 2004-10)Recreational Fishery – Model XA fits/diagnostics

Indices of Abundance

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1983 1986 1989 1992 1995 1998 2001 2004 2007 2010

Estimate (normalized)

Year

CPFV

CRFS

Figure 6 A&B. Indices of abundance: (A) CPFV (CPFV logbook sampling program) and CRFS (non-CPFV fisheries); and (B) the CRFS survey time series evaluated at the fishing mode level (CPFV Logbook=abbreviated CPFV in 6A, CRFS_1 = man-made, CRFS_2=beach/bank, CRFS_3=charter/party, CRFS_4=private/rental, CRFS_124=omits charter/party, and CRFS_1234=all modes). Note that only the CPFV and CRFS_124 indices were used in Model XA. Also, missing lines between data points reflects years with no sampling.

Biological Parameters – Model XA

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

0 1 2 3 4 5 6 7 8+

Proportion

Age (years)

Maturity

Natural mortality

Figure 7A-C. Biological parameters associated with the Pacific mackerel population associated withmaturity schedule and natural mortality.

Stock-Recruitment Relationship – Model XA

Selectivity – Model XA

Commercial fishery Recreational fishery

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1 2 3 4 5 6 7 8 9 10 11 12 13

Proportion

Age (years)

1985-10 CPFV2004-10 CRFS

Figure 12. Estimated time-varying selectivity distributions associated with model XA: (A) commercial fishery (1983-10); and (B) recreational fishery (1985-10 CPFV) and (2004-10 CRFS).

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

0 1 2 3 4 5 6 7 8 9 10 11 12

Proportion

Age (years)

1983-10 Commercial

Figure 12. Estimated time-varying selectivity distributions associated with model XA: (A) commercial fishery (1983-10); and (B) recreational fishery (1985-10 CPFV) and (2004-10 CRFS).

Estimated Biomass Time Series – Model XA

0

300,000

600,000

900,000

1,200,000

83 85 87 89 91 93 95 97 99 01 03 05 07 09 11

B (mt)

Fishing year

Figure 17. Estimated total stock biomass (age 1+ fish in mt, B) of Pacific mackerel based on the final Model XA (1983-11).

Estimated Recruitment Time Series – Model XA

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

3,500,000

83 86 89 92 95 98 01 04 07 10

R (1,000s of fish)

Fishing yearFigure ES4. Estimated recruitment (age-0 fish in 1,000s, R) of Pacific mackerel based on model XA, (1983-10). A confidence interval (95% CI) is also presented as dashed lines.

Harvest Guideline

Commercial landings (mt) and quotas

0

25,000

50,000

75,000

92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11

HG Landings

Figure 22 A-B. Harvest guideline statistics for Pacific mackerel: (A) commercial landings (USA directed fishery in mt) and quotas (HGs in mt), (1992-11); and (B) total landings (mt) and hypothetical quotas based on no USA ‘Distribution’ parameter in the harvest control rule. Incidental landings from Pacific Northwest fisheries are not included, but typically are limited, ranging 100 to 300 mt per year.

Landings (mt)

0

40,000

80,000

120,000

00 01 02 03 04 05 06 07 08 09 10 11

Fishing year

Estimated Biomass Time SeriesHistorical Assessment Period (2004-11)

0

400,000

800,000

1,200,000

1,600,000

62 66 70 74 78 82 86 90 94 98 02 06 10

Fishing year

VPA (2004)

ASAP (2005)

ASAP (2006)

ASAP (2007)

ASAP (2008)

SS AA (2009)

SS XA (2011)

Figure 21. Estimated total stock biomass (B age 1+ fish in mt) of Pacific mackerel for the historical assessment period (1994-11): VPA model-based assessments from 1994-04; ASAP model-based (2005-08); and SS model-based (2009-11).

B (mt)

“First and foremost, the population’s reproductive potential has been only lightly impacted from fishing pressure over the last decade, i.e., the estimated SPR time series, blah, blah, blah …”

Pacific mackerel – California Current Ecosystem

Brown bears – Cabinet Yaak Ecosystem

Pacific bluefin tuna – North Pacific Ocean Ecosystem

California condors – So. CA Coastal Mountain Range Ecosystem

Spawning Potential Ratio Time Series – Model XA

Real conservative benchmark say …

Reeeally conservative benchmarks say …

Ongoing Modeling Issues

• Scaling the population from a fully-depleted condition (early 1980s)

• Sensitivity to new data (e.g., SS model 2008)

• Implausibly high F-rates (SS models 2009-2010): aerial survey biomass treated as absolute

• Recent models had many selectivity parameters and time-varying elements resulting in model instability (i.e., over-parameterized)

Changes from Previous AssessmentsNEW MODEL STRUCTURE

Goal: more parsimonious model; robust to data/scaling; plausible F estimates

•Regional fisheries aggregated to MexCal and PacNW ‘fleets’

•Truncated time series (1993 start year)

•Fewer time-varying elements (selectivity and growth)

•Number of estimated parameters reduced from 132 to 61

NEW DATA SOURCES

•Ensenada fishery composition (1989-2009)

•SWFSC Acoustic survey time series (2006-2011)

Pacific Sardine Recovery and Fishery Expansion

San Pedro (SCA)

Ensenada (ENS)

Washington (WA)

Oregon (OR)

Monterey (CCA)

British Columbia

(BC)2000s

90s

80s

Fishery Compositions: Length, Age, & Selectivity

Age (yr)Length (cm)

Survey Indices of Biomass Selectivity

Estimated Stock Biomass Series from Base Model

988,385 mt

Estimated Stock Biomass and Recruitment Series from Current Base Model and Previous Stock Synthesis Models

Exploitation Rate

U.S. Sardine Management for 2012: OFL, ABC, and HGHarvest Formula Parameters Value

BIOMASS (ages 1+, mt) 988,385

Pstar (probability of overfishing) 0.45 0.40 0.30 0.20

BUFFERPstar (Sigma=0.36) 0.95577 0.91283 0.82797 0.73861

FMSY (stochastic, SST-independent) 0.18

FRACTION 0.15

CUTOFF (mt) 150,000

DISTRIBUTION (U.S.) 0.87

Amendment 13 Harvest Formulas MT

OFL = BIOMASS * FMSY * DISTRIBUTION 154,781

ABC0.45 = BIOMASS * BUFFER0.45 * FMSY * DISTRIBUTION 147,935

ABC0.40 = BIOMASS * BUFFER0.40 * FMSY * DISTRIBUTION 141,289

ABC0.30 = BIOMASS * BUFFER0.30 * FMSY * DISTRIBUTION 128,153

ABC0.20 = BIOMASS * BUFFER0.20 * FMSY * DISTRIBUTION 114,323

HG = (BIOMASS - CUTOFF) * FRACTION * DISTRIBUTION 109,409

Stock assessments for CPS in 2011Future considerations•Model development

o Using age- vs. length-based selectivity (sardine)o Down-weight fishery composition data per Francis (2011)o Time-varying selectivity/catchability considerationso Survey-based indices of abundance (mackerel)

•International-based collaborative effortso Synoptic CPS surveyso Adult sample collection & methods (ageing and reproductive biology)o Stock structure studieso Stock assessment workshops

AcknowledgmentsCDFO: Jake Schweigert, Linnea Flostrand, Jackie Detering

NWFSC: Richard Methot, Ian Taylor, Ian Stewart, Bob Emmett

WDFW: Carol Henry, Sandra Rosenfield, Jennifer Topping

ODFW: Jill Smith, Keith Matteson, Sheryl Manley, Kelly Corbet, David Wolfe Wagman

Northwest Sardine Survey, LLC: Jerry Thon, Tom Jagielo, Ryan Howe, Meghan Mikesell

CDFG: Kirk Lynn, Dianna Porzio, Mandy Lewis, Bill Miller, Paul Ton, Santi Luangpraseut, Briana Brady, Ed Dunn, Sonia Torres, Lou Zeidberg

SWFSC: Dave Griffith, Amy Hays, Dimitry Abramenkoff, Sue Manion, Bill Watson, Elaine Acuña, Andrew Thompson, Sherri Charter, Sarah Zao, Noelle Bowlin, David Demer, Juan Zwolinski, Randy Cutter, Kyle Byers, Josiah Renfree, Steve Sessions, John Field, Vardis Tsontos

IATTC: Mark Maunder and Alex Aires-da-Silva

INAPESCA: Manuel Nevarrez (Guaymas) and Ensenada field staff

CICIMAR: Roberto Felix-Uraga and Casimiro Quiñonez

STAR Panels: Andre Punt, Ray Conser, Larry Jacobson, Chris Francis, Mike Okoniewski, Lorna Wargo, Jonathan Deroba, John Casey, Briana Brady