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

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Presentation transcript:

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

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

YearsModelIssues Pre-1977 Yield, yield-per-recruit, simple stock-production modelsNo growth or recruitment variability Cohort analysis, coastwide, natural mortality (M)=0.2Unstable estimates Catch-AGE-ANalysis (CAGEAN; age-based availability), coastwide, M=0.2 Migratory dynamics not accounted for CAGEAN, area-specific, migratory and coastwide, M=0.2Trends differ by area CAGEAN, area-specific, M=0.2, age-based selectivityRetrospective pattern Statistical Catch-Age (SCA), area-specific, length-based selectivity, M=0.2 M estimate imprecise SCA, area-specific, length-based selectivity, M=0.15Poor fit to data New SCA, area-specific, constant age-based selectivity, M=0.15 Retrospective pattern SCA, area-specific, constant length-based selectivity, M=0.15 Migratory dynamics created bias SCA, coastwide, constant length-based selectivity, M=0.15 Retrospective pattern Assessment model evolution

Retrospective I: Age-based selectivity

Interim: Length-based selectivity Figure from: Clark and Hare, A

Retrospective II: Age-based selectivity Figure from: Clark and Hare, A

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

Retrospective III: Length-based selectivity

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

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

Regulatory areas

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

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

Trends in size-at-age Minimum size limit

Trends in size-at-age (Age-11 male halibut) Minimum size limit

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

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

Abundance by area has changed

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

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

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

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

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

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

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

Retrospective within the 2011 assessment (Sequentially removing data)

Retrospective: Symptoms Age-8 Recruits (millions)

Increasing penalty on large recruitment estimates

SSQs Increasing initial recruitment penalty  Males Females Total

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

Increased survey index weighting

Three tests: similar results

Selectivity – implementations

Time-varying selectivity

Selectivity SD time : Base-case: (50% of smoothing over length)

Selectivity SD time :

Retrospective: Solution

(Data only through 2011)

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

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.

Questions?