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The Stock Synthesis Approach

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Based on many of the ideas proposed in Fournier and Archibald (1982), Methot ... Seasons for seasonal fisheries or seasonal growth. ... – PowerPoint PPT presentation

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Title: The Stock Synthesis Approach


1
The Stock Synthesis Approach
Based on many of the ideas proposed in Fournier
and Archibald (1982), Methot developed a stock
assessment approach and computer program called
Stock Synthesis. It has the following features
  • Multiple fisheries and surveys, each with its own
    selectivity curve.
  • Multinomial errors assumed for the observed age
    composition data (fisheries and surveys).
  • The analysis is tuned using multiple biomass or
    abundance indices (surveys, fishery effort or
    CPUE), assumed to have log-normal errors.

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Stock Synthesis (continued)
  • Catch biomass values are assumed to be known
    exactly and are removed mid-period. (There is no
    explicit fishing mortality coefficient.)
  • Selection can be a function of length or age (or
    both) and can differ by sex.
  • Mean weight-at-age (by sex) is derived from a
    growth model and a length-weight relationship.
  • Most parameters can be configured to vary with
    time (e.g., changing selection coefficients).
  • Unlike VPA or Cohort Analysis, Synthesis does not
    require complete catch-at-age data matrices.

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Stock Synthesis (continued)
  • Seasons for seasonal fisheries or seasonal
    growth.
  • Transition matrices can be used to create
    predicted distributions (e.g., age compositions
    with error).
  • Synthesis can accommodate numerous kinds of data
  • Observations of discarded amounts or percentages.
  • Age or length composition data for retained,
    discarded, or total catch.
  • Mean length-at-age data by fishery and survey.
  • Age composition within specified length ranges.
  • Mean body weight by fishery (retained or
    discarded).

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Stock Synthesis (continued)
  • The maximum likelihood method is used for
    estimating the model parameters.
  • log( Like. ) lj S log( Like.Component j )
  • Parameters can be constrained by including
    penalty functions as log-likelihood components
    and mimic a Bayesian estimation approach.
  • Synthesis II uses Auto-Diff Model Builder (ADMB)
    routines to find the parameter estimates.
  • ADMB allows Synthesis II to produce variance
    estimates for all estimated parameters and for
    quantities derived from the estimated parameters.

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Retention small fish are often discarded
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