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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.
FW599 Winter 2008
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.
FW599 Winter 2008
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).FW599 Winter 2008
Stock Synthesis (continued)
• The maximum likelihood method is used for estimating the model parameters.
log( Like. ) = j * 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.
FW599 Winter 2008
Double-Logistic Selection
0%
25%
50%
75%
100%
3 5 7 9 11 13 15 17 19 21 23 25 27
Age
Sel
ectio
n C
oeffi
cien
t
domed asymptotic
FW599 Winter 2008
Small Fish are Often Discarded
0%
25%
50%
75%
100%
22 23 24 25 26 27 28 29 30 31 32 33 34 35 36Length (cm)
Ret
aine
d
obs Male obs Fem est Male est Fem T&D Mal T&D Fem
1975 Study
1988 Study
FW599 Winter 2008
Retention – small fish are often discarded
Size-Selection can Distort Size-at-Age
Length
0
20
40
60
80
100
10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
No.
Fis
h
0%
25%
50%
75%
100%
Selection
0
20
40
60
80
100
10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
No.
Fis
h
FW599 Winter 2008
Monthly Landings of Petrale Sole
0
100
200
1991 1992 1993 1994 1995 1996 1997 1998
Met
ric T
ons
CA OR WA
FW599 Winter 2008
Age Composition Changes Seasonally
0%
4%
8%
12%
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17+
Break & Burn Age (yr) - Sexes Combined
Winter Summer
FW599 Winter 2008
There is Strong Sexual Dimorphism
Length (cm)
0%
4%
8%
12%
<24 26 30 34 38 42 46 50 54 58
Winter Male Winter Fem
0%
8%
16%
<24 26 30 34 38 42 46 50 54 58
Summer Male Summer Fem
FW599 Winter 2008
Yin's Experiments with Stock Synthesis
29 factorial design with 4 x 200 replicates. NumYrs (8 v 16) F trend (0.1 v 0.3) SmplSize (100 v 400) CatCV (10% v 20%) EffortCV (20% v 80%) FishSel (dom v asym) SurvCV (20% v 80%) RecVar (cons v var) NatlMort (0.2 v 0.4)
Simple Synthesis model configuration with annual catch and effort data from one fishery, one annual survey biomass index, and age composition data for both.
(1) Generate random data sets with known properties.(2) Compare Synthesis estimates with true values.
FW599 Winter 2008
Stock Synthesis Experiments (cont.)
Main Effects - Bias in Estimates of Ending Biomass
RecVarFishSelCatchCVFTrendNatlMortSurvCVEffortCVSmplSizeNumYrs
var
con
domas
y0.
20.
10.
030.
010.4
0.2
0.8
0.2
0.8
0.2
400
10016 8
0.130
0.105
0.080
0.055
0.030
en
d B
io
Main Effects Plot - Data Means for end Bio
FW599 Winter 2008
Stock Synthesis Experiments (cont.)
Main Effects - Bias in Estimates of Starting Biomass
RecVarFishSelCatchCVFTrendNatlMortSurvCVEffortCVSmplSizeNumYrs
var
con
domas
y0.
20.
10.
030.
010.4
0.2
0.8
0.2
0.8
0.2
400
10016 8
0.068
0.056
0.044
0.032
0.020
sta
rt B
io
Main Effects Plot - Data Means for start Bio
FW599 Winter 2008
Stock Synthesis Experiments (cont.)
Main Effects - Bias in Estimates of Depletion
RecVarFishSelCatchCVFTrendNatlMortSurvCVEffortCVSmplSizeNumYrs
var
con
domas
y0.
20.
10.
030.
010.4
0.2
0.8
0.2
0.8
0.2
400
10016 8
0.024
0.020
0.016
0.012
0.008
en
dB
/B0
Main Effects Plot - Data Means for endB/B0
FW599 Winter 2008
Stock Synthesis Experiments (cont.)
Main Effects - Bias in Estimates of Ending Recruitment
RecVarFishSelCatchCVFTrendNatlMortSurvCVEffortCVSmplSizeNumYrs
var
con
domas
y0.
20.
10.
030.
010.4
0.2
0.8
0.2
0.8
0.2
400
10016 8
0.150
0.125
0.100
0.075
0.050
en
d R
ec
Main Effects Plot - Data Means for end Rec
FW599 Winter 2008
Stock Synthesis Experiments (cont.)
Main Effects - Precision in Ending Biomass Estimates
RecVarFishSelCatchCVFTrendNatlMortSurvCVEffortCVSmplSizeNumYrs
var
con
domas
y0.
20.
10.
030.
010.4
0.2
0.8
0.2
0.8
0.2
400
10016 8
0.45
0.40
0.35
0.30
0.25
en
d B
io
Main Effects Plot - Data Means for end Bio
FW599 Winter 2008
Stock Synthesis Experiments (cont.)
Main Effects - Precision in Starting Biomass Estimates
RecVarFishSelCatchCVFTrendNatlMortSurvCVEffortCVSmplSizeNumYrs
var
con
domas
y0.
20.
10.
030.
010.4
0.2
0.8
0.2
0.8
0.2
400
10016 8
0.29
0.24
0.19
0.14
0.09
sta
rt B
io
Main Effects Plot - Data Means for start Bio
FW599 Winter 2008
Stock Synthesis Experiments (cont.)
Main Effects - Precision in Estimates of Depletion
RecVarFishSelCatchCVFTrendNatlMortSurvCVEffortCVSmplSizeNumYrs
var
con
domas
y0.
20.
10.
030.
010.4
0.2
0.8
0.2
0.8
0.2
400
10016 8
0.23
0.21
0.19
0.17
0.15
en
dB
/B0
Main Effects Plot - Data Means for endB/B0
FW599 Winter 2008
Stock Synthesis Experiments (cont.)
Main Effects - Bias in Ending Recruitment Estimates
RecVarFishSelCatchCVFTrendNatlMortSurvCVEffortCVSmplSizeNumYrs
var
con
domas
y0.
20.
10.
030.
010.4
0.2
0.8
0.2
0.8
0.2
400
10016 8
0.55
0.50
0.45
0.40
0.35
en
d R
ec
Main Effects Plot - Data Means for end Rec
FW599 Winter 2008
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