Influence of selectivity and size composition misfit on the scaling of population estimates and possible solutions: an example with north Pacific albacore
Steven L. H. Teo and Kevin R. PinerSouthwest Fisheries Science Center
CAPAM Selectivity Workshop11-14 March
What is the Problem?
• Highly migratory species move around a lot!
• Regional fisheries• Many HMS assessments do not
model movement due to lack of consistent tagging data
• Assume well-mixed stock and differences in selex used as proxies for movements
• But selex processes modeled as less variable in time and space than actual movements
What is the Problem?
• May cause important misfit to size compositions
• Influence recruitment and population scaling
• Similar to mis-specified time-varying selex
• In addition, mis-specified selex of one regional fishery can be strongly linked to selex of other fisheries catching
Albacore non-example
1965 1970 1975 1980 1985 1990 1995 2000 2005 20100
100000
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600000
0.0010.010.025
Spaw
ning
Bio
mas
s (10
00 t)
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 110
10.2
10.4
10.6
10.8
11
11.2
Size composition weighting
LN_R
0
• 16 fleets, 8 fisheries dependent indices, and conditional age-at-length
• Estimate growth• Spawning biomass scaled
strongly with weighting of size composition data
• Size composition weighted to 0.01
• R0 vs Weighting plot• R0 profile plots
Albacore Piner PlotsSize composition weighting of 0.01
Albacore Piner PlotsSize composition weighting of 1.0
Plan BWestern Pacific Eastern Pacific
• Operating model based on Piner et al. 2009 SS model of Pacific bluefin tuna with 2 box annual movement (no tagging data)
• Somewhat funky movement model • All fish move back to western Pacific after every year
and no fish move to eastern Pacific after age 4• Created synthetic data set from the model (expected
data without obs errors)
Age 1-4
Age 1-5
7 fisheries4 longline indices1 age-0 index
2 fisheries (1 selex)3 purse seine indicesAge-based logistic selex
SS Estimation Model
• Estimated dynamics using SS model with no movement• Compare different methods of dealing with the selectivity and
misfit1. Estimate EPO selex (with and without time blocks)2. Fix selex with previous model run and don’t fit to lencomp
data (with and without time blocks)3. Downweight lencomp data4. Annual time-varying selex5. Calc average selex from annual time-varying selex and
don’t fit to data (with and without time blocks) 6. Kitakado the EPO selex (with and without time blocks)7. Kitakado the EPO selex with time-varying selex to help
with convergence
Eastern Pacific Size data
Selectivity of Eastern Pacific PS
0 50 100 150 200 250 3000.0
0.1
0.2
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0.5
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1.0
Est Selex no tblk
Est Selex tblk52-93
Est Selex tblk94-07
Time-Varying Selectivity
Eastern Pacific Size Comp Fits
Estimate selectivity with no time block
Eastern Pacific Size Comp Fits
Recruitment
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True Modelest True ModelEst F8Fix F8Dwt F8TimeVary F8Avg F8 tblkKK F8 tblkKK F8 rndwlkKK F8Est F8 tblkFix F8 tblk
Recr
uitm
ent (
1000
fish
)
Spawning Biomass
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19701973
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True ModelEst SlxFix SlxTimeVary Slx
Spaw
ning
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mas
s (1
000
t)
SSB with Timeblocks in Selectivity
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19601964
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0
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Operating ModelEst SlxFix SlxTimeVary SlxEst Slx tblkFix Slx tblk
Spaw
ning
Bio
mas
s (1
000
t)
SSB using Kitakado Method
19521955
19581961
19641967
19701973
19761979
19821985
19881991
19941997
20002003
20060
20000
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True ModelEst SlxTimeVary SlxEst Slx tblkKK F8KK F8 tblk
Spaw
ning
Bio
mas
s (1
000
t)
Prelim Results & To Do List
• See Felipe’s talk• R0 profile (aka Piner Plots) useful in
understanding scaling influences in model• Do time-varying selex at least once to understand
how selex might be changing – try non-parametric selex
• Create a new synthetic data set with a simpler model (fewer fisheries & indices) with varying amounts of movement
• Include observation and other process errors• How does that affect management?
Averaging Blocks of Selectivity from Time-varying Selectivity
• Fit time-varying selex model
• Average the annual selex for wanted time blocks
• Use selex24.xls and solver to get selex parms
• Use parms in fixed selex for fishery and don’t fit to size comp data
