Figure 1. King crab fishing districts and sections of Statistical Area Q.
43
Figure 2. Closed water regulations in effect for the Norton Sound commercial crab fishery.
44
0.0
0.4
0.8
Commercial Harvest
6
5
4
3
2
1
1976
1979
1982
1985
1988
1991
1994
1997
2000
2003
2006
2009
2012
2000
2003
2006
2009
2012
2003
2006
2009
2012
2003
2006
2009
2012
0.0
0.4
0.8
Winter Pot Survey
1976
1979
1982
1985
1988
1991
1994
1997
0.0
0.4
0.8
Summer Trawl Survey
1976
1979
1982
1985
1988
1991
1994
1997
2000
0.0
0.4
0.8
Summer Observer Survey
1976
1979
1982
1985
1988
1991
1994
1997
2000
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 3. Observed fishery and survey length compositions by data source for the Norton Sound red
king crab stock from 1976-2013.
45
150
15
20
1975
2
4
6
8
1980
500
opefn
150
4
6
8
10
1980
200
opefn
150
0
2
4
6
opefnn
8
1990
2000
2010
dat$iw + 1975
0 50
opefn
2.0
1.0
100
2
Observer
survey
w pefnn
0.0
50
2010
0
0
Observer
survey
w pefn
0
2000
year[-c(1, 16, dat$ny + 1)]
500
Winterscefnn
pot survey
1990
10
150
300
400 800
10
0
100
2005
200
0
500
wpefn
20
10
0
0
1995
0
scefn
400 800
800 1000
wpefn
600
1985
dat$it + 1975
200
400
100 160
40
10
0
0
200
Winterscefn
pot survey
Frequency
5
Commercial
tefnn Catch
scefn
10 20 30
Commercial
tefn Catch
0
Frequency
tefn
0
0 50
100
0 50
tefn
1.0
50
Frequency
Trawl survey
150
2.0
Trawl survey
0.0
Frequency
Effective sample size
1990
2000
2010
dat$io + 1975
Figure 4a: Input effective versus estimated implied sample size: (1) frequency (Left), (2) correlation
(Center), and (3) time series (Right). (alternative model 0)
46
Effective sample size
Trawl survey
150
tefn
50
0
15
20
1975
300
400
2
4
6
8
10
1980
wpefn
400
500
0
6
8
10
0
0
20
40 60
80 100
opefn
1980
opefn
40 80
1.0
0.0
4
Observer
survey
w pefnn
opefn
2.0
Observer
survey
w pefn
2
2010
0
2
4
6
opefnn
8
10
1990
2000
2010
dat$iw + 1975
120
300
2000
0
0
200
1990
year[-c(1, 16, dat$ny + 1)]
200 400
wpefn
20
10
100
200 400
0
scefn
0
Winterscefnn
pot survey
0
0
2005
dat$it + 1975
200 400
500
1995
200 400
200
1985
20 60
100
Winterscefn
pot survey
Frequency
10
0
4
0
Frequency
5
Commercial
tefnn Catch
scefn
8
12
Commercial
tefn Catch
0
Frequency
100
150
150
50
0 50
tefn
4
2
0
Frequency
6
Trawl survey
1990
2000
2010
dat$io + 1975
Figure 4b: Input effective versus estimated implied sample size: (1) frequency (Left), (2) correlation
(Center), and (3) time series (Right). (alternative model 2.i)
47
Effective sample size
Trawl survey
200
tefn
50
0
opefn
60
150
1980
wpefn
0
2
4
6
8
80
10
1980
opefn
2
4
6
opefnn
8
2000
2010
1990
2000
2010
dat$iw + 1975
60
0
1990
year[-c(1, 16, dat$ny + 1)]
0 20
opefn
3.0
1.5
40
10
Observer
survey
w pefnn
0.0
20
8
250
300
Observer
survey
w pefn
0
6
0 100
wpefn
15
200
4
Winterscefnn
pot survey
0 5
Frequency
Frequency
50 100
2
2005
0 50
scefn
0
1995
dat$it + 1975
150
200
Winterscefn
pot survey
0
1985
250
150
1975
0 100
100
20
10
60
50
15
0 50
scefn
4
0
10
Commercial
tefnn Catch
8
12
Commercial
tefn Catch
5
20
150
0
Frequency
100
150
150
50
0 50
tefn
4
2
0
Frequency
6
Trawl survey
1990
2000
2010
dat$io + 1975
Figure 4c: Input effective versus estimated implied sample size: (1) frequency (Left), (2) correlation
(Center), and (3) time series (Right) (alternative model 2.io).
48
100 110 120 130
0.8
0.2
0.0
90
100 110 120 130
100 110 120 130
lengthclass
90
100 110 120 130
lengthclass
0.6
0.4
0.0
0.2
0.4
0.0
0.2
0.4
0.2
0.0
90
80
Commercial 93-12 Selectivity
sc3p
0.6
0.8
1.0
lengthclass
sc1p
wpotp
0.6
0.8
1.0
lengthclass
80
0.6
trawlpa
80
Commercial 77-92 Selectivity
1.0
90
Winter pot Selectivity
0.8
80
0.4
0.8
0.6
0.4
0.2
0.0
0.0
0.2
0.4
moltp
trawlpn
0.6
0.8
1.0
ADFG Trawl Selectivity
1.0
NOAA Trawl Selectivity
1.0
Molting Probability
80
90
100 110 120 130
lengthclass
80
90
100 110 120 130
lengthclass
Figure 5a. Estimated molting probability and trawl/pot selectivity (alternative model 0).
49
100 110 120 130
0.8
0.2
0.0
90
100 110 120 130
100 110 120 130
lengthclass
90
100 110 120 130
lengthclass
0.6
0.4
0.0
0.2
0.4
0.0
0.2
0.4
0.2
0.0
90
80
Commercial 93-12 Selectivity
sc3p
0.6
0.8
1.0
lengthclass
sc1p
wpotp
0.6
0.8
1.0
lengthclass
80
0.6
trawlpa
80
Commercial 77-92 Selectivity
1.0
90
Winter pot Selectivity
0.8
80
0.4
0.8
0.6
0.4
0.2
0.0
0.0
0.2
0.4
moltp
trawlpn
0.6
0.8
1.0
ADFG Trawl Selectivity
1.0
NOAA Trawl Selectivity
1.0
Molting Probability
80
90
100 110 120 130
lengthclass
80
90
100 110 120 130
lengthclass
Figure 5b. Estimated molting probability and trawl/pot selectivity (alternative model 2.i).
50
100 110 120 130
0.8
0.2
0.0
90
100 110 120 130
100 110 120 130
lengthclass
90
100 110 120 130
lengthclass
0.6
0.4
0.0
0.2
0.4
0.0
0.2
0.4
0.2
0.0
90
80
Commercial 93-12 Selectivity
sc3p
0.6
0.8
1.0
lengthclass
sc1p
wpotp
0.6
0.8
1.0
lengthclass
80
0.6
trawlpa
80
Commercial 77-92 Selectivity
1.0
90
Winter pot Selectivity
0.8
80
0.4
0.8
0.6
0.4
0.2
0.0
0.0
0.2
0.4
moltp
trawlpn
0.6
0.8
1.0
ADFG Trawl Selectivity
1.0
NOAA Trawl Selectivity
1.0
Molting Probability
80
90
100 110 120 130
lengthclass
80
90
100 110 120 130
lengthclass
Figure 5c. Estimated molting probability and trawl/pot selectivity (alternative model 2.io).
51
8
Trawl survey crab abundance
4
0
2
Crab Abundance (million)
6
Observed
Predicted
1975
1980
1985
1990
1995
2000
2005
2010
Year
Figure 6a. Area-swept (observed) and model-estimated trawl survey abundance (≥ 74 mm CL)
(alternative model 0).
52
8
Trawl survey crab abundance
4
0
2
Crab Abundance (million)
6
Observed
Predicted
1975
1980
1985
1990
1995
2000
2005
2010
Year
Figure 6b. Area-swept (observed) and model-estimated trawl survey abundance (≥ 74 mm CL)
(alternative model 2.i).
53
8
Trawl survey crab abundance
4
0
2
Crab Abundance (million)
6
Observed
Predicted
1975
1980
1985
1990
1995
2000
2005
2010
Year
Figure 6c. Area-swept (observed) and model-estimated trawl survey abundance (≥ 74 mm CL)
(alternative model 2.io).
54
10
Modeled crab abundance July 01
6
4
0
2
Abundance (million crabs)
8
total
legal
recruits
1980
1990
2000
Year
Figure 7a. Estimated total, legal, and recruitment (model 0).
55
2010
10
Modeled crab abundance July 01
6
4
0
2
Abundance (million crabs)
8
total
legal
recruits
1980
1990
2000
Year
Figure 7b. Estimated total, legal, and recruitment (model 2.i).
56
2010
10
Modeled crab abundance July 01
6
4
0
2
Abundance (million crabs)
8
total
legal
recruits
1980
1990
2000
Year
Figure 7c. Estimated total, legal, and recruitment (model 2.io).
57
2010
Estimated abundance by length class
1500
0
500
1000
Abundance
2000
2500
74-83
84-93
94-103
104-113
114-123
> 124
1980
1990
2000
year
Figure 8a. Estimated abundance by length class (model 0).
58
2010
2500
Estimated abundance by length class
1500
1000
0
500
Abundance
2000
74-83
84-93
94-103
104-113
114-123
> 124
1980
1990
2000
year
Figure 8b. Estimated abundance by length class (model 2.i).
59
2010
Estimated abundance by length class
1000
0
500
Abundance
1500
2000
74-83
84-93
94-103
104-113
114-123
> 124
1980
1990
2000
year
Figure 8c. Estimated abundance by length class (model 2.io).
60
2010
MMB July 01
10
8
2
4
6
MMB (million lb)
12
14
BMSY 4.181 mil.lb
MMB 3.656 mil.lb
Legal B 3.048 mil.lb
OFL 0.437 mil.lb
ABC 0.394 mil.lb
1980
1990
2000
Year
Figure 8a. Estimated model MMB (model 0). The dashed line shows Bmsy.
61
2010
MMB July 01
10
8
4
6
MMB (million lb)
12
14
BMSY 4.237 mil.lb
MMB 3.721 mil.lb
Legal B 3.216 mil.lb
OFL 0.464 mil.lb
ABC 0.417 mil.lb
1980
1990
2000
Year
Figure 8b. Estimated model MMB (model 2.i). The dashed line shows Bmsy.
62
2010
MMB July 01
8
4
6
MMB (million lb)
10
12
BMSY 4.193 mil.lb
MMB 3.705 mil.lb
Legal B 3.192 mil.lb
OFL 0.463 mil.lb
ABC 0.417 mil.lb
1980
1990
2000
Year
Figure 8c. Estimated model MMB (model 2.io). The dashed line shows Bmsy.
63
2010
7
Summer commercial standardized cpue
0
1
2
3
CPUE
4
5
6
Predicted
Observed
1980
1990
2000
2010
Year
Figure 9a. Standardized summer commercial fishery CPUE with 95% CI (solid: modeled, dash: with
additional variance) (model 0).
64
7
Summer commercial standardized cpue
0
1
2
3
CPUE
4
5
6
Predicted
Observed
1980
1990
2000
2010
Year
Figure 9b. Standardized summer commercial fishery CPUE with 95% CI (solid: modeled, dash: with
additional variance) (model 2.i).
65
7
Summer commercial standardized cpue
0
1
2
3
CPUE
4
5
6
Predicted
Observed
1980
1990
2000
2010
Year
Figure 9c. Standardized summer commercial fishery CPUE with 95% CI (solid: modeled, dash: with
additional variance) (model 2.io).
66
0.10
0.00
0.05
0.2
0.0
1980
1990
2000
Year
Figure 10a: Total catch and model-estimated harvest rate (model 0).
67
2010
Estimated harvest rate
0.15
0.20
0.6
0.4
Total Catch (million)
0.25
0.8
0.30
Total Catch
Estimated Harvest Rate
0.35
1.0
Total catch & Harvest rate
0.10
0.00
0.05
0.2
0.0
1980
1990
2000
Year
Figure 10b: Total catch and model-estimated harvest rate (model 2.i).
68
2010
Estimated harvest rate
0.15
0.20
0.6
0.4
Total Catch (million)
0.25
0.8
0.30
Total Catch
Estimated Harvest Rate
0.35
1.0
Total catch & Harvest rate
0.10
0.00
0.05
0.2
0.0
1980
1990
2000
Year
Figure 10c: Total catch and model-estimated harvest rate (model 2.io).
69
2010
Estimated harvest rate
0.15
0.20
0.6
0.4
Total Catch (million)
0.25
0.8
0.30
Total Catch
Estimated Harvest Rate
0.35
1.0
Total catch & Harvest rate
Residuals Histogram, Q-Q Plot, Predicted vs. Residual
6
predicted vs. residual
-500 0
500
1500
500
-1000
-0.5
0.5
1.5
2000
Normal
Plot
TheoreticalQ-Q
Quantiles
4000
6000
predicted
residual
(rept$ett1 vs.
+ rept$ett2)
-2.5
-1.5
-0.5
resd.cpue
0.5
0.0
-2.0
-1.0
resd.cpue
0.0
-2.0
-1.0
Sample Quantiles
10
5
0
Frequency
15
1.0
Commercial
resd.traw CPUE
l
-1.5
1.0
-1500
0
resd.trawl
500
-1000
0
Sample Quantiles
4
3
2
0
1
Frequency
5
1500
Normal Q-Q Plot
1500
Trawl survey
-2
-1
0
1
Theoretical Quantiles
2
1.0 1.5 2.0 2.5 3.0 3.5
rept$ecpue[-c(1, 13, 16, dat$ny)]
Figure 11a: Histogram of residuals, QQ plot, and predicted vs. residual plots for observed versus for model
fitted to trawl survey and summer commercial fishery CPUE (model 0).
70
Residuals Histogram, Q-Q Plot, Predicted vs. Residual
Normal Q-Q Plot
predicted vs. residual
500 1000
-500
0
resd.trawl
500 1000
0
-500
0
2
1
Frequency
3
Sample Quantiles
4
Trawl survey
0
500
1500
-1.5
1.5
2000
6000
0.5
0.5
predicted
residual
(rept$ett1 vs.
+ rept$ett2)
resd.cpue
-1.5 -1.0 -0.5 0.0
Sample Quantiles
10
5
4000
0
Frequency
0.5
Normal
Plot
TheoreticalQ-Q
Quantiles
15
Commercial
resd.traw CPUE
l
-0.5
-1.5 -1.0 -0.5 0.0
-1000
-2.0
-1.0
0.0 0.5 1.0
resd.cpue
-2
-1
0
1
Theoretical Quantiles
2
0.5
1.0
1.5
2.0
2.5
3.0
rept$ecpue[-c(1, 13, 16, dat$ny)]
Figure 11b: Histogram of residuals, QQ plot, and predicted vs. residual plots for observed versus for model
fitted to trawl survey and summer commercial fishery CPUE (model 2.i).
71
Residuals Histogram, Q-Q Plot, Predicted vs. Residual
Normal Q-Q Plot
predicted vs. residual
500 1000
1000
0.5
1.5
2000
4000
6000
0
-1.5
resd.cpue
-0.5 0.0 0.5
predicted
residual
(rept$ett1 vs.
+ rept$ett2)
-1.5
10
-0.5
Normal
Plot
TheoreticalQ-Q
Quantiles
Sample Quantiles
15
Commercial
resd.traw CPUE
l
5
500
-500
-1.5
-0.5 0.0 0.5
0
0
resd.trawl
1000
500
-500
0
-1000
Frequency
0
Sample Quantiles
4
3
2
1
Frequency
5
6
Trawl survey
-2.0
-1.0
0.0 0.5 1.0
resd.cpue
-2
-1
0
1
Theoretical Quantiles
2
1.0
1.5
2.0
2.5
3.0
3.5
rept$ecpue[-c(1, 13, 16, dat$ny)]
Figure 11c: Histogram of residuals, QQ plot, and predicted vs. residual plots for observed versus for model
fitted to trawl survey and summer commercial fishery CPUE (model 2.io).
72
1
3
5
Commercial Harvest
1975
1980
1985
1990
1995
2000
2005
2010
2000
2005
2010
2000
2005
2010
2000
2005
2010
1
3
5
Winter Pot Survey
1975
1980
1985
1990
1995
1
3
5
Trawl Survey
1975
1980
1985
1990
1995
1
3
5
Observer Survey
1975
1980
1985
1990
1995
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 12a: Bubble plot of predicted and observed length proportion (model 0). Black circle indicates
model estimates lower than observed, white circle indicates model estimates higher than observed. Size
of circle indicate degree of deviance (larger circle = larger deviance).
73
1
3
5
Commercial Harvest
1975
1980
1985
1990
1995
2000
2005
2010
2000
2005
2010
2000
2005
2010
2000
2005
2010
1
3
5
Winter Pot Survey
1975
1980
1985
1990
1995
1
3
5
Trawl Survey
1975
1980
1985
1990
1995
1
3
5
Observer Survey
1975
1980
1985
1990
1995
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 12b: Bubble plot of predicted and observed length proportion (model 2.i). Black circle indicates
model estimates lower than observed, white circle indicates model estimates higher than observed. Size
of circle indicate degree of deviance (larger circle = larger deviance).
74
1
3
5
Commercial Harvest
1975
1980
1985
1990
1995
2000
2005
2010
2000
2005
2010
2000
2005
2010
2000
2005
2010
1
3
5
Winter Pot Survey
1975
1980
1985
1990
1995
1
3
5
Trawl Survey
1975
1980
1985
1990
1995
1
3
5
Observer Survey
1975
1980
1985
1990
1995
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 12c: Bubble plot of predicted and observed length proportion (Alternative model 2.io). Black
circle indicates model estimates lower than observed, white circle indicates model estimates higher than
observed. Size of circle indicate degree of deviance (larger circle = larger deviance).
75
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1 2 3 4 5 6
1983Index
1 2 3 4 5 6
1989Index
1 2 3 4 5 6
1996Index
1 2 3 4 5 6
2002Index
1 2 3 4 5 6
2008Index
1 2 3 4 5 6
0.0
0.3
0.6
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1978
1 2 3 4 5 6
1984Index
1 2 3 4 5 6
1990Index
1 2 3 4 5 6
1997Index
1 2 3 4 5 6
2003Index
1 2 3 4 5 6
2009Index
1 2 3 4 5 6
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1979
1 2 3 4 5 6
1985Index
1 2 3 4 5 6
1992Index
1 2 3 4 5 6
1998Index
1 2 3 4 5 6
2004Index
1 2 3 4 5 6
2010Index
1 2 3 4 5 6
1: 74-83,
94-103, 4: 104-113,
6: >124
Index 2: 84-93, 3: Index
Index 5: 114-123,
Index
Index
Figure 13a: Modeled (dashed line) vs. observed (black dots) length class proportion for commercial catch
(model 0).
Index
76
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1980
1 2 3 4 5 6
1986Index
1 2 3 4 5 6
1993Index
1 2 3 4 5 6
1999Index
1 2 3 4 5 6
2005Index
1 2 3 4 5 6
2011Index
1 2 3 4 5 6
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1981
1 2 3 4 5 6
1987Index
1 2 3 4 5 6
1994Index
1 2 3 4 5 6
2000Index
1 2 3 4 5 6
2006Index
1 2 3 4 5 6
2012Index
1 2 3 4 5 6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
1977
commercial harvest length: observed vs predicted
1982
1 2 3 4 5 6
1988Index
1 2 3 4 5 6
1995Index
1 2 3 4 5 6
2001Index
1 2 3 4 5 6
2007Index
1 2 3 4 5 6
2013Index
1 2 3 4 5 6
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1 2 3 4 5 6
1983Index
1 2 3 4 5 6
1989Index
1 2 3 4 5 6
1996Index
1 2 3 4 5 6
2002Index
1 2 3 4 5 6
2008Index
1 2 3 4 5 6
Index
0.0
0.3
0.6
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1978
1 2 3 4 5 6
1984Index
1 2 3 4 5 6
1990Index
1 2 3 4 5 6
1997Index
1 2 3 4 5 6
2003Index
1 2 3 4 5 6
2009Index
1 2 3 4 5 6
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1979
1 2 3 4 5 6
1985Index
1 2 3 4 5 6
1992Index
1 2 3 4 5 6
1998Index
1 2 3 4 5 6
2004Index
1 2 3 4 5 6
2010Index
1 2 3 4 5 6
77
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1980
1 2 3 4 5 6
1986Index
1 2 3 4 5 6
1993Index
1 2 3 4 5 6
1999Index
1 2 3 4 5 6
2005Index
1 2 3 4 5 6
2011Index
1 2 3 4 5 6
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1981
1 2 3 4 5 6
1987Index
1 2 3 4 5 6
1994Index
1 2 3 4 5 6
2000Index
1 2 3 4 5 6
2006Index
1 2 3 4 5 6
2012Index
1 2 3 4 5 6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
1977
commercial harvest length: observed vs predicted
1: 74-83,
94-103, 4: 104-113,
6: >124
Index 2: 84-93, 3: Index
Index 5: 114-123,
Index
1982
1 2 3 4 5 6
1988Index
1 2 3 4 5 6
1995Index
1 2 3 4 5 6
2001Index
1 2 3 4 5 6
2007Index
1 2 3 4 5 6
2013Index
1 2 3 4 5 6
Index
Figure 13b: Modeled (dashed line) vs. observed (black dots) length class proportion for commercial catch
(model 2.i).
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1 2 3 4 5 6
1983Index
1 2 3 4 5 6
1989Index
1 2 3 4 5 6
1996Index
1 2 3 4 5 6
2002Index
1 2 3 4 5 6
2008Index
1 2 3 4 5 6
0.0
0.3
0.6
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1978
1 2 3 4 5 6
1984Index
1 2 3 4 5 6
1990Index
1 2 3 4 5 6
1997Index
1 2 3 4 5 6
2003Index
1 2 3 4 5 6
2009Index
1 2 3 4 5 6
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1979
1 2 3 4 5 6
1985Index
1 2 3 4 5 6
1992Index
1 2 3 4 5 6
1998Index
1 2 3 4 5 6
2004Index
1 2 3 4 5 6
2010Index
1 2 3 4 5 6
1: 74-83,
94-103, 4: 104-113,
6: >124
Index 2: 84-93, 3: Index
Index 5: 114-123,
Index
Index
Figure 13c: Modeled (dashed line) vs. observed (black dots) length class proportion for commercial catch
(model 2.io).
Index
78
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1980
1 2 3 4 5 6
1986Index
1 2 3 4 5 6
1993Index
1 2 3 4 5 6
1999Index
1 2 3 4 5 6
2005Index
1 2 3 4 5 6
2011Index
1 2 3 4 5 6
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
1981
1 2 3 4 5 6
1987Index
1 2 3 4 5 6
1994Index
1 2 3 4 5 6
2000Index
1 2 3 4 5 6
2006Index
1 2 3 4 5 6
2012Index
1 2 3 4 5 6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
0.0
0.3
0.6
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
dat$onc[, i] + dat$ooc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
dat$onc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[,
i] + dat$ooc[, i]
i]
i]
i]
i]
i]
0.0
1977
commercial harvest length: observed vs predicted
1982
1 2 3 4 5 6
1988Index
1 2 3 4 5 6
1995Index
1 2 3 4 5 6
2001Index
1 2 3 4 5 6
2007Index
1 2 3 4 5 6
2013Index
1 2 3 4 5 6
1 2 3 4 5 6
0.4
0.0 0.2
0.2 0.4
2002
0.0
0.2 0.4
2001
0.0
1 2 3 4 5 6
1995
1 2 3 4 5 6
2007
1 2 3 4 5 6
0.0 0.2 0.4
1 2 3 4 5 6
0.0 0.2 0.4
2006
0.2 0.4
0.0
0.2 0.4
0.0
0.4
0.0 0.2
0.4
0.0 0.2
0.2 0.4
1999
0.0
0.0 0.2 0.4
2005
1994
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.4
1992
1986
1 2 3 4 5 6
2008
1 2 3 4 5 6
2011
0.0 0.2
2010
0.2 0.4
0.0
0.2 0.4
0.4
0.0 0.2
0.2 0.4
0.0 0.2 0.4
2004
0.0 0.2
0.0 0.2
2009
1998
1985
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.4
1 2 3 4 5 6
1990
0.0
0.2 0.4
1997
1984
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.0 0.2 0.4
2003
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.0 0.2 0.4
1989
0.0
1996
0.0
0.2 0.4
1 2 3 4 5 6
1983
0.0
0.2 0.4
0.4
1 2 3 4 5 6
0.0 0.2
1988
0.0 0.2
0.4
1 2 3 4 5 6
0.4
1982
0.0
1981
0.0
0.2 0.4
Winter pot length: observed vs predicted
1 2 3 4 5 6
1 2 3 4 5 6
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 14a: Modeled (dashed line) vs. observed (black dots) length class proportion for winter pot survey
(model 0).
.
79
1 2 3 4 5 6
0.4
0.0 0.2
0.2 0.4
2002
0.0
0.2 0.4
2001
0.0
1 2 3 4 5 6
1995
1 2 3 4 5 6
2007
1 2 3 4 5 6
1 2 3 4 5 6
0.0 0.2 0.4
1 2 3 4 5 6
0.0 0.2 0.4
2006
0.2 0.4
0.0
0.2 0.4
0.0
0.4
0.0 0.2
0.4
0.0 0.2
0.2 0.4
1999
0.0
0.0 0.2 0.4
2005
1994
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.4
1992
1986
2008
1 2 3 4 5 6
2011
0.0 0.2
2010
0.2 0.4
0.0
0.2 0.4
0.4
0.0 0.2
0.2 0.4
0.0 0.2 0.4
2004
0.0 0.2
0.0 0.2
2009
1998
1985
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.4
1 2 3 4 5 6
1990
0.0
0.2 0.4
1997
1984
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.0 0.2 0.4
2003
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.0 0.2 0.4
1989
0.0
1996
0.0
0.2 0.4
1 2 3 4 5 6
1983
0.0
0.2 0.4
0.4
1 2 3 4 5 6
0.0 0.2
1988
0.0 0.2
0.4
1 2 3 4 5 6
0.4
1982
0.0
1981
0.0
0.2 0.4
Winter pot length: observed vs predicted
1 2 3 4 5 6
1 2 3 4 5 6
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 14b: Modeled (dashed line) vs. observed (black dots) length class proportion for winter pot survey
(model 2.i).
80
1 2 3 4 5 6
0.4
0.0 0.2
0.2 0.4
2002
0.0
0.2 0.4
2001
0.0
1 2 3 4 5 6
1995
1 2 3 4 5 6
2007
1 2 3 4 5 6
1 2 3 4 5 6
0.0 0.2 0.4
1 2 3 4 5 6
0.0 0.2 0.4
2006
0.2 0.4
0.0
0.2 0.4
0.0
0.4
0.0 0.2
0.4
0.0 0.2
0.2 0.4
1999
0.0
0.0 0.2 0.4
2005
1994
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.4
1992
1986
2008
1 2 3 4 5 6
2011
0.0 0.2
2010
0.2 0.4
0.0
0.2 0.4
0.4
0.0 0.2
0.2 0.4
0.0 0.2 0.4
2004
0.0 0.2
0.0 0.2
2009
1998
1985
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.4
1 2 3 4 5 6
1990
0.0
0.2 0.4
1997
1984
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.0 0.2 0.4
2003
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.0 0.2 0.4
1989
0.0
1996
0.0
0.2 0.4
1 2 3 4 5 6
1983
0.0
0.2 0.4
0.4
1 2 3 4 5 6
0.0 0.2
1988
0.0 0.2
0.4
1 2 3 4 5 6
0.4
1982
0.0
1981
0.0
0.2 0.4
Winter pot length: observed vs predicted
1 2 3 4 5 6
1 2 3 4 5 6
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 14c: Modeled (dashed line) vs. observed (black dots) length class proportion for winter pot survey
(model 2.io).
81
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.2 0.4
1991
0.0
0.2 0.4
0.4
2008
1 2 3 4 5 6
2010
0.0 0.2
0.4
2006
1 2 3 4 5 6
0.0 0.2
0.4
1 2 3 4 5 6
0.0 0.2
0.0 0.2
2002
1988
0.0
0.2 0.4
0.0
0.2 0.4
1985
1 2 3 4 5 6
1 2 3 4 5 6
2011
1 2 3 4 5 6
1 2 3 4 5 6
0.6
0.6
1 2 3 4 5 6
0.3
1994
0.0
0.3
1992
0.0
0.3
0.0
0.3
1 2 3 4 5 6
1990
1 2 3 4 5 6
1 2 3 4 5 6
0.3
2013
0.0
0.0
0.3
2012
1989
0.0
0.0
0.3
1988
0.6
0.0
0.3
0.6
0.6
1 2 3 4 5 6
0.6
Observer length: observed vs predicted
0.0
0.6
0.4
1999
1 2 3 4 5 6
1 2 3 4 5 6
1987
0.6
1982
0.0
0.2 0.4
0.4
1 2 3 4 5 6
0.0 0.2
1996
0.0 0.2
0.4
1 2 3 4 5 6
0.2 0.4
1979
0.0
1976
0.0
0.2 0.4
Trawl length: observed vs predicted
1 2 3 4 5 6
1 2 3 4 5 6
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 15a: Modeled (dashed line) vs. observed (black dots) length class proportion for trawl survey and
summer commercial observer (model 0).
.
82
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.2 0.4
1991
0.0
0.2 0.4
0.4
2008
1 2 3 4 5 6
2010
0.0 0.2
0.4
2006
1 2 3 4 5 6
0.0 0.2
0.4
1 2 3 4 5 6
0.0 0.2
0.0 0.2
2002
1988
0.0
0.2 0.4
0.0
0.2 0.4
1985
1 2 3 4 5 6
1 2 3 4 5 6
2011
1 2 3 4 5 6
1 2 3 4 5 6
0.6
0.6
1 2 3 4 5 6
0.3
1994
0.0
0.3
1992
0.0
0.3
0.0
0.3
1 2 3 4 5 6
1990
1 2 3 4 5 6
1 2 3 4 5 6
0.3
2013
0.0
0.0
0.3
2012
1989
0.0
0.0
0.3
1988
0.6
0.0
0.3
0.6
0.6
1 2 3 4 5 6
0.6
Observer length: observed vs predicted
0.0
0.6
0.4
1999
1 2 3 4 5 6
1 2 3 4 5 6
1987
0.6
1982
0.0
0.2 0.4
0.4
1 2 3 4 5 6
0.0 0.2
1996
0.0 0.2
0.4
1 2 3 4 5 6
0.2 0.4
1979
0.0
1976
0.0
0.2 0.4
Trawl length: observed vs predicted
1 2 3 4 5 6
1 2 3 4 5 6
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 15b: Modeled (dashed line) vs. observed (black dots) length class proportion for trawl survey and
summer commercial observer (model 2.i).
83
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
0.2 0.4
1991
0.0
0.2 0.4
0.4
2008
1 2 3 4 5 6
2010
0.0 0.2
0.4
2006
1 2 3 4 5 6
0.0 0.2
0.4
1 2 3 4 5 6
0.0 0.2
0.0 0.2
2002
1988
0.0
0.2 0.4
0.0
0.2 0.4
1985
1 2 3 4 5 6
1 2 3 4 5 6
2011
1 2 3 4 5 6
1 2 3 4 5 6
0.6
0.6
1 2 3 4 5 6
0.3
1994
0.0
0.3
1992
0.0
0.3
0.0
0.3
1 2 3 4 5 6
1990
1 2 3 4 5 6
1 2 3 4 5 6
0.3
2013
0.0
0.0
0.3
2012
1989
0.0
0.0
0.3
1988
0.6
0.0
0.3
0.6
0.6
1 2 3 4 5 6
0.6
Observer length: observed vs predicted
0.0
0.6
0.4
1999
1 2 3 4 5 6
1 2 3 4 5 6
1987
0.6
1982
0.0
0.2 0.4
0.4
1 2 3 4 5 6
0.0 0.2
1996
0.0 0.2
0.4
1 2 3 4 5 6
0.2 0.4
1979
0.0
1976
0.0
0.2 0.4
Trawl length: observed vs predicted
1 2 3 4 5 6
1 2 3 4 5 6
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 15c: Modeled (dashed line) vs. observed (black dots) length class proportion for trawl survey and
summer commercial observer (model 2.io).
84
Tag recovery data observed vs predicted
1980-92, Recovery after 1 year
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
4
5
6
4
5
6
4
5
6
4
5
6
4
5
6
4
5
6
1980-92, Recovery after 2 years
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
1980-92, Recovery after 3 years
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
1993-2013, Recovery after 1 year
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
1993-2013, Recovery after 2 years
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
1993-2013, Recovery after 3 years
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 16a: Modeled (dashed line) vs. observed (black dots) length class proportion for tag recovery (model
2.i).
85
Tag recovery data observed vs predicted
1980-92, Recovery after 1 year
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
4
5
6
4
5
6
4
5
6
4
5
6
4
5
6
4
5
6
1980-92, Recovery after 2 years
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
1980-92, Recovery after 3 years
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
1993-2013, Recovery after 1 year
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
1993-2013, Recovery after 2 years
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
1993-2013, Recovery after 3 years
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
5
6
0.6
0.0
0.6
Length 5
0.0
0.0
0.0
0.0
1
Length 4
0.6
Length 3
0.6
Length 2
0.6
Length 1
1
2
3
4
5
6
1
2
3
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 16b: Modeled (dashed line) vs. observed (black dots) length class proportion for tag recovery
(model 2.io).
86
2
3
4
5
5
4
3
2
1
1993-2013, Recovery after 1 year
1
1980-92, Recovery after 1 year
1
2
3
4
5
6
1
2
3
4
5
6
2
3
4
5
5
4
3
2
1
1993-2013, Recovery after 2 years
1
1980-92, Recovery after 2 year2
1
2
3
4
5
6
1
2
3
4
5
6
2
3
4
5
5
4
3
2
1
1993-2013, Recovery after 3 years
1
1980-92, Recovery after 3 year
1
2
3
4
5
6
1
2
3
4
5
6
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 17a: Bubble plot of modeled and observed tag recovery length proportion (model 2.i). Black
circle indicates model estimates lower than observed, white circle indicates model estimates
higher than observed. Size of circle indicate degree of deviance (larger circle = larger deviance).
87
2
3
4
5
5
4
3
2
1
1993-2013, Recovery after 1 year
1
1980-92, Recovery after 1 year
1
2
3
4
5
6
1
2
3
4
5
6
2
3
4
5
5
4
3
2
1
1993-2013, Recovery after 2 years
1
1980-92, Recovery after 2 year2
1
2
3
4
5
6
1
2
3
4
5
6
2
3
4
5
5
4
3
2
1
1993-2013, Recovery after 3 years
1
1980-92, Recovery after 3 year
1
2
3
4
5
6
1
2
3
4
5
6
1: 74-83, 2: 84-93, 3: 94-103, 4: 104-113, 5: 114-123, 6: >124
Figure 17b: Bubble plot of modeled and observed tag recovery length proportion (model 2.io). Black
circle indicates model estimates lower than observed, white circle indicates model estimates
higher than observed. Size of circle indicate degree of deviance (larger circle = larger deviance).
88
8000
2000
4000
6000
MMB
10000
12000
14000
Retrospective Analysis
1976
1981
1986
1991
1996
2001
2006
2011
year
Figure 18a: Retrospective analysis (model 0). The bold red line shows retrospective predicted MMB and
each line shows retrospective MMB from prior assessments.
89
8000
4000
6000
MMB
10000
12000
14000
Retrospective Analysis
1976
1981
1986
1991
1996
2001
2006
2011
year
Figure 18b: Retrospective analysis (model 2.i). The bold red line shows retrospective predicted MMB
and each line shows retrospective MMB from prior assessments.
90
8000
4000
6000
MMB
10000
12000
Retrospective Analysis
1976
1981
1986
1991
1996
2001
2006
2011
year
Figure 18c: Retrospective analysis (model 2.io). The bold red line shows retrospective predicted MMB
and each line shows retrospective MMB from prior assessments.
91