204 
Fishery Bulletin 109(2) 
Table 4 
Performance and convergences of assessment models. Percentages of runs finished indicate that the assessment models finished 
stock synthesis (SS3) runs but maximum gradient component (MGC) statistics did not satisfy convergence criteria. Percent- 
ages of MGC satisfied indicate that the assessment models finished SS3 runs and MGC statistics satisfied convergence criteria 
(MGC<0.05). 
Run no. No. of simulations 
% of runs finished 
% MGC satisfied 
No. of parameters 
1 
3000 
100.0 
100.0 
82 
2 
500 
100.0 
100.0 
82 
3 
500 
86.2 
81.3 
86 
4 
500 
78.6 
48.2 
86 
5 
500 
83.3 
81.0 
86 
6 
500 
70.2 
53.0 
86 
7 
500 
100.0 
100.0 
82 
8 
500 
100.0 
100.0 
82 
9 
500 
100.0 
100.0 
82 
10 
500 
100.0 
100.0 
82 
11 
500 
84.5 
80.1 
86 
12 
500 
77.4 
45.7 
86 
13 
500 
100.0 
100.0 
83 
14 
500 
100.0 
100.0 
86 
15 
500 
83.8 
79.5 
87 
16 
500 
75.1 
48.4 
90 
200 
>, 160 
£ 120 
I 80 
£ 40 
0 
Percentage of difference: virgin spawning output 
200 
>, 160 
£ 120 
| 80 
£ 40 
0 
Percentage of difference: depletion 
Figure 4 
Frequency plots of estimated differences of virgin spawning outputs (B 0 ) 
and depletions between simulation and stock synthesis (SS3) assessment 
models from run 1. The differences are percentages of differences between 
simulation and assessment divided by true simulation values. Values equaled 
to zero indicate no differences between simulation and assessment models. 
population trajectories were very dif- 
ferent between the simulation and 
assessment models for run 2 (top right 
panel, Fig. 6), and stock recruitment 
parameters ( B 0 h) were poorly esti- 
mated, with B () being lower and h being 
higher in the assessment models than 
those in the simulation models. The 
estimated catchability coefficients in 
the assessment models were higher 
than those in the simulation models. 
Estimated catchability coefficients for 
juvenile fish (q 2 ) were especially high 
(>3.6 versus the correct value of 1.0) 
for run 2. This result occurred also 
for all other scenarios in which juve- 
nile natural mortalities were misspeci- 
fied in assessment models (Table 3). 
However, estimated selectivity func- 
tions matched fairly well between the 
simulation and estimation models (top 
row, Fig. 7). Performance of the stock 
assessment models in this setting was 
very good; 100% of the runs finished 
successfully and MGC values were sat- 
isfied (Table 4). 
Similar results were obtained if se- 
lectivity functions were double normal 
and were correctly specified in the 
