Ralston et a!.: A meta-analytic approach to quantifying scientific uncertainty in stock assessments 
227 
Table 2 
Summary of stock-specific analyses of variation for estimates of terminal stock size from assessments of groundfish and coastal 
pelagic species. CV=coefficient of variation. 
Stock 
group 
Common name 
Scientific name 
No. of 
stock 
assessments 
Squared 
deviations 
(n) 
Log-scale 
standard 
deviation 
Statistical 
uncertainty 
CV 
Rockfish 
bocaccio 
Sebastes paucispinis 
5 
61 
0.367 
15% 
canary rockfish 
Sebastes pinniger 
8 
85 
0.375 
15% 
chilipepper 
Sebastes goodei 
2 
22 
0.354 
14% 
darkblotched rockfish 
Sebastes crameri 
3 
45 
0.103 
13% 
Pacific ocean perch 
Sebastes alutus 
3 
20 
0.352 
15% 
widow rockfish 
Sebastes entomelas 
5 
61 
0.241 
31% 
yelloweye rockfish 
Sebastes ruberrimus 
4 
58 
0.492 
14% 
yellowtail rockfish 
Sebastes flavidus 
6 
66 
0.269 
24% 
shortspine thornyhead 
Sebastolobus alascanus 
3 
39 
0.923 
9% 
Roundfish 
cabezon 
Scorpaenichthys marmoratus 3 
46 
0.154 
21% 
lingcod 
Ophiodon elongatus 
4 
56 
0.263 
10% 
Pacific whiting 
Merluccius productus 
15 
151 
0.286 
28% 
sablefish 
Anoplopoma fimbria 
7 
82 
0.340 
10% 
Flatfish 
Dover sole 
Microstomus pacificus 
3 
41 
0.360 
9% 
petrale sole 
Eopsetta jordani 
3 
41 
0.227 
15% 
Coastal pelagic 
Pacific mackerel 
Scomber japonicus 
4 
66 
0.415 
25% 
Pacific sardine 
Sardinops sagax 
3 
51 
0.206 
41% 
Table 3 
Comparison of different methods of pooling stock-spe- 
cific variance estimates. Method 1 weights each spe- 
cies equally, whereas method 2 weights each data point 
equally. In the table, a is the standard deviation of log- 
scale anomalies from the mean. 
Group 
Number 
of stocks 
a 
Method 1 
Method 2 
rockfish 
9 
0.442 
0.418 
roundfish 
4 
0.269 
0.281 
flatfish 
2 
0.301 
0.299 
coastal pelagic 
2 
0.328 
0.339 
All stocks 
17 
0.337 
0.358 
the lognormal distribution (1.00) is indicative of the 
best risk-neutral point estimate of catch ( = OFL), 91% 
of that amount would be associated with a 0.40 prob- 
ability of exceeding the true OFL. 
Other approaches and future work 
The approach outlined in this study is a pragmatic 
way to address the legislative requirement to calculate 
ABCs from OFLs, accounting for scientific uncertainty. 
Although the approach has been adopted and imple- 
mented as an ABC control rule for decision-making 
at the PFMC, 5 quantification of scientific uncertainty 
> 
a 
C 
CD 
E 
c n 
c n 
CD 
c n 
c n 
03 
C 
'sz 
I 
0.50 - 
0.40 - 
0.30 - 
0.20 - 
0.10 - 
shortspine 
thornyhead 
o 
o.oo -I 1 1 1 1 1 1 i 
0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 
Among-assessment CV 
Figure 4 
Relationship between the coefficients of variation (CV) 
calculated from biomass variation over multiple full 
stock assessments (x axis) and the CV based on the 
measurement error of the most recent analysis ( y axis). 
5 PFMC and NMFS. 2010. Proposed harvest specifications 
and management measures for the 2011-2012 Pacific Coast 
groundfish fishery and Amendment 16-5 to the Pacific Coast 
Groundfish Fishery Management Plan to update existing 
rebuilding plans and adopt a rebuilding plan for petrale sole: 
Draft environmental impact statement including Regulatory 
Impact Review and Initial Regulatory Flexibility Analy- 
sis. Pacific Fishery Management Council, Portland, OR 
(submitted to NOAA Fisheries Service), June 2010. 
