282 
Using experiments and expert judgment 
to model catchability of Pacific rockfishes 
in trawl surveys, with application 
to bocaccio ( Sebastes paucispinis ) 
off British Columbia 
Email address for contact author: m.mcallister@fisheries.ubc.ca 
1 Fisheries Centre, Aquatic Ecosystems Research Laboratory (AERL) 
2202 Main Mall 
The University of British Columbia 
Vancouver, British Columbia V6T 1Z4, Canada 
2 Marine Ecosystem and Aquaculture Division 
Science Branch, Fisheries and Oceans Canada 
Pacific Biological Station 
Nanaimo, British Columbia V9T 6N7, Canada 
3 Canadian Groundfish Research and Conservation Society 
1406 Rose Ann Drive 
Nanaimo, British Columbia V9T 4K8, Canada 
Abstract — The time series of abun- 
dance indices for many groundfish 
populations, as determined from trawl 
surveys, are often imprecise and 
short, causing stock assessment esti- 
mates of abundance to be imprecise. 
To improve precision, prior probability 
distributions (priors) have been devel- 
oped for parameters in stock assess- 
ment models by using meta-analysis, 
expert judgment on catchability, and 
empirically based modeling. This arti- 
cle presents a synthetic approach for 
formulating priors for rockfish trawl 
survey catchability ( q gross ). A multi- 
variate prior for q gross for different 
surveys is formulated by using 1) a 
correction factor for bias in estimating 
fish density between trawlable and 
untrawlable areas, 2) expert judgment 
on trawl net catchability, 3) observa- 
tions from trawl survey experiments, 
and 4) data on the fraction of popu- 
lation biomass in each of the areas 
surveyed. The method is illustrated by 
using bocaccio ( Sebastes paucipinis) 
in British Columbia. Results indicate 
that expert judgment can be updated 
markedly by observing the catch-rate 
ratio from different trawl gears in 
the same areas. The marginal priors 
for q aross are consistent with empiri- 
cal estimates obtained by fitting a 
stock assessment model to the survey 
data under a noninformative prior for 
q cross- Despite high prior uncertainty 
(prior coefficients of variation >0.8) 
and high prior correlation between 
q gross’ the prior for q gross still enhances 
the precision of key stock assessment 
quantities. 
Manuscript submitted 8 May 2009. 
Manuscript accepted 5 April 2010. 
Fish. Bull. 108:282-304(2010). 
The views and opinions expressed 
or implied in this article are those of the 
author (or authors) and do not necessarily 
reflect the position of the National 
Marine Fisheries Service, NOAA. 
Murdoch K. McAllister (contact author ) 1 
Richard D. Stanley 2 
Paul Starr 3 
Rockfishes (Sebastes spp.) are a group 
of groundfish species on the west coast 
of North America, many of which are 
commonly exploited; over 25 stocks are 
assessed and individually managed in 
the United States and Canada (DFO, 
2008; NPFMC, 2008; PFMC, 2008). 
Stock assessment models for rock- 
fish are typically fitted to a variety 
of data, such as estimates of popula- 
tion biomass determined from survey 
trawl-swept areas. These swept-area 
biomass estimates are usually treated 
as relative indices of abundance 
because of the unknown relationship 
between the availability of the target 
population to the survey net. Factors 
affecting this relationship include the 
proportion of fish present within the 
path of the net that on average enter 
the net, the proportion of the popula- 
tion that is potentially available to be 
captured by the survey gear and the 
relative density of rockfish in traw- 
lable and untrawlable areas. Treated 
as a relative abundance index, a 
single scalar parameter is typically 
estimated, called “bulk catchability” 
or “q gross’ scale the model-predicted 
population biomass to the swept-area 
biomass values (Millar and Methot, 
2002). Owing to the trawl survey data 
being available for only a portion of 
the history of a stock’s exploitation 
and because of moderate to large 
amounts of variation in interannual 
error, stock assessment estimates of 
q gross are often imprecise and may not 
provide reliable estimates of popu- 
lation biomass (Millar and Methot, 
2002 ). 
In order to reduce the large uncer- 
tainty common to estimates of q gross 
and population abundance for rock- 
fishes and many other assessed fish- 
es, stock assessment scientists have 
quantified Bayesian prior probabil- 
ity density functions (pdfs) for q gross - 
Among these quantifications, there 
have been efforts to quantify expert 
judgment (e.g., Punt et al., 1993; 
McAllister and Ianelli, 1997; Boyer et 
ah, 2001) on factors affecting survey 
catchability. Others have performed 
hierarchical analyses of stock assess- 
ments for different rockfish species to 
quantify the mean and variance in 
q g ross across different populations for 
surveys, using the same gear (Millar 
and Methot, 2002). Although these 
