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Fishery Bulletin 108(3) 
Approach to acquiring information from trawl experts 
Our approach relies on a large number of experts being 
interviewed to seek their judgments on the credibil- 
ity of hypothesized values for factors affecting trawl- 
net catchability ( q net ). A sufficiently large number of 
experts is required to characterize the range of dif- 
ferences in opinion among experts (e.g., Martin et ah, 
2005; Uusitalo et al., 2005). This can be achieved by 
continuing to sample until the distribution of inputs 
stabilizes, e.g., the means and standard deviations in 
inputs change by less than 10% for each new expert 
interviewed. In the interviews each trawl captain was 
asked to specify the most likely, minimum plausible, 
and maximum plausible average values for a set of 
key factors conjectured to determine q net and these 
values were then used to formulate a triangular dis- 
tribution for each factor for each survey net specific to 
each captain. The component factors of q net formulated 
below represent “average” effects. Thus the minimum 
and maximum input values for each key factor do not 
reflect a predicted response for one case (i.e., from the 
population of all tows), but the minimum and maximum 
values for the average value across all tows combined. 
The pdfs formulated thus represent density functions 
of the mean value for a given factor, not the population 
of values from all conceivable tows. 
The probabilistic modeling approach that was applied 
to synthesize the captains’ inputs was similar to that 
taken by Uusitalo et al. (2005) and Martin et al. (2005) 
to formulate priors based on interviews with several 
different experts. For each net type, the resulting q net 
was modeled as a mixture of the distributions result- 
ing from the specifications from each of the interviewed 
captains. 
Answers to our questions allowed us to simplify the 
process of catching a bocaccio to six steps based on four 
questions: 
Step 1 Resolve the relative distribution in the water 
column (a x ). Question 1) What is your best estimate (and 
minimum and maximum) of the percentage of target 
species that would be near-bottom (within 3-4 m) as the 
vessel passed overhead ? 
Rockfish, particularly bocaccio, are presumed to oc- 
cupy the water column from surface to bottom, but their 
density increases with depth. The factor, a v for the 
relative distribution of the target species in the water 
column (zone A, Fig. 3) defines the proportion of fish 
below headrope height, as the vessel passes over the 
fish. For this step, three assumptions are made: 
1 fish below the headrope, as the vessel passes over 
them, continue to stay below the height of the head- 
rope until they arrive at the mouth of the net; 
2 fish outside the doors (horizontally), continue to stay 
outside the doors; and 
3 a T is the same for all nets (this is reasonable because 
most of the nets have headline heights of around 3 m 
and only the U.S. triennial net is higher). 
Step 2 Resolve the proportion of off-bottom target 
species that “dive” into the “kill zone” (i.e., the area 
immediately in front of the opening of the trawl net), 
(i.e., zone E, Fig. 3) (a 2 ). Question 2) What percentage 
of those fish initially off-bottom would dive into the kill 
zone? 
The factor a 2 is the proportion of fish in zone B that 
would dive into the kill zone from those initially above 
the head rope of a given type of net (zone B, Fig. 3). For 
factor a 2 , the following assumptions are made: 
1 all fish below the headrope, stay below the headrope 
until at the mouth of the net; 
2 fish dive in response to vessel noise and warps; 
and 
3 dive rate is equal for all net -warp-vessel combinations. 
Step 3 Resolve the proportion of fish which lie in the 
“dead” zone, i.e., the zone between the doors but external 
to the trawl warps. 
The answers to questions 1 and 2 provided the per- 
centage of fish that were initially in the path of the 
trawl doors that would lie in the capture zone as the 
doors approached (between the doors and below the 
headrope) (zones C-D, Fig. 3). The disposition of the 
fish horizontally would then be partially determined by 
whether they lay directly in the path of the net between 
or outside the wingtips but still within the door path. 
Fish in zone C were assumed to stay there as the net 
approached (zone E). Fish in zone D would have to be 
herded inwards to area C by the sweeps and bridles 
(Fig. 3). 
Discussions with some captains indicated that for 
fish that lie within 6 m of doors inside the door path 
there is zero catchability. As the trawl warps approach 
the doors near the bottom, they spread out towards the 
doors, possibly scaring near-bottom fish out of the kill 
zone. Therefore, as the doors approach the fish, the fish 
are assumed to be distributed across the path of the 
doors in one of three sectors, in proportion to the linear 
dimensions of that sector (Fig. 3), namely: 
1 in the path of the net (i.e., between wingtips, zone C, 
Fig. 3, Tables 3 and 4); 
2 in the path of the sweep and bridles but more than 
6 m (for survey nets used for bocaccio) inside of the 
door path (herding zone, Dl, Fig. 3B) (factor a 31n )\ 
and 
3 in the path of sweep and bridles but within 6 m of the 
doors (dead zone, i.e., horizontal area in which all fish 
are expected to escape capture) (D2, Fig. 3B). 
Step 4 Resolve arithmetic correction for the relative 
proportions of fish remaining in front of the net (between 
wingtips) or in front of sweeps and bridles (inside of the 
dead zone). 
After allowing fish in the dead zone to escape, we 
estimated the proportions of remaining fish that ei- 
ther lie in front of the net (zone C, Fig. 3) (factor a 4 „) 
or the “herdable” section of the sweeps and bridles 
