644 
Fishery Bulletin 99(4) 
Table 1 
Trawl configuration parameters for each herding experiment. Included are the bridle and tail chain lengths that were used, the 
number of sampling blocks occupied, and the means and standard deviations (in parentheses) of the wing spread, door spread, and 
bridle angle. Also included are the mean values for the bridle off-bottom path width ( W o ^). WA = Washington State. 
Experiment 
Bridle 
length 
(m) 
Tailchain 
length 
(m) 
Number 
of 
blocks 
Wing 
spread 
(m) 
(W n ) 
Door 
spread 
(m) 
(W d ) 
Bridle 
angle 
(deg) 
(a) 
Bridle off-bottom 
path width 
(m) 
Woff) 
Bering Sea 
27.3 
13.9 
15 
18.0(0.6) 
44.6(2.1) 
18.9(1.2) 
23.3 
54.6 
13.9 
15 
17.3 (0.6) 
58.7(2.9) 
17.6 (1.0) 
21.8 
81.6 
13.9 
15 
17.1 (0.5) 
71.6(3.7) 
16.6(1.0) 
20.5 
West Coast (WA) 
27.3 
8.0 
19 
17.7 (0.3) 
41.9(0.7) 
20.0 (0.5) 
24.1 
54.6 
8.0 
19 
17.1 (0.6) 
57.5 (1.5) 
18.8(0.7) 
23.1 
81.6 
8.0 
19 
16.8 (0.3) 
70.0 (1.5) 
17.3(0.5) 
21.3 
ber 1995 aboard the RV Alaska off the coast of Washington 
State using the 83-112 Eastern trawl equipped with stan- 
dard 55-m bridles. The experiment consisted of recording 
views of the lower bridle with a silicon-intensified target 
(SIT) video camera while the trawl was in operation. The 
camera was mounted in a positively buoyant case attached 
to the upper bridle with a 1-m tether line and aligned so 
that the lower bridle directly below the attachment point 
could be viewed. The tether was positioned at 5-m inter- 
vals between 23 m and 43 m behind the doors. One 15-min 
tow at each of the five bridle positions was taken at both 
depths of 20 m and 35 m. 
The video tapes were subsequently analyzed to deter- 
mine the degree of bottom contact at each bridle position. 
This was done by viewing each tow at ten randomly chosen 
10-sec sampling intervals. Bottom contact was recognized 
by the presence of sediment that is mixed into the water at 
the point of contact. Because the bottom is irregular, when 
the bridle has weak contact, just the tops of the irregulari- 
ties are touched, whereas when the bridle has strong con- 
tact, the entire bottom in the field of view is touched. The 
average percentage of the bridle in the field of view that 
was in contact with the bottom was scored according to the 
following four-level scale: 1) no contact, 2) <25% contact, 3) 
>25% and <75% contact, 4) >75% contact. The degree of bot- 
tom contact at each bridle position and depth was then es- 
timated as the mean of the ten evaluations. 
The length of the bridle not in contact with the bottom 
(L o ff, Fig. 1) was defined as the distance between the at- 
tachment of the tailchain to the door and the point along 
the bridle where bottom contact was 50%. To estimate L of - f> 
a logistic function was fitted to the bottom-contact and bri- 
dle-position data with generalized linear modeling (Ven- 
ables and Ripley, 1994), then the fitted logistic equation 
was evaluated at a bottom contact score of 3.0 (i.e. bottom 
contact >25% and <75%). Variance of L o ^ was estimated 
with bootstrapping (Efron and Tibshirani, 1993), where 
the bootstrap samples were obtained by randomly choos- 
ing, with replacement, from the haul mean scores at each 
bridle position. 
In subsequent analysis, L off was treated as a constant 
for all three bridle lengths and for both vessels. However 
the variable actually used in the herding model, W off , was 
calculated as L 0 ^ multiplied by the sine of the bridle an- 
gle (Fig. 1) and therefore varied slightly between bridle 
lengths and experiments because the bridle angle varied. 
In addition to the camera placements for measuring 
we also made placements at bridle positions both clos- 
er to the doors to examine for any evidence of herding in 
the area where the lower bridles were not in contact with 
the bottom and closer to the wing tips to determine if bot- 
tom contact was maintained continuously near the junc- 
tion of the bridle and wing. 
Fitting the model to the herding data 
The herding model (Eq. 4) was modified in several ways to 
clarify the way it was fitted to the experimental data and 
to better define its underlying statistical structure. First, 
because of the block design of the experiment, fish density 
< D ) was considered to be a constant within each block but 
to vary between blocks. Furthermore, net efficiency (kj 
was also considered to be a constant for all tows within 
a block because depth and other bottom conditions are 
nearly constant but vary between blocks. Because D and 
k n are both block-specific constants and are confounded 
in the model, they were combined into a new constant 
k. Second, herding can vary with fish length (Engas and 
Godp, 1989a; Dickson, 1993b), therefore Equation 4 was 
modified to allow length dependency. The modified equa- 
tion is 
N ljk = k l [LW n \. +k t h k [L(.W d -W n -W^)].. +£ (5) 
where the subscript i = block number; 
j = bridle length within a block; 
k - fish length class and 
e = ~ MO, <r). 
