Somerton and Munro: Bridle efficiency of a survey trawl for flatfish 
649 
Table 4 
Estimates of bridle efficiency, k b , the standard deviation (SD) of k b by species, and the r 2 for the model fitted without length depen- 
dency. For the two species where k h varies with length, parameters for predicting k b and SD(k b ) as functions of fish length are 
provided. The two functions are k b = a + b exp (cL) and SD(£ fc )= a + bL + cL 2 , where L = fish length in centimeters; and h = the 
average efficiency in the portion of the bridle where herding occurs. 
Parameters of Parameters of 
k b = /'(fish length) SD(£ b ) = /"(fish length) 
Species 
r 2 
h 
K 
SD(£ 6 ) 
a 
b 
c 
a 
b 
c 
Rock sole 
0.91 
0.840 
0.400 
0.056 
Yellowfin sole 
0.77 
0.580 
0.275 
0.057 
Flathead sole 
0.70 
0.510 
0.242 
0.065 
Rex sole 
0.71 
0.502 
0.216 
0.061 
Dover sole 
0.80 
0.636 
0.274 
0.064 
English sole 
0.81 
0.384 
0.165 
0.041 
0.033 
42.667 
-0.221 
0.3338 
-0.0232 
0.00042 
Pacific sanddab 
0.83 
0.161 
0.070 
0.030 
0.046 
36.783 
-0.354 
0.0774 
-0.0059 
0.00012 
Form of the herding model 
The herding model that we propose is essentially 
the same as Dickson’s (1993a) model except that it 
includes an additional parameter (W J needed to cor- 
rect a potential shortcoming of the original. This short- 
coming can be seen in the following example, which for 
simplicity considers a herding experiment with only 
two bridle lengths. Starting with Dickson’s model (sim- 
ilar to Eq. 3 in our study), an estimator for k b can be 
derived from the quotient of the catches obtained with 
long bridles to the catches obtained with short bridles: 
k W n -RW n 
h R(W dl -W n )-(W d2 -W n ) 
where R = N 2 / A^; 
W dv W d2 = the door spreads with the shorter and 
longer bridles; and all other variables 
are the same as those in Equation 3. 
Estimates of k b , based on values of W rfl , W d2 , and 
W n from the Bering sea experiment, increase with 
catch ratio (R) and reach a value of 1.0 when R 
equals the ratio of the door spreads (W d2 /W dl )- This increase 
indicates that the bridles are completely efficient (& 6 =1.0) 
when the proportionate increase in the area subjected to 
herding equals the proportionate increase in catch. If R 
exceeds the ratio of the door spreads, then k b >1.0, which 
is not feasible. In our herding experiments, however, R 
exceeded door spread ratios for all species except English 
sole and Pacific sanddab; therefore, in most cases the unmod- 
ified herding model failed to provide feasible estimates of k b . 
By comparison, estimates of k b from the modified model are 
feasible over the entire observed range of catch ratios. 
In our initial attempts to fit the herding model to experi- 
mental data, we treated W o ^ as an additional parameter to 
be estimated in the fitting process. However, it soon became 
clear that W 0 ^and h are confounded in the model and that 
convergent solutions required an independent estimate 
of W off . We were able to obtain such an estimate and ob- 
serve fish behavior near the bridle by using video methods, 
because in the standard configuration of the 83-112 East- 
ern trawl the bridles are not obscured by mudclouds over 
much of their lengths. However, in perhaps more typical 
cases where the bridles are obscured by the mudclouds, es- 
timation of W a ff with video methods would be problematic. 
A further complication in such cases is that the mudclouds 
themselves might provide a herding stimulus and confuse 
the interpretation of W^, 
