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Fishery Bulletin 1 10(4) 
Figure 7 
Comparison of bootstrap versus derived analytical results for the 
estimators for the Trawl and Acoustic Presence/Absence Survey 
(TAPAS) sampling design, with (A) a proportion of the 80 th percentile 
of the mean volume backscattering (S B ) in a 31-cell window and (B) 
simple random sampling (SRS) and the 2009 NMFS trawl survey 
in the same area. Analytical confidence intervals are approximately 
95% (±2 standard deviation). Bootstrap confidence intervals are 
bias-corrected 95% percentile intervals. 
Max S v (dB) 
Figure 8 
Relationship of maximum mean volume backscattering (S v ) to the 
fourth root of Pacific ocean perch (Sebastes alutus) catch per unit of 
effort (CPUE), from our 2009 acoustic-trawl survey, in an acoustic 
sampling window with a length of 3 trawls (~ 3.0 km). Light gray 
squares indicate background stations, and black diamonds indicate 
patch stations. 
and background areas are estimated. De- 
spite the minimal requirement of classify- 
ing the acoustic data into only 2 catego- 
ries, the results of our study indicate that 
the effectiveness of the TAPAS design re- 
mains dependent upon the strength of the 
relationship between S v and trawl CPUE. 
Patch size and CPUE were only weakly 
correlated, and the variance of the planned 
stations was not as high as expected. Var- 
iogram analysis of ACS data showed that 
the spatial correlation range for trawl 
CPUE may be smaller than the range for 
S v data. Previous variograms estimated 
for the NMFS GOA trawl surveys had in- 
dicated a range of -4.5 km (Hanselman et 
al. 2001), which was also smaller than the 
range of the acoustic backscatter collected 
in our study. The larger range of the S v 
data may indicate that some of the inten- 
sity of S y is a result of ambient variables 
other than POP density. The nugget (un- 
explained variance) of the trawl CPUE is 
large, relative to the total variance for the 
trawl CPUE, an indication that the trawl 
CPUE data likely have more measurement 
error than the acoustic data and that the 
data were sparser. The trawl CPUE var- 
iogram in our study had a larger range 
than did the individual areas analyzed in 
Hanselman et al. (2001). This difference in 
range could have occurred because the ag- 
gregated data in our study had more pairs 
of trawl densities at larger lag distances 
than did the spatially explicit variograms 
with smaller sample sizes in that earlier 
study. 
One source of discrepancy between the 
acoustic and trawl data is that multiple 
species contribute to the acoustic backscat- 
ter. Von Szalay et al. (2007) had success 
relating acoustic backscatter of walleye pol- 
lock with CPUE in the Bering Sea. Howev- 
er, walleye pollock make up the majority of 
the biomass in the Bering Sea; in contrast, 
POP is one of a number of abundant spe- 
cies in the GOA. Krieger et al. (2001) had 
more success relating acoustic backscat- 
ter with rockfishes using a Simrad EK500 
quantitative echosounder. In their study, 
which was conducted in the more rugged 
habitat off Southeast Alaska, the catch was 
primarily rockfishes and contained species 
that were smaller in size than the larger 
rockfish species and walleye pollock that 
made up the non-POP catch in our study. 
Although we restricted our study area to 
depths where POP would be the dominant 
species and, indeed, where POP was the 
largest component of our catch, our origi- 
