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Fishery Bulletin 106(3) 
and seafloor slopes were known (Rooper and Zimmer- 
mann, 2007). 
Assumption 1: scale of measurements 
Although as a group the 166 EMs ranged between zero 
and one (Legendre et al., 2002), this was tested for each 
of the 166 EMs; and EMs fully extending across this 
range would indicate that the data had been standard- 
ized for proper PCA (Manly, 1994; Legendre and Legen- 
dre, 1998). PCA was also conducted (S-Plus, vers. 6.1, 
Insightful Corp., Seattle, WA) independently to ensure 
that the QTC PCA results could be reproduced. 
Assumption two: first echo 
Although it is widely reported or implied in the lit- 
erature that QTC IMPACT software analyzes only the 
first echo, that conclusion is not strictly correct. QTC 
IMPACT analyzes the first 251 sound samples beneath 
the bottom pick, and it is up to the user to ensure that 
this is a meaningful window. The relationship between 
the 251 samples and the analysis depth range is directly 
related to half of the sample interval preset in the 
echosounder; 
Analysis depth range (m) = Sample interval (s/sample) 
x (0.5) x (1500 m/s) x 251 samples, 
where 1500 m/s = the approximate speed of sound 
through seawater. 
This relationship was tested to determine how well 
the 251 sample size corresponded with the first echo 
in the NMFS 2003 FV Gladiator data sets and with 
the external data sets collected by other agencies from 
other vessels. 
Results 
Gain settings 
Determining the proper gain setting for the NMFS 2003 
FV Gladiator data sets was a time-intensive process 
because a wide range of gains needed to be applied and 
weak or bad data had not yet been identified. We deter- 
mined that a gain setting of -18 dB would be appropriate 
for shallow sites (25-100 m, 68 sites, 97,119 pings) and 
a gain setting of -17 dB would be appropriate for deep 
trawl sites (100-200 m, 19 sites, 25,110 pings). Several 
additional sites with too many weak pings (>50%), an 
indication of bad data, were identified and eliminated 
from processing at this stage. Although changing the 
gain setting within QTC IMPACT by 0.5 dB was equiva- 
lent to changing the gain setting by 1.0 dB in Echo- 
View®, use of the gain adjustment within QTC IMPACT 
was far more convenient for adjusting the echo signal 
strength to be within the required 96-dB range, and for 
identifying bad data. 
Bottom picks 
In the NMFS 2003 FV Gladiator data sets, there were 
72,296 shallow (25-100 m) pings with bottom picks 
including 3961 that were clipped, and there were 18,021 
deep (100-200 m) pings with bottom picks including 
1106 of those that were clipped. Thus there was a greater 
than 70% success rate in bottom picking and approxi- 
mately 6% clipping among both data sets, indicating that 
the gain settings were appropriate. Each bottom pick 
was inspected and found to occur anywhere between the 
base and the tip of the peak — in the general region of 
the seafloor location. Thus QTC IMPACT software did 
an excellent job of bottom picking in the NMFS 2003 FV 
Gladiator shallow and deep data sets. 
Generating echogram measurements 
The NMFS 2003 FV Gladiator shallow data set yielded 
14,432 stacks (of five pings) and the deep data set 
yielded 3598 stacks (of five pings); odd lots of fewer 
than five pings were not included in stacks, and there- 
fore the total number of stacks was slightly less than 
one fifth of the total number of pings with bottom picks. 
Padding was required at all shallow sites for all of 
the stacks, and padding was required at 16 of 19 deep 
sites on a total of 3112 stacks. A reference depth of 50 
m was used for the shallow sites and 150 m was used 
for the deep sites. The EMs for the shallow sites were 
combined into a single data set for PCA and A-means 
clustering. The process was repeated for the EMs from 
the deep sites. 
Optimum substrate classification 
The A'-means clustering of the first three PCs indicated 
that a solution of any specific number of acoustically 
derived substrate classes would not explain much more 
of the variance than other solutions. Therefore the data 
processing was repeated several times to check for errors 
that may have influenced the results. The main focus 
was on gaining a better understanding of the numbers 
that were being created and processed with PCA and 
A-means clustering, and on exploring factors that may 
have affected the EMs. 
Examination of the data 
Examinations of the spreadsheets of EMs from the 
NMFS 2003 FV Gladiator shallow and deep data sets, 
and the four externally collected data sets, showed the 
same groups as those revealed by the examination of the 
stack of the single pings repeated five times; EMs 1-23, 
EMs 24-39, EMs 40-70, EMs 71-101, and EMs 102-166. 
Across all data sets, the EMs in the first (EMs 1-23) 
and fifth (EMs 102-166) groups were, in general, highly 
correlated with their neighbors (e.g., EM 22 versus 23, 
Fig. 1). In the second group of EMs (EMs 24-39), EM 
31 was the sum of EM 32 through EM 39, each of which 
were fractions of 256 (e.g., 1/256, 2/256). Among the 31 
