Zimmermann and Rooper: Comparison of echogram measurements for distinguishing seafloor substrates 
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cally increased to -96 dB. Another convenience of the 
QTC software was that abnormally weak echoes could 
be eliminated by specifying a minimal signal strength, 
and this was set to be equal to 25% of the maximum 
permissible amount (0 dB). 
Bottom picks 
After importing the recorded echoes into the software at 
an appropriate gain setting, another method for further 
improving the signal-to-noise ratio would be to assemble 
a stack of successive echoes, presumably from the same 
substrate, and average the echo stack into a single echo 
(Pace and Ceen, 1982). For QTC IMPACT, a minimum 
stack size of five pings was recommended, which corre- 
sponded to 2.5 seconds or 3.85 m traveled at 1.54 m/s, 
for a theoretical yield of 288 stacks per trawl path. The 
strong, positive benefits of stacking were dependent on 
correctly aligning events with the successive echoes, and 
therefore on the software’s interpretation of the seafloor 
inflection point. Although this data check is not men- 
tioned in the literature, it is a critical part of the process, 
because all measurements start at the seafloor inflection 
point. We examined every bottom pick for appropriate 
placement, as recommended by QTC guidelines. This 
process determined that the bottom pick was not inter- 
polated between sample intervals, and that the natural 
variability of the depth among a group of pings would 
be the distance sound travels during half the sampling 
interval (0.768 m). 
Generating echogram measurements 
Once the bottom pick had been located, an automatic 
determination of the length or extent of any seafloor 
echo was difficult because rough, steep, soft, and deep 
areas have longer reflections than smooth, flat, hard, 
and shallow areas. The QTC IMPACT software uses 256 
sound samples of vertical time intervals, or recorded 
sound intensity within a ping, surrounding the bottom 
pick. Starting at the bottom pick, five samples (repre- 
senting the water column) were taken above the seafloor 
inflection point and 251 samples were taken below the 
start of the first seafloor reflection (representing the 
seafloor). If the echograms contained fewer than 251 
time intervals below the start of the first seafloor reflec- 
tion, the last sample was repeated (padded) as many 
times as needed until the 251 sample requirement was 
fulfilled. The QTC software then generated 166 EMs 
for each stack with reference to a specific depth such 
that depth-related changes in signal protraction were 
corrected. 
Optimum substrate classification 
Organizing the echogram measurements along a contin- 
uum of measurements or grouping them into a number 
of acoustically distinct substrate classes is the final 
step in the process. Ideally this step would identify sub- 
strate qualities of importance to EFH species, such that 
researchers could infer essential fish habitat from sub- 
strate types and use this information for better resource 
management. The QTC method first uses continua by 
performing PCA on the 166 EMs and retaining the first 
three PCs for plotting the location of each stack in three- 
dimensional space. Then it is up to the user to determine 
the optimum number of substrate classes on the basis of 
the A-means clustering of the first three PCs. 
Examination of the data 
Because the algorithms for producing the 166 EMs are 
proprietary, the data values produced by the 166 EMs 
were exported and viewed in a text editor, which showed 
that the data values for each stack were displayed as 
seven decimal-place numbers in four columns, under- 
neath a stack header. In order to resolve the possible 
complications of having a single set of 166 EMs for five 
different stacked pings, a single ping was exported from 
EchoView® and imported into QTC IMPACT five times, 
to create one stack of identical pings. The four columns 
of 166 EMs were reformatted into a single column in a 
spreadsheet and an examination of the data revealed 
that the EMs from this single, repeated ping were occur- 
ring in five groups (von Szalay, 1998). 
Variability and covariance of echogram measurements 
Simple data checks, such as checks of averages, vari- 
ances, minima, and maxima, enabled us to describe 
each data set and determine the range or scale of each 
EM. The variance between EMs, or the covariance, was 
derived to determine the amount of collinearity among 
the EMs. 
Correlation of echogram measurements with depth 
The correlation between each EM versus depth was 
determined from each of the data sets. This simple 
analysis, which could provide some useful diagnostics, 
has not been reported in any of the literature. 
Angle of incidence 
The angle of echosounder seafloor reflections has a 
potentially confounding influence on any depth-cor- 
relation analysis, because the rate of change of depth 
and slope vary together. In general, QTC and similar 
products should be used to analyze normal (90°) incident 
reflections (see Pace and Ceen, 1982; Orlowski, 1984), 
and it is expected that severe departures from normality 
would cause analytical failures. The influence of non- 
normal (<90°) reflections could not be formally exam- 
ined in our study because of a lack of knowledge about 
cross-track slope, vessel pitch and roll, and interactions 
between seafloor angle and vessel angle. However, more 
single-beam data were analyzed from the FV Gladiator 
in 2005 at small study sites in the Aleutian Islands 
that had been groundtruthed with video and multibeam 
sonar equipment in 2004, such that the substrate types 
