293 
Abstract — Defining types of seafloor 
substrate and relating them to the 
distribution of fish and invertebrates 
is an important but difficult goal. An 
examination of the processing steps 
of a commercial acoustics analyzing 
software program, as well as the data 
values produced by the proprietary 
first echo measurements, revealed 
potential benefits and drawbacks 
for distinguishing acoustically dis- 
tinct seafloor substrates. The positive 
aspects were convenient processing 
steps such as gain adjustment, accu- 
rate bottom picking, ease of bad data 
exclusion, and the ability to average 
across successive pings in order to 
increase the signal-to-noise ratio. A 
noteworthy drawback with the pro- 
cessing was the potential for acciden- 
tal inclusion of a second echo as if it 
were part of the first echo. Detailed 
examination of the echogram mea- 
surements quantified the amount 
of collinearity, revealed the lack of 
standardization (subtraction of mean, 
division by standard deviation) before 
principal components analysis (PCA), 
and showed correlations of individual 
echogram measurements with depth 
and seafloor slope. Despite the facil- 
ity of the software, these previously 
unknown processing pitfalls and echo- 
gram measurement characteristics 
may have created data artifacts that 
generated user-derived substrate clas- 
sifications, rather than actual sea- 
floor substrate types. 
Manuscript submitted 4 February 2008. 
Manuscript accepted 28 March 2008. 
Fish. Bull. 106:293-304 2008). 
The views and opinions expressed or 
implied in this article are those of the 
author and do not necessarily reflect 
the position of the National Marine 
Fisheries Service, NOAA. 
Comparison of echogram measurements 
against data expectations and assumptions 
for distinguishing seafloor substrates 
Mark Zimmermann (contact author) 
Christopher N. Rooper 
Email address for M Zimmermann: Mark.Zimmermann@noaa.gov 
National Marine Fisheries Service 
Alaska Fisheries Science Center 
7600 Sand Point Way NE, Bldg. 4 
Seattle, Washington 981 15-6349 
Marine natural resource managers 
must define essential fish habitat 
(EFH) for federally managed, com- 
mercially exploited species (Federal 
Register, 2002) but the best method 
for fulfilling this mandate across the 
vast area and significant depths of 
the U.S. Exclusive Economic Zone 
remains unknown. A successful acous- 
tic method for determining EFH would 
be of great benefit, because single- 
beam seafloor echosounder reflections 
are collected simultaneously with fish 
density estimates during National 
Marine Fisheries Service (NMFS) 
stock assessment bottom trawl sur- 
veys in the Gulf of Alaska (~800 sta- 
tions among 320,000 km 2 , <1000 m 
depth) and the Aleutian Islands (-400 
stations among 67,000 km 2 , <500 m 
depth). Therefore we conducted an 
acoustic analysis on data from a small 
portion from one survey in order to 
determine if there was a direct cor- 
relation between substrate classes or 
echogram measurements with species 
abundance. 
We tested a widely used, propri- 
etary software package (vers. 3.30, 
QTC IMPACT™), developed by the 
Quester Tangent Corporation (QTC, 
Sidney, British Columbia, Canada), 
to resolve the echosounder reflec- 
tions into substrate types for com- 
parison with the survey trawl catch 
data to determine whether there was 
a correlation or relationship between 
seafloor substrate classes and fish- 
density. This software produces 166 
proprietary unitless echogram mea- 
surements (EMs) on the first seafloor 
echo for an internal principal compo- 
nents analysis (PCA), and then uses 
the first three principal components 
(PCs), generally accounting for more 
than 95% of the covariance (Ellingsen 
et al., 2002; Legendre et al., 2002) in 
A-means clustering, for dividing the 
first seafloor echoes into acoustically 
distinct substrate types. 
Our initial efforts with Tf-means 
clustering indicated that a solution 
of any particular number of classes 
was not much better than other solu- 
tions (e.g., four versus five substrate 
classes), and therefore the 166 EMs 
were analyzed to determine if they 
could be used in another analysis for 
resolving substrate types. Although 
the general manner in which the 166 
EMs, or the data, are acquired, pro- 
cessed, and divided into substrate 
classes by QTC software has been 
well reported in the literature, many 
specific details are lacking and it was 
therefore not clear what these 166 
EMs represent. 
To investigate an acoustic method 
for determining EFH we described 
the specific details of the processing 
method that QTC software follows, 
focusing on potential pitfalls and ad- 
vantages for the user. We report on 
new findings based on some simple 
data explorations on the 166 EMs 
from echosounder data collected dur- 
ing a 2003 NMFS research cruise; 
and our findings are corroborated 
with four data sets collected indepen- 
dently from other agencies on other 
ships. In this analysis we checked 
the assumption that these 166 EMs 
have the same scale or range as that 
normally used in PCA, and the as- 
