298 
Fishery Bulletin 106(3) 
Initial 
sums 
Secondary Tertiary Final 
sums sums sum 
70 + 69 = 68 
67 + 66 = 65 
68 + 65 = 64 
63 + 62 = 61 
60 + 59 = 58 
61 + 58 = 57 
64 + 57 = 56 
55 + 54 = 53 
52 + 51 =50 
53 + 50 = 49 
48 + 47 = 46 
45 + 44 = 43 
46 + 43 = 42 
49 + 42 = 41 
56 + 41 =40= 1.000000 
Figure 2 
Schematic diagram depicting a sequence (from left to right) of 15 sums 
from 16 original unitless echogram measurements — a sequence of sums 
that leads to a final sum of one. The left column shows how 16 original 
echogram measurements are summed into eight new echogram mea- 
surements. The next column shows how these eight sums are summed 
into four new echogram measurements. The third column shows how 
these four sums are summed into two new echogram measurements. 
The fourth column shows how these two sums are summed to produce 
a final echogram measurement of one. 
seven EMs had variance inflation factors >10 (a gen- 
eral threshold indicating high correlations but not full 
collinearity with the remaining variables; Neter et al., 
1990), leaving only three to six relatively independent 
EMs in each data set. 
Correlation of echogram measurements with depth 
There was a significant relationship between depth and 
some EMs in all data sets (Fig. 3). This relationship 
translated into significant relationships (LOESS curve 
fits) between PCI and PC2 versus depth for all six data 
sets (F-tests, P<0.001), indicating that depth has a direct 
influence on the QTC substrate classification. 
Angle of incidence 
At the Aleutian Islands groundtruth site (FV Gladiator 
in 2005; Rooper and Zimmermann, 2007), there were 
significant linear correlations (P<0.05) between slope 
and EMs for the most common substrate classes of sand- 
boulder (n = 368 video observations), sand-sand (rc = 351), 
and bedrock-boulder (n=259), even when the analyses 
were restricted to low (<5°) slopes (von Szalay, 1998; 
von Szalay and McConnaughey, 2002). The influence 
of slope resulted in EMs that were equivalent among 
different substrates and different slopes. For example, 
EM 1 on a substrate of bedrock-boulder at 1° slope was 
equivalent to EM 1 on sand-sand substrate at 4.1° slope, 
and equivalent to EM 1 on sand-boulder substrate at 4.9° 
slope (Fig. 4), illustrating how easily substrates can be 
misclassified at low slopes. 
Assumption one: scale of measurements 
The S-Plus version of PCA, conducted after eliminat- 
ing invariant EMs (16, 31, and 40), confirmed that the 
QTC IMPACT method of PCA does not use any addi- 
tional data ranging or standardization. PCA performed 
in S-Plus with standardization (subtraction of mean, 
