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Fishery Bulletin 111(4) 
Table 3 
Summary of significant comparisons from post hoc permutational analysis of variance (PERMANOVA) of fork lengths for 
bottomfish restricted fishing area location (BR), protection (PR), habitat type (HA), and the interaction of these factors for 
Opakapaka ( PristipomoicLes filamentosus), Kalekale (P. sieboldii), Onaga ( Etelis coruscans), and Ehu (E. carbunculus ) within 
the preferred depths of each species from our study of these species in the main Hawaiian Islands between May 2007 and 
June 2009. Locations of the 6 BRFAs where sampling was conducted are the following: Niihau (B), Kaena (D), Makapuu (E), 
Penguin Bank (F), Pailolo Channel (H), and Hilo (L). Protection is designated as inside (in) or outside (out) a BRFA. Habitat 
types are hard-high (HH), hard-low (HL), soft-high (SH), soft-low (SL). NS=nonsignificant comparisons. Preferred depths are 
noted under the species name in the first column. 
BR 
PR 
HA 
BRxPR 
BRxHA 
PRxHA 
BRxPRxHA 
Opakapaka 
(90-210 m) 
Largest 
in B 
Smallest 
in L 
Larger 
outside 
Smallest 
in HL 
NS 
(D) largest in SH, 
smallest in HL 
(E) largest in SH, 
smallest in HL 
(F) largest in high slope, 
smallest in low slope 
(L) largest in SL, 
smallest in HL 
NS 
(D in) SH>HL 
(E in) HH,SH>HL 
(E out) SH>HH>HL 
(F in) HH,SH>HL 
(F out) HH,SH>SL 
(L in) HH>HL 
(L out) SL>HH>SH>HL 
Kalekale 
(180-270 m) 
Smallest 
in D 
NS 
Largest 
in HH 
(F) larger inside 
(H) larger inside 
(L) larger outside 
NS 
NS 
NS 
Onaga 
(210-300 m) 
Smallest 
in H 
No test 
NS 
(H) larger inside 
(B) larger in HL 
than HH 
(F) similar mean size 
NS 
(B in) HL>HH 
(F in) HH>HL 
Ehu 
(210-300 m) 
Similar 
mean size 
No test 
NS 
NS 
NS 
NS 
No test 
tions in all size classes and did not show any habitat 
shifts with size (Pearson’s chi-square, P>0.05). Opak- 
apaka had a shift from hard-low habitats to hard-high 
habitats with an increase in size. There was a greater 
proportion of sexually mature individuals (>43 cm FL; 
Kikkawa, 1984) for this species over hard-high habi- 
tats, and individuals <43 cm FL were seen mostly 
in hard-low habitats. Although less evident than the 
habitat shift by Opakapaka, a habitat shift by Kale- 
kale to hard-high from other habitat types was ob- 
served within the size class of 25-35 cm. Onaga and 
Ehu were recorded mostly in hard-low habitats in all 
size classes. For Onaga, however, the smallest individ- 
uals (<55 cm FL) were found only in hard-low habi- 
tats, and, as size increased, hard-high habitats were 
equally dominant for this species. 
Discussion 
Depth has a significant influence on the distribution 
of bottomfishes in Hawaii. Two distinct depth group- 
ings were seen within the sampling range of this study. 
Opakapaka was dominant in the shallower end of the 
sampling depths (<200 m), and Kalekale, Onaga, and 
Ehu were observed more frequently toward the deep- 
er end (>200 m). This finding is consistent with that 
of previous studies in Hawaii (Haight, 1989; Everson 
et al., 1989; Merritt et al., 2011) and in the Mariana 
Archipelago (Polovina et al., 1985). When establishing 
species-specific differences in distribution, depth must 
be the first factor evaluated. 
Although the limitations of our sampling methods 
have been discussed in previous studies (e.g., Mer- 
ritt et al., 2011; Moore et al., 2013), it is important 
to review them here before further discussion of our 
results. The absence of a quantifiable sampling area, 
variability in the field of view of the BotCam, and the 
scale at which habitats were classified are confounding 
factors that limit the interpretation of the results of 
this study to a semiquantitative nature. Because the 
BotCam makes use of ambient light and because envi- 
ronmental conditions, such as water clarity can differ 
from site to site, variability in the visual area sampled 
was unavoidable. However, unlike other visual survey 
methods, where quadrats or transect lines are used, 
this approach reduces, but does not eliminate, the ef- 
fect of visual area because it relies on attracting fishes 
close to the cameras. What may be more important is 
the effect of the attracting bait-odor plume. 
It was our working assumption that any fish seen 
on BotCam video was from the targeted grid area 
