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Fishery Bulletin 108(3) 
bad, or reflective) experienced by each observer. Visibil- 
ity was defined as the observer’s subjective assessment 
of the conditions for the likelihood of seeing a harbor 
porpoise and the observer’s assessment of the effect of 
glare, sea state, as well as less quantifiable factors such 
as turbidity, sun angle, unusual weather conditions, and 
fatigue on the observer’s ability to sight a harbor por- 
poise. The observers reported these environmental data 
as changes in such data were noticed along a transect. 
For each sighting, the observer notified the computer 
operator when the beam line of the plane crossed the 
animal’s location. The primary observers used inclinom- 
eters to obtain the vertical angle below the horizontal to 
convert the perpendicular distance of the animal from 
the trackline (Lerczak and Hobbs, 1998). To determine 
the distance of a sighting from the trackline indicated 
by a center line on the belly window, the window was 
subdivided with a grease pencil into six 10°-bins (out 
to 30° to either side of the trackline for an averaged 
eye height), labeled 1-6 from port to starboard. When 
alerted to a sighting by the primary or independent 
observers, the computer operator immediately entered 
the sighting by using a hot key assigned to an observer 
(which recorded the observer’s initials and which cap- 
tured the time and position from the GPS unit). The hot 
key also opened a window for entering species name, 
vertical angle or angle bin, group size, and any notable 
animal behavior. 
Matching sightings from side and belly windows 
Sighting data (time, perpendicular distance, species, 
and group size) collected on the same transects were 
compared between side and belly observers. For compari- 
son purposes, left- and right-side sighting angles were 
converted to corresponding belly observer bin number. 
Sightings were considered matches (same group seen 
by both observers) if they 1) occurred within 5 seconds 
of each other; 2) were not greater than one 10° bin dif- 
ference; and 3) met other conditions such as a species 
of similar size or of hierarchical relation (e.g., harbor 
porpoise matched to unidentified small cetacean) and 
similar group size. Matched sightings were used 1) 
to estimate an empirical average angle for each belly 
window bin, based on the angles measured from the 
side windows; 2) to identify circumstances resulting 
in unreliable species identifications (see Error's in spe- 
cies identification in Appendix I); 3) to estimate bias 
in group-size estimates by the belly observer; 4) to 
estimate perception bias and g(0) (here g(0) accounts 
only for the consequences of perception bias; correction 
for availability bias is treated separately as described 
below); and 5) to eliminate duplicate sightings from the 
distance analysis. 
Correction for bias in group-size estimates determined 
by belly observers 
Initial inspection of the data when both the side and 
belly observers reported a sighting indicated that the 
group size estimate of the belly observer was occasion- 
ally less than that provided by the side observer — a 
result of the restricted visual field and limited observa- 
tion time for the belly observer. For each of these pairs, 
the count by the side observer was divided by the count 
by the belly observers. These ratios were then grouped 
by belly observer group size and averaged to estimate 
a correction for each group size reported by the belly 
observer. The standard error for each correction factor 
was estimated by the usual formula. The correction was 
applied to all group sizes from belly sightings included 
in the average estimate of group size. 
Distance smearing 
Angle rounding occurred in both the side observer data 
and the belly observer data. In the case of the side 
observer data, peaks in frequency occurred on multiples 
of 5°. The rounding of angles often occurred after the 
sighting was out of the field of view and the observer 
estimated the angle from a remembered location. The 
accuracy for these remembered locations may not have 
been any better than 5°, and therefore created a ten- 
dency for observers to use a close 5° increment number 
rather than one of the marks in between. Belly observer 
data were assigned to a bin and were thus automati- 
cally rounded. To remove these effects, side sightings 
were dithered uniformly over 13 m (2.5° on either side 
of the reported angle) and belly sightings were dithered 
uniformly over 26 m (5° on either side of the reported 
angle, the center of sighting bins). The dithering dis- 
tance was chosen empirically as the minimum distance 
necessary to remove the rounding effect. The dithering 
was repeated several times and the cumulative distri- 
bution of the sightings by distance to the trackline was 
examined. An instance of the dithering which gave a 
visually smooth distribution was retained and used as 
the data set for further analysis to estimate the sight- 
ing distribution. 
Estimation of perception bias and g( 0) 
All three years of data were combined to estimate per- 
ception bias from comparisons of the primary and the 
independent observer sightings. Logistic regression with 
a generalized linear model (the GLM function in S-PLUS, 
Lucent Technologies, Murray Hill, NJ) and an offset 
algorithm for comparison of paired sightings (Buckland 
et al., 1993) was used to estimate the perception bias of 
the side and belly observers on the trackline. Review of 
the ratio of matched to unmatched sighting for the belly 
and side observers by 25-m bins indicated that the two 
inner bins were consistent with each other (0-25 m and 
25-50 m), whereas the outer bin (50-75 m) differed. Con- 
sequently, perception bias was estimated by using only 
sightings within 50 m of the trackline (approximately 
20° at the standard survey altitude or bins 2 through 5 
in the belly window). Sightings beyond this cutoff dis- 
tance were excluded. Possible covariates in the logistic 
regression were visibility, sea state, cloud cover, glare, 
