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Fishery Bulletin 110(1) 
Theoretical quantiles 
Theoretical quantiles 
Theoretical quantiles 
Theoretical quantiles 
Theoretical quantiles 
Figure 2 
Quantile-quantile normal plots of residuals from the best-fitting models of rockfish abundance 
predicted by habitat variables for the Gulf of Alaska bottom trawl survey data. Plots are shown 
only for the species where a normal distribution was used in the modeling. 
model-based estimate (0.21) was slightly smaller than 
the stratified estimate (0.24). Shortspine thornyhead 
was the only species for which there was a noticeable 
difference between the two methods in the variability 
around the point estimates of CPUE each year. The 
habitat model-based estimates had much larger con- 
fidence intervals than the stratified survey estimates. 
It could be argued that the estimates provided by the 
stratified survey were unreasonably small, because the 
average coefficient of variability was ~7% across years. 
It is unclear why the habitat model-based estimates had 
higher variability in this case. 
The habitat model-based abundance index presented 
here is different from other model-based indices in the 
methods used to model abundance. For one, it is rare 
to model a fisheries-independent data set. Modeling 
fishery-collected data to derive an abundance index 
is much more common (Maunder and Punt, 2004). 
Previous model-based abundance indices have been 
produced for shortbelly rockfish (Field et ah, 2007), 
as well as other fish species (Goodyear, 2003) with 
varying levels of success. These models have generally 
used a combination of generalized linear or additive 
modeling, with a two-stage model predicting presence 
and absence and then abundance (Maunder and Punt, 
2004). This approach is similar to ours, but the model 
forms presented here were chosen a priori based on 
probable ecological relationships with resource conti- 
nua (May, 1973). The resulting models may be more 
robust to changing patterns in the bottom trawl survey 
data because the habitat variables used in our analy- 
sis were chosen to reflect major processes influencing 
distribution, as well as the survival and growth for 
rockfish species. 
