Rooper and Martin: Comparison of indices of abundance with biomass estimates from trawl surveys 
25 
Table 3 
Habitat variables (and abbreviations from the text) used in the habitat modeling analysis for rockfish species in the Gulf of 
Alaska. The units of each measurement and the definition of how the variable was acquired, the process the variable is meant to 
index , and the source of the data are also provided. 
Unit 
Definition 
Index 
Data source 
Shrimp abundance (P) 
kg/ha 
Shrimp (combined species) 
catch per unit of effort 
Prey 
availability 
Bottom trawl haul 
catch 
Bottom temperature (T) 
°C 
Average bottom temperature 
microbathy- 
thermograph 
Bottom depth (D) 
m 
Average bottom depth 
microbathy- 
thermograph 
Local slope (S) 
% change 
Slope at each bottom 
trawl station 
Kriged bathymetry 
maps 
Coral and sponge abundance (CS) 
log( kg/ha) 
Combined catch per unit of 
effort of sponge and coral 
Refuge from 
predation 
Bottom trawl haul 
catch 
Thermocline depth/bottom depth (TD) 
Ratio of the thermocline 
depth to the bottom depth 
Water column 
stratification 
microbathy- 
thermograph 
a shallow thermocline could indicate nutrient-limited 
growth. For this analysis the water column stratifica- 
tion was estimated by the ratio of the thermocline depth 
to the bottom depth (i.e., when the ratio = l, the entire 
water column was mixed and no thermocline was pres- 
ent). The depth of the thermocline was estimated algo- 
rithmically from data collected with the microbathy- 
thermograph (MBT) attached to the trawl headrope. 
Data representing less than 5 meters in depth were 
excluded. The temperatures as a function of depth were 
smoothed with a smooth spline implemented in R soft- 
ware (R Foundation for Statistical Computing, Vienna, 
Austria) and the rate of change in temperature per 
unit of depth was estimated by dividing the change in 
smoothed temperature by the change in depth for each 
successive MBT observation. The descent rate of the net 
slows as it approaches the bottom after the doors have 
reached the bottom, and this slow descent sometimes 
resulted in anomalous results as the changes in depth 
became quite small. Therefore, data where the rate of 
depth change fell below 0.12 m/s (almost exclusively 
after doors reached the bottom) were excluded from 
consideration. No thermocline estimation was attempted 
when the temperature difference between the maximum 
and minimum temperatures during the descent of the 
trawl net were less than 0.4°C and these areas were 
assumed to be well-mixed to the bottom. The resulting 
estimates were binned into 10 equal intervals between 
5 meters and the maximum depth when the net reached 
the bottom. A mean of the rate of temperature change 
was estimated for each bin. Within the bin with the 
highest negative mean temperature change, the single 
depth observation associated with the highest negative 
temperature change was used as the estimate of ther- 
mocline depth. 
Rocky, hard bottom substrates and benthic inverte- 
brates are sources of refuge from predators and thus 
are presumed to be important in determining survival. 
Hard seafloor in Alaska is often substrate for a com- 
bination of benthic invertebrates, including corals and 
sponges (Freese, 2001), and rockfishes are often as- 
sociated with these invertebrates (Rooper and Boldt, 
2005). The log-transformed CPUE of combined coral 
and sponge (coral and sponge abundance) was used as 
an index of the amount of potential refuge from preda- 
tion at each trawl haul site in this analysis. 
The final habitat variable used in this analysis was 
an index of prey availability for the species (shortspine 
thornyhead, rougheye and blackspotted rockfish, and 
shortraker rockfish) that consumed large or benthic 
prey (such as shrimp, squid, or myctophid fish). Shrimp 
of a number of taxa (Pandalidae, Crangonidae, etc.) are 
captured in bottom trawl hauls and the shrimp abun- 
dance (kg/ha) for each bottom trawl haul was used as 
an index of the amount of prey available at the trawl 
survey station for the shrimp-consuming species. 
To model rockfish abundance, LCPUE was estimated 
as a function of six habitat variables: depth (D), tem- 
perature (T), thermocline depth to bottom depth ratio 
(TD), local bottom slope (S), coral and sponge abun- 
dance (CS), shrimp abundance (P), and a dummy vari- 
able indicating the year effect (Y): 
LCPUE = R* 
'f{D) + f{T) + f(S) + f(TD) + 
f(CS) + f(P) + Y + £ 
( 1 ) 
where R = presence (1) or absence (0) in the analysis of 
niche dimensions (stage 1), and e is the error 
term. 
As in Rooper and Martin (2009), the relationships 
between rockfish LCPUE and habitat variables were 
estimated with one of three equations. The most com- 
