Arendt et al.: Temporal trends and influences on fishery-independent catch rates for Caretta caretta in an important coastal foraging region 
477 
0to5.0 5.1 to 10.0 10.1 to 15.0 15.1 to28.5 
Distance from shore (km) 
Figure 3 
Modeled catch (mean ±95% Cl) of loggerhead sea turtles ( Caretta caretta) 
per linear kilometer with respect to incremental distances from shore 
during 4097 coastal trawling events conducted between St. Augustine, 
Florida, (29.9°N) and Winyah Bay, South Carolina, (33.1°N) in 2000-03, 
2008-09, and 2011. Distance from shore was analyzed as a continuous 
variable, but it is plotted here as a factor for comparative purposes. 
The black line denotes overall catch rates. Bars denote the following 
5-cm size classes of minimum straight-line carapace length: 55.1-60.0 
(light gray); 60.1-65.0 (dark gray); 65.1-70.0 (white); 70.1-75.0 (medium 
gray); 75.1-80.0 (charcoal). 
cant terms in the final model for loggerhead sea turtles 
75.1- 80.0 cm SCLmin and accounted for 1.3% and 2% 
of data set deviance, respectively (Table 3). Transect 
bearing was retained only as a significant model term 
overall and for loggerhead sea turtles that measured 
60.1- 65.0 cm SCLmin and accounted for <0.3% of data 
set deviance. 
Seafloor type, bearing from inlet, tide range, mean 
trawl depth, and the interaction between distance from 
shore and distance from inlet were retained as a mix- 
ture of significant or nonsignificant terms in a subset 
of final models. Seafloor type was significant for the 
overall data set and for loggerhead sea turtles that 
measured 60.1-70.0 cm SCLmin, where it explained 
0.6-1. 6% of data set deviance (Table 3). Greatest catch 
rates were associated with habitats that were not classi- 
fied as hard (Fig. 5), and these habitats represented 54 
±9% (mean ±SD) of all trawling events; probably hard 
and hard habitats constituted 21 ±5% and 25 ±8% of 
trawling events, respectively. Distributions of seafloor 
type differed significantly among years (^ 2 12 = 160.0, 
P<0.001); however, temporal trends were not detected 
(F 15 =0.0, r 2 =0.00, P=0.966) in the annual proportion 
of trawling events classified as not hard. 
When retained, bearing from inlet was predominantly 
(3 of 4 models) significant but only accounted for 0.2- 
0.6% of data set deviance (Table 3). Mean trawl depth 
and tide range were retained only as significant terms 
for loggerhead sea turtles that measured 75.1-80.0 cm 
SCLmin, where they accounted for 1.0% and 0.9% of 
data set deviance, respectively (Table 3). The interac- 
tion between distance from shore and distance to inlet 
was significant only for the overall data set in the final 
model, and it accounted for 0.2% of data set deviance 
(Table 3). Of the remaining 13 parameters, 9 were re- 
tained only as nonsignificant terms in a subset of fi- 
nal models and 4 were excluded from all final models 
(Table 3). 
Discussion 
Trawling generated a large annual sample size of log- 
gerhead sea turtles over a vast coastal expanse in a 
concise time frame, and this large sample size in turn 
enabled a reliable assessment of interannual trends. 
Although trawling admittedly is more expensive than 
other methods (Bjorndal and Bolten, 2000), it is also an 
effective and appropriate means for the capture of sea 
turtles in turbid coastal waters where sea turtles are 
seasonally abundant (Schmid, 1995; Casale et al., 2004). 
Therefore, the expense associated with collection of the 
