variables in my linear regression models. I chose not to include BM or CL as variables because

body size was strongly affected by diet treatment (Fig. 3-1), and the goal of this study was to

assess the applicability of RNA:DNA measurements in estimating recent growth rates of wild

turtles with unknown dietary histories.

 Regression equations for SGRbm and SGRcI versus each biochemical index were

determined using least squares linear regression. Data were natural log-transformed, if necessary,

to linearize them and to decrease heteroscedasticity. I verified the assumptions of linear

regression by visually inspecting plots of Studentized deleted residuals versus standardized

predicted values. To construct comprehensive growth models for predicting SGR, data were

analyzed using stepwise multiple linear regression. The same transformations used for linear

regressions were used for stepwise multiple linear regressions. Condition index and all

biochemical indices measured for a particular tissue (liver, heart, or blood) were included in

separate models. A growth model incorporating condition index and all biochemical indices

measured for all tissues was also constructed. To enter a model, variables had to meet a 0.05

significance level. All statistical tests were performed using SPSS for Windows (Release 11.0.0).

Means are reported + standard errors with alpha set at 0.05.

 Results

 When fed to satiation, green turtle juveniles in the final 10-11 days of the 12-week trial

grew at an average SGRbm of 1.84% and 2.01% per day and an average SGRcI of 0.68% and

0.64% per day for AL and R-AL individuals, respectively. Food-restricted turtles grew much

more slowly at an average SGRbm of 0.34% per day and an average SGRcI of 0.15% per day (Fig.

3-1 and Table 3-1).

 Intake and growth patterns significantly affected all morphometric measurements of body

size (Fig. 3-1 and Table 3-1). At the time of tissue sampling, AL turtles were significantly