Interpreting temporal variation in omnivore foraging ecology via stable isotope modelling

1. The use of stable carbon (C) and nitrogen (N) isotopes ( δ 15 N and δ 13 C, respectively) to delineate trophic patterns in wild animals is common in ecology. Their utility as a tool for interpreting temporal change in diet due to seasonality, migration, climate change or species invasion depends upon an understanding of the rates at which stable isotopes incorporate from diet into animal tissues. To best determine the foraging habits of invasive rats on island ecosystems and to illuminate the interpretation of wild omnivore diets in general, I investigated isotope incorporation rates of C and N in fur, liver, kidney, muscle, serum and red blood cells (RBC) from captive rats raised on a diet with low δ 15 N and δ 13 C values and switched to a diet with higher δ 15 N and δ 13 C values. 2. I used the reaction progress variable method (RPVM), a linear fitting procedure, to estimate whether a single or multiple compartment model best described isotope turnover in each tissue. Small sample Akaike Information criterion (AIC c ) model comparison analysis indicated that 1 compartment nonlinear models best described isotope incorporation rates for liver, RBC, muscle, and fur, whereas 2 compartment nonlinear models were best for serum and kidney. 3. I compared isotope incorporation rates using the RPVM versus nonlinear models. There were no differences in estimated isotope retention times between the model types for serum and kidney (except for N turnover in kidney from females). Isotope incorporation took longer when estimated using the nonlinear models for RBC, muscle, and fur, but was shorter for liver tissue. 4. There were no statistical differences between sexes in the isotope incorporation rates. I also found that N and C isotope incorporation rates were decoupled for liver, with C incorporating into liver tissue faster than N. 5. The data demonstrate the utility of analysing isotope ratios of multiple tissues from a single animal when estimating temporal variation in mammalian foraging ecology.