A revised model for lipid-normalizing δ13C values from aquatic organisms, with implications for isotope mixing models
Mikko Kiljunen, Department of Biological and Environmental Science, University of Jyväskylä, PO Box 35, FIN-40014, Finland (fax + 358 14 2602321; e-mail email@example.com).
- 1Stable isotope analyses coupled with mixing models are being used increasingly to evaluate ecological management issues and questions. Such applications of stable isotope analyses often require simultaneous carbon and nitrogen analyses from the same sample. Correction of the carbon isotope values to take account of the varying content of 13C-depleted lipids is then frequently achieved by a lipid-normalization procedure using a model describing the relationship between change in δ13C following lipid removal and the original C:N ratio of a sample.
- 2We evaluated the applicability of two widely used normalization models using empirical data for muscle tissue from a wide range of fish and for aquatic invertebrates. Neither normalization model proved satisfactory, and we present some modifications that greatly improve the fit of one of the models to the fish muscle data. For invertebrates we found no clear relationship between change in δ13C following lipid removal and the original C:N ratio.
- 3We also examined the effect of lipid-normalization on the output of a mixing model designed to calculate the proportional contribution of prey items to the diet of a consumer. Mixing model output was greatly influenced by whether prey or consumer values alone or together were lipid-normalized and we urge caution in the interpretation of results from these models pending further experimental evidence.
- 4Synthesis and applications. We describe a revised lipid-normalization model that should be applicable to a wide range of marine and freshwater fish species in studies applying stable isotope analyses to ecological management issues. However, we strongly advise against applying these kinds of lipid-normalization models to aquatic invertebrate data. The interpretation of outputs from mixing models is greatly influenced by whether the carbon isotope data have been lipid-normalized or not.