Stable Isotope Mixing Models Are Biased by the Choice of Sample Preservation and Pre-treatment: Implications for Studies of Aquatic Food Webs

Abstract

Stable isotope analysis has become one of the most widely used techniques in ecological studies. However, there are still uncertainties about the effects of sample preservation and pre-treatment on the ecological interpretation of stable isotope data and especially on Bayesian stable isotope mixing models. Here, Bayesian mixing models were used to study how three different preservation methods (drying, freezing, formalin) and two pre-treatments (acidification, lipid removal) affect the estimation of the utilized organic matter sources for two benthic invertebrate species (Limecola balthica, Crangon crangon) collected in the Baltic Sea. Furthermore, commonly used mathematical lipid normalization and formalin correction were applied to check if they were able to adjust the model results correctly. Preservation effects were strong on model outcomes for frozen as well as formalin preserved L. balthica samples, but not for C. crangon. Pre-treatment effects varied with species and preservation method and neither lipid normalization nor mathematical formalin correction consistently resulted in the desired model outcomes. Our analysis highlights that particularly small, not significant changes in stable isotope ratios introduced by different preservation and pre-treatments display a so far unrecognized source of error in stable isotope mixing models. We conclude that mathematical correction of benthic invertebrate stable isotopes data should be avoided for Bayesian mixing models and that previously unaddressed effects of sample preservation (especially those arising from preservation by freezing) have potentially biased our understanding of the utilization of organic matter in aquatic food webs.