|Document Type:||Journal Article|
|Title:||A Fatty Acid Based Bayesian Approach for Inferring Diet in Aquatic Consumers|
|Author:||A.W.E. Galloway, M. T. Brett, Gordon W. Holtgrieve, E. J. Ward, A.P. Ballantyne, C. W. Burns, M. J. Kainz, D. C. Müller-Navarra, J. Persson, J. L. Ravet, U. Strandberg, S. J. Taipale, G. Alhgren|
|Keywords:||fatty acid,mixing model,MixSIR,Bayesian,daphnia|
1. We developed a novel quantitative approach for infering primary producer contributions to consumer diets using a Bayesian mixing model framework. Our model, Fatty Acid Source-Tracking Algorithm in R (FASTAR), was adapted from the stable isotope model MixSIR. We generated a ‘resource library’ of Daphnia fatty acid (FA) signatures from 34 feeding trials using diverse phytoplankton lineages. Because FASTAR is based on the FA profiles of zooplankton consuming known diets, and not the diets directly, trophic modification of consumer lipids is directly accounted for in the model.