Data from: Evaluating Bayesian stable isotope mixing models of wild animal diet and the effects of trophic discrimination factors and informative priors

1. Ecologists quantify animal diets using direct and indirect methods,
including analysis of faeces, pellets, prey items and gut contents. For
stable isotope analyses of diet, Bayesian stable isotope mixing models
(BSIMMs) are increasingly used to infer the relative importance of food
sources to consumers. Although a powerful approach, it has been hard to
test BSIMM performance for wild animals because precise, direct dietary
data are difficult to collect. 2. We evaluated the performance of BSIMMs
in quantifying animal diets when using δ13C and δ15N stable isotope ratios
from the feathers and red blood cells of common buzzard Buteo buteo
chicks. We analysed mixing model outcomes with various trophic
discrimination factors (TDFs), with and without informative priors, and
compared these to direct observations of prey provisioned to chicks by
adults at nests, using remote cameras.  3. Although BSIMMs with
different TDFs varied markedly in their performance, the statistical
package SIDER generated TDFs for both feathers and blood that resulted in
model outputs that accorded well with direct observations of prey
provisioning. Using feather TDFs derived from captive peregrines Falco
peregrinus resulted in estimates of diet composition that were also
similar to provisioned prey, though blood TDFs from the same study
performed poorly. The inclusion of informative priors, based on
conventional analysis of pellet and prey remains, markedly reduced model
performance. 4. BSIMMs can provide accurate assessments of diet in wild
animals. TDF estimates from the SIDER package performed well. The
inclusion of informative priors from conventional methods in Bayesian
mixing models can transfer biases into model outcomes, leading to
erroneous results.