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

Title: Evaluating Bayesian stable isotope mixing models of wild animal diet and the effects of trophic discrimination factors and informative priors
Authors: Swan, George J. F.; Bearhop, Stuart; Redpath, Steve M.; Silk, Matthew J.; Goodwin, Cecily E. D.; Inger, Richard; McDonald, Robbie A.
Contributors: Freckleton, Robert; University of Exeter; Comisión Nacional de Investigación Científica y Tecnológica; H2020 European Research Council
Source: Methods in Ecology and Evolution ; volume 11, issue 1, page 139-149 ; ISSN 2041-210X 2041-210X
Publisher Information: Wiley
Publication Year: 2019
Collection: Wiley Online Library (Open Access Articles via Crossref)
Description: 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. We evaluated the performance of BSIMMs in quantifying animal diets when using δ 13 C and δ 15 N 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. 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, although 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. 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.
Document Type: article in journal/newspaper
Language: English
DOI: 10.1111/2041-210x.13311
DOI: 10.1111/2041-210X.13311
Availability: https://doi.org/10.1111/2041-210x.13311; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2F2041-210X.13311; https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.13311; https://onlinelibrary.wiley.com/doi/full-xml/10.1111/2041-210X.13311; https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.13311
Rights: http://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.6712D902
Database: BASE