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Inference for stable isotope mixing models: a study of the diet of dunlin
Author(s) -
Erhardt Erik Barry,
Bedrick Edward J.
Publication year - 2014
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/rssc.12047
Subject(s) - frequentist inference , stable isotope ratio , inference , mixing (physics) , seabird , statistical inference , isotope , population , isotope analysis , statistics , mathematics , econometrics , ecology , computer science , biology , bayesian inference , bayesian probability , demography , physics , artificial intelligence , predation , quantum mechanics , sociology
Stable isotope sourcing is used to estimate proportional contributions of sources to a mixture, such as in the analysis of animal diets and plant nutrient use. Statistical methods for inference on the diet proportions by using stable isotopes have focused on the linear mixing model. Existing frequentist methods assume that the diet proportion vector can be uniquely solved for in terms of one or two isotope ratios. We develop large sample methods that apply to an arbitrary number of isotope ratios, assuming that the linear mixing model has a unique solution or is overconstrained. We generalize these methods to allow temporal modelling of the population mean diet, assuming that isotope ratio response data are collected over time. The methodology is motivated by a study of the diet of dunlin, a small migratory seabird.