Estimating the Diets of Animals Using Stable Isotopes and a Comprehensive Bayesian Mixing Model

John B Hopkins,Jake M Ferguson,Lyle Konigsberg

doi:10.1371/journal.pone.0028478

John B Hopkins, Jake M Ferguson + Show 1 more

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https://doi.org/10.1371/journal.pone.0028478

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Journal: PLoS ONE	Publication Date: Jan 3, 2012
Citations: 199	License type: CC BY 4.0

Affiliation: University of Florida, Montana State University

Abstract

Using stable isotope mixing models (SIMMs) as a tool to investigate the foraging ecology of animals is gaining popularity among researchers. As a result, statistical methods are rapidly evolving and numerous models have been produced to estimate the diets of animals—each with their benefits and their limitations. Deciding which SIMM to use is contingent on factors such as the consumer of interest, its food sources, sample size, the familiarity a user has with a particular framework for statistical analysis, or the level of inference the researcher desires to make (e.g., population- or individual-level). In this paper, we provide a review of commonly used SIMM models and describe a comprehensive SIMM that includes all features commonly used in SIMM analysis and two new features. We used data collected in Yosemite National Park to demonstrate IsotopeR's ability to estimate dietary parameters. We then examined the importance of each feature in the model and compared our results to inferences from commonly used SIMMs. IsotopeR's user interface (in R) will provide researchers a user-friendly tool for SIMM analysis. The model is also applicable for use in paleontology, archaeology, and forensic studies as well as estimating pollution inputs.

Highlights

Stable isotopes were first used to investigate the foraging ecology of animals in the 1970s [1,2,3,4,5]
Studies used stable isotope analysis (SIA) to determine the relative importance of food sources to animals by comparing distributions of isotope ratios for animal tissues to the foods they consume after corrected for fractionation—a technique primarily used when food sources had distinctly different isotope values (e.g., C3 and C4 plants, or prey that differ in trophic level) [2,6]
IsotopeR generated credible intervals that were generally wider than other models (Fig. 2, Tables S5 & S6); IsotopeR calculated more accurate parameter estimates because the model includes all recognized and quantifiable SIMM features, including measurement error, concentration dependence, isotopic correlation, individual-level estimation, and a fully Bayesian calculation

Summary

Introduction

Stable isotopes were first used to investigate the foraging ecology of animals in the 1970s [1,2,3,4,5]. Studies used stable isotope analysis (SIA) to determine the relative importance of food sources to animals by comparing distributions of isotope ratios (expressed as isotope values; derived below) for animal tissues to the foods they consume after corrected for fractionation (the sorting of isotopes during natural biochemical processes)—a technique primarily used when food sources had distinctly different isotope values (e.g., C3 and C4 plants, or prey that differ in trophic level) [2,6]. Euclidian distance formulas were used in some early studies (e.g., [14,15,16,17,18]); these methods did not provide correct solutions for observed and simulated data [19] These Euclidean distance models failed to preserve mass balance, an application of the law of conservation of mass which states that the proportional assimilated dietary contributions (mass) flowing into an organism or population are constrained to sum to one. The profusion of SIMMs (many of which are discussed in this paper) indicates the importance of this field to ecologists, current models require researchers to make tradeoffs (Table 1) when choosing one model over another

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