articlePLoS ONEMar 11, 2010GOLD OA

Source Partitioning Using Stable Isotopes: Coping with Too Much Variation

University College Dublin · University of Exeter · +1 more institution

PubMed
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Abstract

Background

Stable isotope analysis is increasingly being utilised across broad areas of ecology and biology. Key to much of this work is the use of mixing models to estimate the proportion of sources contributing to a mixture such as in diet estimation. METHODOLOGY: By accurately reflecting natural variation and uncertainty to generate robust probability estimates of source proportions, the application of Bayesian methods to stable isotope mixing models promises to enable researchers to address an array of new questions, and approach current questions with greater insight and honesty.

Conclusions

We outline a framework that builds on recently published Bayesian isotopic mixing models and present a new open source R package, SIAR. The formulation in R will allow for continued and rapid development of this core model into an all-encompassing single analysis suite for stable isotope research.

Citation impact

2,898
total citations
FWCI
117.34
Percentile
100%
References
27
Citations per year

Authors

4

Topics & keywords

Keywords
  • Suite
  • Stable isotope ratio
  • Bayesian probability
  • Computer science
  • Variation (astronomy)
  • Isotope analysis
  • Mixing (physics)
  • Data science
UN Sustainable Development Goals
  • Life in Land
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Funding