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Incorporating concentration dependence in stable isotope mixing models.

Donald L Phillips1, Paul L Koch2

  • 1Office of Research and Development, National Health and Environmental Effects Research Laboratory, Western Ecology Division, U.S. Environmental Protection Agency, 200 SW 35th Street, 97333, Corvallis, OR, USA.

Oecologia
|May 27, 2017
PubMed
Summary
This summary is machine-generated.

A new concentration-weighted model accurately quantifies source contributions using stable isotopes, especially when elemental concentrations vary significantly between sources. This method improves dietary and ecological mixing models.

Keywords:
Carbon:nitrogen ratiosConcentrationDietary analysisMixing modelStable isotopes

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Area of Science:

  • Stable isotope analysis
  • Ecological modeling
  • Biogeochemistry

Background:

  • Stable isotopes (e.g., C, N) are natural tracers for quantifying source contributions in mixtures.
  • Standard linear mixing models assume equal source contributions for all elements, which fails when elemental concentrations differ significantly.

Purpose of the Study:

  • To develop and validate a concentration-weighted linear mixing model for stable isotope analysis.
  • To improve the accuracy of source contribution estimations when elemental concentrations vary among sources.

Main Methods:

  • Developed a concentration-weighted linear mixing model, generalizing to n elements and n+1 sources.
  • Conducted sensitivity analyses for C and N in three-source scenarios.
  • Applied the model to a case study of bears and a captive feeding study of mink.

Main Results:

  • Varying N concentration significantly impacted estimated source contributions in sensitivity analyses.
  • The concentration-weighted model provided more accurate dietary proportions for mink compared to the standard model.
  • The standard model failed to yield valid proportions in the mink feeding study.

Conclusions:

  • The concentration-weighted model is recommended when elemental concentrations differ substantially among sources.
  • This model enhances applications in dietary studies, food webs, water source tracing, and soil dynamics.
  • The model offers improved accuracy for ecological and geochemical stable isotope analyses.