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Related Experiment Videos

Combining sources in stable isotope mixing models: alternative methods.

Donald L Phillips1, Seth D Newsome, Jillian W Gregg

  • 1US Environmental Protection Agency, Office of Research & Development, Western Ecology Division, National Health & Environmental Effects Research Laboratory, 200 SW 35th St., Corvallis, OR, 97333, USA. Phillips.Donald@epa.gov

Oecologia
|February 16, 2005
PubMed
Summary
This summary is machine-generated.

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Stable isotope mixing models help identify source contributions but can be complex with many sources. This study presents methods to aggregate sources, either before or after analysis, to achieve clearer, more interpretable results for complex ecological and dietary studies.

Area of Science:

  • Ecology
  • Environmental Science
  • Biogeochemistry

Background:

  • Stable isotope mixing models are crucial for quantifying source contributions in various environmental and ecological studies.
  • A frequent challenge arises when numerous sources prevent a unique, interpretable solution.

Purpose of the Study:

  • To present and evaluate two distinct methodologies for addressing the issue of excessive sources in stable isotope mixing models.
  • To enhance the interpretability and feasibility of source contribution analysis when dealing with complex mixtures.

Main Methods:

  • A priori source aggregation: combining sources with similar isotopic signatures before analysis, contingent on statistical similarity and functional relevance.
  • Posteriori source aggregation: utilizing the IsoSource mixing model to identify all feasible solutions and then summing contributions from functionally related source groups.

Related Experiment Videos

Main Results:

  • A priori aggregation can simplify models but may increase uncertainty in end-member signatures and contribution estimates, quantifiable with the IsoError model.
  • Posteriori aggregation, demonstrated with a paleo-human dietary analysis, can yield narrower, more conclusive ranges for aggregate source contributions, revealing temporal dietary shifts.

Conclusions:

  • Both a priori and a posteriori aggregation strategies offer viable solutions for managing complex source numbers in stable isotope mixing models.
  • Posteriori aggregation, particularly when combined with functional grouping, can provide robust insights into dietary or environmental source dynamics that might otherwise be obscured.