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Improving Bayesian isotope mixing models: a response to Jackson et al. (2009)
Brice X Semmens1, Jonathan W Moore, Eric J Ward
1Northwest Fisheries Science Center, National Marine Fisheries Service, Seattle, WA 98112, USA. brice.semmens@noaa.gov
Ecology Letters
|February 28, 2009
Summary
The MixSIR software accurately estimates prey contributions in predator diets using stable isotope mixing models. Minor coding errors were fixed, and the tool demonstrates robustness to additional error.
Area of Science:
- Ecology
- Quantitative Ecology
Background:
- A Bayesian framework and MixSIR software were developed for stable isotope mixing models.
- Criticism of MixSIR performance was based on flawed simulated data.
Discussion:
- Re-evaluation identified and fixed two minor coding errors in MixSIR.
- Correctly simulated data show MixSIR accurately estimates proportional prey contributions.
- MixSIR demonstrated robustness to additional unquantified error.
Key Insights:
- MixSIR accurately estimates prey proportions in predator diets.
- The software is robust to additional error beyond model assumptions.
- A Dirichlet prior is recommended for source proportion parameters.
Outlook:
- Further model complexity, such as additional error parameters, requires careful data-driven evaluation.
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