A quantitative approach to combine sources in stable isotope mixing models

By Eric J. Ward, B. Semmens, D. Phillips, J. Moore, N. Bouwes. 2011

59 citations recorded by the source corpus.

Stable isotope mixing models, used to estimate source contributions to a mixture, typically yield highly uncertain estimates when there are many sources and relatively few isotope elements. Previously, ecologists have either accepted the uncertain contribution estimates for individual sources or addressed the problem in an ad hoc way by combining either related sources prior to analysis or the estimated proportions of related sources following analysis. Neither of these latter approaches explicitly account for uncertainty in source combinations within the likelihood framework. In this paper we incorporate uncertainty in both the number of source groups and group assignment within a formal Bayesian mixing model framework. By dynamically exploring model complexity due to aggregating sources based on shared proportional contributions, we can estimate posterior probabilities of alternative group configurations, and construct posterior dendrograms of group membership. We apply this method to simulated data, and illustrate applications to two consumer datasets (rainbow trout, coastal mink). Our results demonstrate that estimating, rather than fixing, the number of proportional contributions in a mixing model can improve model inference and reduce bias in estimates of source contributions to a mixture.

Subfields: Astronomy and Astrophysics, Atmospheric Science, Ecology

View Paper: https://www.semanticscholar.org/paper/c7786e3dd721595d018352538448161a51aa96ff

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Citations in the corpus

Diet-specific biomarkers show that high-quality phytoplankton fuels herbivorous zooplankton in large boreal lakes (2014, background): “Recent studies have concluded that Bayesian mixing models are robust to limitations on the number of sources (Ward et al., 2011; Semmens et al., 2013), but the application of SI-based mixing models is clearly limited in cases where distinct resources have overlapping SI signatures.”
Tools for quantifying isotopic niche space and dietary variation at the individual and population level (2012, unknown): “Other approaches, such as binning sources with similar isotopic values, can be utilized to further decrease the number of potential sources and increase the accuracy of the results (Phillips et al. 2005; Ward et al. 2011).”
Amphibian Contributions to Ecosystem Services (2014, background): “For generalist and omnivorous amphibians, fatty acid stable isotope analysis and mixing models may elucidate amphibian-altered energy pathways in the ecosystem (DeForest et al. 2004; Moore and Semmens 2008; Parnell et al. 2010; Ward et al. 2011).”
Best practices for use of stable isotope mixing models in food-web studies (2014, methodology): “Ward et al. (2011) proposed a procedure using the MixSIR Bayesian mixing model to evaluate the posterior probabilities of various combinations of sources for the a posteriori approach.”
Applying stable isotopes to examine food‐web structure: an overview of analytical tools (2012, background): “Bayesian approaches are evolving rapidly, greatly expanding in capability and scope (Jackson et al., 2011; Ward et al., 2011), and are being applied to yield novel insights into aspects of trophic structure (e.”