Bayesian stable isotope mixing models
By Andrew C. Parnell, D. Phillips, S. Bearhop, B. Semmens, Eric J. Ward, J. Moore, A. Jackson, J. Grey, David J. Kelly, Richard Inger. 2012
967 citations recorded by the source corpus.
In this paper, we review recent advances in stable isotope mixing models (SIMMs) and place them into an overarching Bayesian statistical framework, which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixture. The most widely used application is quantifying the diet of organisms based on the food sources they have been observed to consume. At the centre of the multivariate statistical model we propose is a compositional mixture of the food sources corrected for various metabolic factors. The compositional component of our model is based on the isometric log‐ratio transform. Through this transform, we can apply a range of time series and non‐parametric smoothing relationships. We illustrate our models with three case studies based on real animal dietary behaviour. Copyright © 2013 John Wiley & Sons, Ltd.
Subfields: Artificial Intelligence, Ecology, Paleontology
View Paper: https://www.semanticscholar.org/paper/854073652cfc2d774e86470c28c8cdab153bef9b
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Citations in the corpus
- Garden Bird Feeding: Insights and Prospects from a North-South Comparison of This Global Urban Phenomenon (2017, methodology): “Statistical approaches that allow dietary reconstruction from SIA outputs using Bayesian modeling are growing ever more sophisticated (e.g., Parnell et al., 2013) and now extend to multiple food (reference) sources.”
- A Bayesian framework for stable isotope mixing models (2013, background): “Oxygen and hydrogen, δ18 O and δ2H, vary across multiple spatial scales and environmental gradients (Bowen and Revenaugh 2003; Deines et al. 2009; Finlay et al. 2010; Solomon et al. 2011, 2009).”
- Exploring the Isotopic Niche: Isotopic Variance, Physiological Incorporation, and the Temporal Dynamics of Foraging (2015, methodology): “Isotope mixing models, which originally used a bootstrapping framework [39, 40] and now employ Bayesian methods [5, 6, 41, 42], are used to reconstruct the probability distribution that describes the contribution of different prey.”
- Unravelling the ecological role and trophic relationships of uncommon and threatened elasmobranchs in the western Mediterranean Sea (2015, background): “Moreover, by combining stable isotope values from consumers with those from their potential prey, isotopic mixing models can be applied to obtain estimates of the relative contribution of each prey item to the diet of the consumer (e.g. Parnell et al. 2013).”
- Connected macroalgal‐sediment systems: blue carbon and food webs in the deep coastal ocean (2019, methodology): “—Tracing organic matter using stable isotopes, from sources to potential sedimentary sinks, requires an understanding of how these signals may themselves vary at sources (Parnell et al. 2013).”