Evidence map›Paper›PMID 29942712›Full record

ArticlePeerJ2018

Analyzing mixing systems using a new generation of Bayesian tracer mixing models.

Brian C Stock, Andrew L Jackson, Eric J Ward, Andrew C Parnell, Donald L Phillips, Brice X Semmens

Abstract read
In one paragraph

Article in PeerJ, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 185 papers.

0numbers the graph read from it
0cells of the map it votes in
185citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

185 citing papers in PubMed.

  1. The Single, the Whole, and the Pooled: Implications of Tissue Choice for Stable Isotope Analysis.Journal of experimental zoology. Part A, Ecological and integrative physiology · 2026
    Review
  2. Article
  3. Predator-mediated trophic connectivity between reef and oceanic habitats in Palau.Ecological applications : a publication of the Ecological Society of America · 2026
    Article
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  10. A trade-off in vital rates for a large carnivore inhabiting an anthropogenic landscape and a protected island ecosystem.Ecological applications : a publication of the Ecological Society of America · 2026
    Article
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125 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Brian C StockScripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA.ORCID 0000-0002-2393-6747
Andrew L JacksonDepartment of Zoology, School of Natural Sciences, University of Dublin, Trinity College, Dublin, Ireland.ORCID 0000-0001-7334-0434
Eric J WardNorthwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA.ORCID 0000-0002-4359-0296
Andrew C ParnellSchool of Mathematics and Statistics, Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland.
Donald L PhillipsEcoIsoMix.com, Corvallis, OR, USA.
Brice X SemmensScripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ongoing evolution of tracer mixing models has resulted in a confusing array of software tools that differ in terms of data inputs, model assumptions, and associated analytic products. Here we introduce MixSIAR, an inclusive, rich, and flexible Bayesian tracer (e.g., stable isotope) mixing model framework implemented as an open-source R package. Using MixSIAR as a foundation, we provide guidance for the implementation of mixing model analyses. We begin by outlining the practical differences between mixture data error structure formulations and relate these error structures to common mixing model study designs in ecology. Because Bayesian mixing models afford the option to specify informative priors on source proportion contributions, we outline methods for establishing prior distributions and discuss the influence of prior specification on model outputs. We also discuss the options available for source data inputs (raw data versus summary statistics) and provide guidance for combining sources. We then describe a key advantage of MixSIAR over previous mixing model software-the ability to include fixed and random effects as covariates explaining variability in mixture proportions and calculate relative support for multiple models via information criteria. We present a case study of

Indexed as

Bayesian statisticsFatty acidsMixing modelsMixSIRSIARStable isotopesTrophic ecology

Identifiers

PMID29942712
PMCPMC6015753

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.