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MixSIAR specifications

Information


Unique identifier OMICS_30433
Name MixSIAR
Software type Package/Module
Interface Command line interface, Graphical user interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 3.0
Computer skills Advanced
Version 3.1.10
Stability Stable
Requirements
testthat, rmarkdown, knitr, ggplot2(≥2.2.1), R(≥3.4.0), rjags(≥4-6), R2jags(≥0.5-7), MASS(≥7.3), RColorBrewer(≥1.1), reshape(≥0.8.7), reshape2(≥1.4.3), lattice(≥0.20-35), MCMCpack(≥1.4-2), ggmcmc(≥1.1), coda(≥0.19-1), loo(≥2.0.0), bayesplot(≥ 1.4.0), gWidgets(≥0.0-54), gWidgetsRGtk2(≥0.0-86), splancs(≥ 2.01-40)
Maintained Yes

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Documentation


Publication for MixSIAR

MixSIAR citations

 (12)
library_books

Quantitative assessment of Pb sources in isotopic mixtures using a Bayesian mixing model

2018
Sci Rep
PMCID: 5906678
PMID: 29670142
DOI: 10.1038/s41598-018-24474-0

[…] Another potential application of MixSIAR and isotope mixing is the interpretation of the Pb isotope signal as recorded in individual metal artefacts. Determining the provenance of metal artefacts is of crucial importance in archaeolo […]

library_books

Time and depth wise trophic niche shifts in Antarctic benthos

2018
PLoS One
PMCID: 5865725
PMID: 29570741
DOI: 10.1371/journal.pone.0194796

[…] f all potential food sources. In order to describe the diet of specimens, a Bayesian mixing model, returning outputs as probability distributions for the parameters of interest, was applied using the mixSIAR package (implemented by R software ver. 2.15.2). The output of the model is a probability density function of plausible values for the proportion of the diet accounted for by each dietary item […]

library_books

Evaluating the use of stable isotope analysis to infer the feeding ecology of a growing US gray seal (Halichoerus grypus) population

2018
PLoS One
PMCID: 5821315
PMID: 29466372
DOI: 10.1371/journal.pone.0192241

[…] s by selecting the values that provided the best fit (i.e. fewest number of consumer signatures near the edge of the polygon’s 95% confidence interval).Stable isotope mixing models were run using the MixSIAR package []. Separate models were run for each tissue (vibrissae and lanugo) and for each prey cluster grouping (six prey sources and three prey sources). Additional variants of the three prey […]

library_books

Trophic signatures of seabirds suggest shifts in oceanic ecosystems

2018
Sci Adv
PMCID: 5812733
PMID: 29457134
DOI: 10.1126/sciadv.aao3946

[…] We used hierarchal Bayesian mixing models [R package MixSIAR; ()] to visualize shifts in diet proportions of prey sources across time. In this model, the TP values in are the mixture biotracer response as a function of prey item assimilation, where the […]

library_books

Grazer responses to variable macroalgal resource conditions facilitate habitat structuring

2018
R Soc Open Sci
PMCID: 5792922
PMID: 29410845
DOI: 10.1098/rsos.171428

[…] All data were analysed in R [] using the ‘nlme’, ‘SIBER’, ‘MixSIAR’ and ‘mvabund’ packages [–]. Isotopic niche space provides a quantitative metric of expanse per trophic guild, an informative tool for defining the variability of different food webs and the b […]

call_split

Seabirds fighting for land: phenotypic consequences of breeding area constraints at a small remote archipelago

2018
Sci Rep
PMCID: 5766501
PMID: 29330422
DOI: 10.1038/s41598-017-18808-7
call_split See protocol

[…] ize category along with the pairwise overlap percentage value between ellipses. Proportions of prey contribution to the diet of each group were estimated with Bayesian mixing models as implemented in MixSIAR package. For this, isotopic ratios of the three most important prey species found in the %PSIRI analysis (see below) were used as source data, and trophic enrichment factors were 1.1 ± 0.5 for […]

Citations

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MixSIAR institution(s)
Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA; Department of Zoology, School of Natural Sciences, University of Dublin, Trinity College, Dublin, Ireland; Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA; School of Mathematics and Statistics, Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland; EcoIsoMix.com, Corvallis, OR, USA
MixSIAR funding source(s)
Supported in part by the Cooperative Institute for Marine Ecosystems and Climate (CIMEC) and the Center for the Advancement of Population Assessment Methodology (CAPAM), the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1144086.

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