SIAR - Stable Isotope Analysis in R
Parnell, A.C., Inger R., Bearhop, S. & Jackson, A.L. 2010. Source partioning using stable isotopes: coping with too much variation. PLoS ONE, 5(3), e9672 . doi
Collaborators: Andrew Jackson, Trinity College Dublin, Andrew Parnell, Dept of Statistics, University College Dublin; Richard Inger and Stuart Bearhop, School of Biosciences, University of Exeter, Tremough Campus, UK.
We have developed a freeware package that runs in the R statistical computing environment called SIAR for solving linear mixing models - specifically, but not exclusively, aimed at inferring diet composition from stable isotope analysis in consumers and their food sources. SIAR can be downloaded free, and so too can R. I have several video podcasts for people new to R that might help you get up to speed. A specific series of podcasts for the mixing models in SIAR are available, along with some podcasts supporting the SIBER functions.
Note that siar is no longer compatible with cran requirements and it should be installed from github and not from cran. We are phasing out its use for mixing models. SIAR will always be available at the new github SIAR development page and updates on progress can be found there and on the Facebook page. The mixing model functionality in SIAR is superceded by MixSIAR and a lighter implementation of mixing models in simmr.
This package uses Bayesian Inference to solve for the most likely set of dietary proportions given the isotopic ratios in a set of possible food sources and a set of consumers. The model is similar in principle to IsoSource (Phillips & Gregg 2003) but allows all sources of uncertainty such as in the sources or trophic fractionation values to be propagated through the model to return a true probability distribution of estimated dietary proportions. Previously it was necessary to ignore variation and uncertainty and work only with mean estimates of isotope ratios.
The maths underlying SIAR can be found published in Jackson et al. (2009) and Moore and Semmens (2008). Work is on-going to add further functionality to this model with the aim being to develop a complete analysis suite for isotope ecology.
Some files available that might be of use in learning and applying SIAR
- Podcasts for SIAR
- An extensive workbook called "SIAR for Ecologists" written by Richard Inger runs through the main details of getting the package working on your own data
- A range of example scripts for SIAR including how to aggregate sources a posteriori and how to use siarelicit() to generate informative priors among other examples are available from github (although I admit these are not very well curated in this repository: see the folder siar-mixing-models for more information).
- Podcasts for SIBER
- Example scripts and analyses for SIBER are available as vignettes installed as part of the package.
When citing SIAR please refer to this paper: Parnell, A.C., Inger R., Bearhop, S. & Jackson, A.L. 2010. Source partioning using stable isotopes: coping with too much variation. PLoS ONE, 5(3), e9672 . doi
Figure 1. Sample data provided as a demo within SIAR representing the 4 possible food sources of Brent Geese in Ireland with variation indicated by the horizontal and vertical lines (data taken from a previous IsoSource analysis - Inger et al. 2006). The isotopic ratios of the geese's blood plasma are plotted in grey - 8 different groups representing trappings from 8 different time points across 2 seasons.
It is clear from Figure 1 that the diet changes between groups, i.e. over time. SIAR returns true probability estimates for the likely proportion of each source in the diet.
Figure 2. The estimated proportion of Zostera in the diet across the 8 groups changes dramatically over time. Groups 1 and 4 represent the first sampling time point after their arrival in Ireland.
References:
Inger R., Ruxton G.D., Newton J., Colhoun K., Robinson J.A., Jackson A.L. & Bearhop S. (2006) Temporal and intra-population variation in prey choice of wintering geese determined by stable isotope analysis. Journal of Animal Ecology 75(5), 1190-1200, doi
Jackson, A.L., Inger, R., Bearhop, S. & Parnell, A. 2009. Erroneous behaviour of MixSIR, a recently published Bayesian isotope mixing model: a discussion of Moore & Semmens, Ecology Letters, 2008. Ecology Letters, 12, E1-E5. doi
Jackson, A.L., Parnell, A.C., Inger R., & Bearhop, S. 2011. Comparing isotopic niche widths among and within communities: SIBER – Stable Isotope Bayesian Ellipses in R. Journal of Animal Ecology, 80, 595-602. doi
Moore J.W. & Semmens B.X. (2008) Incorporating uncertainty and prior information into stable isotope mixing models. Ecology Letters, 11, doi
Parnell, A.C., Inger R., Bearhop, S. & Jackson, A.L. 2010. Source partioning using stable isotopes: coping with too much variation. PLoS ONE, 5(3), e9672 . doi
Phillips D.L. & Gregg J.W. (2003) Source partitioning using stable isotopes: coping with too many sources. Oecologia, 136, 261-269, doi