SIAR

The SIAR Package

SIAR is an R package that is based around two main Bayesian statistical methods commonly employed in stable isotope ecology: a mixing model for determining the proportional contribution of sources to a mixture (e.g. proportion of food in a consumer's diet); and quantitative tools for comparing dispersion in isotope-space.

The mixing model component of SIAR is described in 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. Learning resources including podcasts are available for the mixing model component of SIAR.

The tools for comparing variation within and among groups of isotope-space data are described in 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. Learning resources including podcasts are available for the SIBER component of SIAR.

Development of SIAR as a package is mostly restricted to keeping up to date with changes in R, bug fixes and minor improvements to code. The development of a generalised framework for fitting mixing models incluing random effects and linear covariates has moved to MixSIAR in collaboration with Jonathan Moore, Donald Phillips, Brice Semmens, Brian Stock and Eric Ward. Development of SIBER is in the process of moving to a standalone package.

Warning!

I implore everyone planning a study using isotopes for mixing model type analysis to read the original IsoSource paper and our Best practices for use of stable isotope mixing models in food web studies in that order, BEFORE collecting the data, and AGAIN before the analysis... and maybe AGAIN afterwards!

Isotopes are not a magic bullet for determining or comparing diets (either using mixing models or SIBER), and your studies need to be carefully designed and executed if they are to be of use. As is often the case with ecology, you also need a little luck in there too in terms of the geometry of your system in isotope space, which impacts on the mathematical and statistical power you will have to answer your questions.

Authors and Contributors

SIAR was developed by Andrew Parnell, Andrew Jackson, Richard Inger and Stuart Bearhop.

Support or Contact

Having trouble with SIAR? Check out the learning resources pages for SIAR and SIBER. Bugs and suggestions should be left as issues on the main SIAR development page. or contact Andrew Jackson or Andrew Parnell and we will try to help you out.