Trinity College Dublin

Skip to main content.

Top Level TCD Links

Complex Ecological and Evolutionary Systems

Home | Research group | Opportunities | Publications | Projects | Outreach | EcoEvo@TCD blog
SIAR Stable Isotope Ecology in R

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 owing to some new and quite restrictive requirements put on package structures by CRAN, SIAR is likely to be not available in future updates until we can implement the changes (more information at https://github.com/AndrewLJackson/siar). I have downloaded snapshots of the binaries for windows, snow leopard and mavericks as of 05/01/2015. 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.

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.

Additionally, SIAR will take account of a grouping structure and directly compare the estimated diets between groups of individuals. These groups could represent multiple observations on the same individual, sub-populations or entire species.

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

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.

bi-plot of geese isotope data

 

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 drammatically over time. Groups 1 and 4 represent the first sampling time point after their arrival in Ireland.

proportion of zostera consumed over time

 

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

 

 


Last updated 10 August 2017 by SHASSETT@tcd.ie.