title: Improving Bayesian isotope mixing models: a response to Jackson et al. (2009).
abstract: We recently described a Bayesian framework for stable isotope mixing models and provided a software tool, MixSIR, for conducting such analyses (Ecol. Lett., 2008; 11:470). Jackson et al. (Ecol. Lett., 2009; 12:E1) criticized the performance of our software based on tests using simulated data. However, their simulation data were flawed, rendering claims of erroneous behaviour inaccurate. A re-evaluation of the MixSIR source code did, however, uncover two minor coding errors, which we have fixed. When data are correctly simulated according to eqns (1)-(4) in Jackson et al. (2009), MixSIR consistently and accurately estimated the proportional contribution of prey to a predator diet, and was surprisingly robust to additional unquantified error. Jackson et al. (2009) also suggested we use a Dirichlet prior on the source proportion parameters, which we agree with. Finally, Jackson et al. (2009) propose adding additional error parameters to our mixing model framework. We caution that such increases in model complexity should be evaluated based on data support.
authors.affiliation: Northwest Fisheries Science Center, National Marine Fisheries Service, Seattle, WA 98112, USA. brice.semmens@noaa.gov
authors.forename: Brice X
authors.initials: BX
authors.lastname: Semmens
authors.forename: Jonathan W
authors.initials: JW
authors.lastname: Moore
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Ward
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D003198:Computer Simulation; D004032:Diet; D020387:Food Chain; D005518:Food Preferences; D007554:Isotopes / Q000378:metabolism*; D008954:Models, Biological; D015233:Models, Statistical; D012680:Sensitivity and Specificity; D012984:Software
chemical_list: D007554:Isotopes