You are here:
INCORPORATING CONCENTRATION DEPENDENCE IN STABLE ISOTOPE MIXING MODELS
Citation:
Phillips, D L. AND P. L. Koch. INCORPORATING CONCENTRATION DEPENDENCE IN STABLE ISOTOPE MIXING MODELS. Presented at Ecological Society of America 2001 meeting, Madison, WI, August 5-8, 2001.
Description:
Stable isotopes are frequently used to quantify the contributions of multiple sources to a mixture; e.g., C and N isotopic signatures can be used to determine the fraction of three food sources in a consumer's diet. The standard dual isotope, three source linear mixing model assumes that the proportional contribution of a source to a mixture is the same for both elements (e.g., C, N). This may be a reasonable assumption if the concentrations, or at least the concentration ratios (e.g., C:N) are similar among all sources. However, frequently one source is particularly rich or poor in one element (e.g., N), which would logically lead to a proportionate increase or decrease in the contribution of that source to the mixture for that element relative to the other element (e.g., C). We have developed a concentration-weighted linear mixing model, which assumes that for each element, a source's contribution is proportional to the contributed mass times the elemental concentration in that source. The model is outlined for two elements and three sources, but can be generalized to n elements and n + 1 sources. Sensitivity analyses for C and N in three sources indicated that varying just the N concentration of one source had substantial and differing effects on the estimated source contributions of mass, C, and N. The same was true for a case study of bears feeding on salmon, moose, and N-poor plants, in which the estimated biomass contribution of salmon was markedly less than the standard model estimated. Application of the model to a captive feeding study of mink fed on salmon, lean beef, and C-rich, N-poor beef fat reproduced very closely the known dietary proportions, whereas the standard model was unable to determine a set of positive source proportions. Use of this concentration-weighted model is recommended whenever the elemental concentrations vary substantially among the sources.