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UNCERTAINTY IN SOURCE PARTITIONING USING STABLE ISOTOPES
Citation:
Phillips, D L. AND J W. Gregg. UNCERTAINTY IN SOURCE PARTITIONING USING STABLE ISOTOPES. OECOLOGIA. Springer-Verlag, New York, NY, 127:171-179, (2001).
Description:
Stable isotope analyses are often used to quantify the contribution of multiple sources to a mixture, such as proportions of food sources in an animal's diet, C3 vs. C4 plant inputs to soil organic carbon, etc. Linear mixing models can be used to partition two sources with a single isotopic signature (e.g., 13C) or three sources with a second isotopic signature (e.g. 15N). Although variability of source and mixture signatures are often reported, confidence interval calculations for source proportions typically use only the mixture variability. We provide examples showing that omission of source variability can lead to underestimation of the variability of source proportion estimates. For both two and three source mixing models, we present formulas for calculating variances, standard errors (SE), and confidence intevals for source proportion estimates that account for the observed variability in the isotopic signatures for the sources as well as the mixture. We then performed sensitivity analyses to assess the relative importance of (a) the isotopic signature difference between the sources, (b) isotopic signature standard deviations (SD) in the source and mixture populations, (c) sample size, (d) analytical SD, and (e) the evenness of the source proportions, for determining the variability (SE) of source proportion estimates. The proportion SE's varied inversely with the signature difference btween sources, so doubling the source difference 2% to 4% reduced the SE's by half. Source and mixture signature SD's had a substantial linear effect on source proportion SE's. However, the proportion variability of the sources and the mixture are fixed and the sampling error component can be changed only by increasing sample size. Source proportion SE's varied inversely with the square root of sample size, so an increase from 1 to 4 samples per population cut the SE in half. Analytical SD had little effect over the range examined since it was generally substantially