Technical note: A linear model for predicting δ13Cprotein

Objective : Development of a model for the prediction of δ¹³C_protein from δ¹³C_collagen and Δ¹³C_ap‐co. Model‐generated values could, in turn, serve as “consumer” inputs for multisource mixture modeling of paleodiet. Methods : Linear regression analysis of previously published controlled diet data facilitated the development of a mathematical model for predicting δ¹³C_protein (and an experimentally generated error term) from isotopic data routinely generated during the analysis of osseous remains (δ¹³C_co and Δ¹³C_ap‐co). Results : Regression analysis resulted in a two‐term linear model (δ¹³C_protein (%) = (0.78 × δ¹³C_co) ? (0.58× Δ¹³C_ap‐co) ? 4.7), possessing a high R‐value of 0.93 (r² = 0.86, P < 0.01), and experimentally generated error terms of ±1.9% for any predicted individual value of δ¹³C_protein. This model was tested using isotopic data from Formative Period individuals from northern Chile's Atacama Desert. Conclusions : The model presented here appears to hold significant potential for the prediction of the carbon isotope signature of dietary protein using only such data as is routinely generated in the course of stable isotope analysis of human osseous remains. These predicted values are ideal for use in multisource mixture modeling of dietary protein source contribution. Am J Phys Anthropol 157:694–703, 2015. © 2015 Wiley Periodicals, Inc.