Abstract
Development of a model for the prediction of δ<sup>13</sup>C<sub>protein</sub> from δ<sup>13</sup>C<sub>collagen</sub> and δ<sup>13</sup>C<sub>ap-co</sub>. Model-generated values could, in turn, serve as "consumer" inputs for multi source mixture modeling of paleodiet. Linear regression analysis of previously published controlled diet data facilitated the development of a mathematical model for predicting δ<sup>13</sup>C<sub>protein</sub> (and an experimentally generated error term) from isotopic data routinely generated during the analysis of osseous remains (δ<sup>13</sup>C<sub>co</sub> and δ<sup>13</sup>C<sub>ap-co</sub>). Regression analysis resulted in a two-term linear model (δ<sup>13</sup>C<sub>protein</sub> (%) = (0.78 × δ<sup>13</sup>C<sub>co</sub> ) - (0.58× δ<sup>13</sup>C<sub>ap-co</sub>) - 4.7), possessing a high R-value of 0.93 (r(2) = 0.86, P < 0.01), and experimentally generated error terms of ±1.9% for any predicted individual value of δ<sup>13</sup>C<sub>protein</sub>. This model was tested using isotopic data from Formative Period individuals from northern Chile's Atacama Desert. 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.
