Calibration chain transformation improves the comparability of organic hydrogen and oxygen stable isotope data. Issue 4 (7th February 2021)

• Record Type: Journal Article
• Authors: Magozzi, Sarah; Bataille, Clement P.; Hobson, Keith A.; Wunder, Michael B.; Howa, John D.; Contina, Andrea; Vander Zanden, Hannah B.; Bowen, Gabriel J.
• Editors: Soto, David
• Is Part Of: Methods in ecology and evolution. Volume 12:Issue 4(2021)
• Page Start: 732
• Page End: 747
• Publication Date: 2021-02-07
• Subjects: calibration -- comparative equilibration -- database -- isotopic exchange -- keratin -- known‐origin -- reference materials -- standards; Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.13556
• Languages: English
• ISSNs: 2041-210X

Abstract

Abstract: Stable hydrogen and oxygen isotopic compositions (δ 2 H and δ 18 O, respectively) of animal tissues have been used to infer geographical origin or mobility based on the premise that the isotopic composition of tissue is systematically related to that of local water sources. Isotopic data for known‐origin samples are required to quantify these tissue–environment relationships. Although many of such data have been published and could be reused by researchers, differences in the standards used for calibration and analytical procedures for different datasets limit the comparability of these data. We develop an algorithm that uses results from comparative analysis of secondary standards to transform data among reference scales and estimate the uncertainty inherent in these transformations. We apply the algorithm to a compilation of known‐origin keratin data published over the past ~20 years. We show that transformation improves the comparability of data from different laboratories, and that the transformed data suggest ecophysiologically meaningful differences in keratin–water relationships among different animal groups and taxa. The compiled data and algorithms are freely available in the ASSIGNR r ‐package to support geographical provenance research, and more generally offer a methodology overcoming several challenges in geochemical data integration and reuse.