Expressing biomarker data in stoichiometric terms: shifts in distribution and biogeochemical interpretation

Abstract

Quantitative biomarker analysis is an invaluable tool used routinely by organic geochemists to interpret and explain environmental processes. Since the advent of organic geochemistry, all levels of biomarker methodology from wet chemistry to data interpretation have significantly advanced; however, an important aspect of data analysis has remained constant and that is the expression of biomarkers in terms of mass (e.g., mg gOC−1). We argue that biomarkers are more appropriately expressed in terms of moles (e.g., mmol molOC−1) to better reflect molecular‐level distribution of compounds of interest, as well as introducing a chemical consistency for better comparability and transferability between data sets. Using modeled and real data culled from the literature, we demonstrate that the use of moles is not a trivial conversion and that distribution and relative weighting of biomarker data sets are shifted and affect the total data structure. The shift is sometimes strong enough to exert changes in interpretation (e.g., microbial abundance in an estuarine system), alter proxies (e.g., terrestrial‐to‐aquatic ratio), and potentially influence the use of multivariate statistical methods (e.g., principal components analysis).