Do early diagenetic processes affect the applicability of commonly-used organic matter source tracking tools? An assessment through controlled degradation end-member mixing experiments

Abstract

In the development of organic matter (OM) source tracking tools, it is critical to validate if (1) the tracers are conservative with source mixing, and (2) they can be conservative under diagenetic processes (e.g., microbial degradation). In this study, these two critical points were rigorously tested for three commonly-used source tracking tools (i.e., absorbance and fluorescence proxies, stable carbon isotopes and lipid biomarkers) via a controlled experiment at laboratory scale. To this end, two end-members (e.g., soil and algae), which represent the most common and contrasted sources of OM to sediments in an aquatic environment, were mixed in different ratios and then incubated under different oxygen conditions (oxic versus anoxic) in the dark at 25 degrees C for 60 days. The initial and final signals of the source tracking tools were analyzed and compared for each mixing ratio. Based on three evaluation criteria concerning the linearity of the relationships, discrimination sensitivity, and conservative mixing behavior, we evaluated the applicability of the tools to trace the sediment organic matter in the aquatic environment. Although most of the source tracking proxies evaluated in this study showed a conservative nature after incubation, there are only a few that demonstrated both conservative behaviors with the sources mixing and under early diagenetic processes. The fluorescence proxies such as the relative distribution of a humic-like component associated with refractory source material (Ex/Em: 220/430 nm), modified fluorescence index (YFI), humification index (HIX), and carbon stable isotope ratios were identified to be the most reliable tracers for tracking sedimentary OM sources under early diagenetic processes. This study provides strong insights into the validation of common OM source tracking tools for sediment and a reasonable guideline to select the optimum indices for source discrimination via end-member mixing analysis. (C) 2020 Elsevier Ltd. All rights reserved.