LAUSR

Abstract Amazon rivers and flooded areas can be categorized into three types of water: white, black, and clear. These categories present unique physical–chemical characteristics that influence the characteristics and distribution of sedimentary organic matter (SOM). A geochemical assessment of the short sedimentary cores of four floodplain lakes within the Brazilian Amazon basin was performed. Two black, one white, and one clear-water floodplain lakes were selected to evaluate the variability of OM composition based on aliphatic biomarker and carbon isotopic ratios, as proxies for an enhanced methane cycle, anoxia, and to determine the origin of predominant aliphatic biomass. Gas chromatography was coupled to flame ionization detection (GC–FID), mass spectrometry (GC–MS) and combustion-isotope ratio mass spectrometry (GC–C–IRMS). These were used to determine aliphatic biomarker ratios, for quantification, and to measure carbon isotopic compositions. The TOC content was inversely proportional to the expected OM productivity; one black water (low OM productivity) presented the highest TOC content, and white water (high productivity) presented the lowest. Also, clear water lake (intermediate productivity) presented TOC content between the other lakes. Based on n-alkane proxies and profiles, as well as bacterial and plant-derivative terpene distribution, we observed a mostly terrigenous contribution for the black and clear water lakes (allochthonous SOM), as well as a prevalence of aquatic organisms in white water lake (autochthonous SOM). Only in the most superficial section of the white water lake, was intense OM degradation substantiated with n-alkanes showing an even-short-chain predominance, indicative of OM cycling. Also, for one black water lake, we detected depleted n-alkane and diploptene δ13C values (–42‰) associated with methanotrophic archaea and higher relative concentrations of des-A-triterpenes commonly associated with anoxic sedimentation. Based on these data, the influence of water-type on the SOM composition was verified. The approach helps to understand the application of n-alkane proxies to differentiate Amazonian environments.