Large variability in n-alkane δ13C values in Lake Pa Kho (Thailand) driven by wetland wetness and aquatic productivity

Abstract

Understanding past climate and environmental conditions depends largely on accurate interpretations of proxy records from a range of environments, including tropical wetlands and lakes. Lipid biomarker analysis can provide important information about the sources of the accumulated organic material, and thus about the environmental information contained therein. Here we use n-alkane distributions and stable carbon isotopes of leaf waxes (δ13Cwax) to identify the sources of organic matter (OM) of a 2000-year long sediment/peat record from Lake Pa Kho (LPK) in northeastern Thailand, and to constrain the mechanisms that cause shifts in δ13Cwax and in δ13C of bulk organic matter (δ13Cbulk). Our results show three main sources of OM: terrestrial plants, aquatic macrophytes and algae. The δ13C values of the long chain n-alkanes, show two distinct groups: C27–C31 and C33–C35n-alkanes, where the δ13C values of C33–C35n-alkanes reflect that of δ13Cbulk. Lower moisture availability on the wetland, known from other sedimentary evidence, was characterized by low carbon isotope values typically seen for C3 plants, whereas greater moisture availability corresponded to higher δ13C values (around −20‰) of C33–C35n-alkanes, resembling a typical C4 plant signal. However, various lines of evidence argue against large shifts between C3 and C4 plant input. Instead, we suggest that the high δ13C values were indirectly caused by higher aquatic productivity during periods of greater moisture availability, decreasing dissolved CO2, but increasing bicarbonate availability caused by higher pH. This caused the dominant macrophytes (e.g., Potamogeton spp.) to shift their carbon source from CO2 to bicarbonate, which has much higher δ13C values. Our results show that the environmental context should be taken into account when interpreting n-alkane δ13C variability as a paleo-environmental/climatic signal as this contains several important variables that need to be disentangled and explained.