Reply on RC1

Abstract

Plant wax n-alkane chain length distribution and δ13C have been studied in modern ecosystems as proxies to reconstruct vegetation and climate of the past. Studies on modern plants often report both chain-specific n-alkane concentrations and δ13C values. However, studies on geological archives interpret only one proxy, while both carry crucial information on the mixing sources. We propose a multi-source mixing model in a Bayesian framework that evaluates both proxies simultaneously. The model consists of priors that include user-defined source groups and their associated parametric distributions of n-alkane concentration and δ13C with well characterized uncertainties. The mixing process involves newly defined mixing fractions such as fractional leaf mass contribution (FLMC) that can be used in vegetation reconstruction, and fractional source contribution to a specific n-alkane homologue (FSCn). Markov Chain Monte Carlo is used to generate samples from the posterior distribution conditioned on both proxies. We present two case studies with distinct sets of priors. One involves n-C27, n-C29 and n-C31 alkanes in lake surface sediments of Lake Qinghai, China. The model provides more specific interpretations on the n-alkane input from aquatic sources than the conventional Paq proxy. The other involves n-C29, n-C31 and n-C33 alkanes in lake surface sediments in Cameroon, western Africa. The model produces mixing fractions of forest C3, savanna C3, and C4 plants, offering additional information on the dominant biomes compared to the traditional two-endmember mixing regime. FSCn can be used to assess the interpretation of associated n-alkane δ2H values, and future versions of the model incorporating lipid H isotope systematics could support integration of this proxy with C isotope and chain length distribution data. Despite the achievements, processes associated with n-alkane integration into sedimentary archives have not been incorporated, and the model could be further improved by adding components such as n-alkane turnover and transportation. Future studies on modern plants and catchment systems will be critical to develop calibration datasets that advance the strength and utility of the framework.