Integrating plant wax abundance and isotopes for paleo-vegetation and paleoclimate reconstructions: a multi-source mixing model using a Bayesian framework

Abstract. Plant wax n-alkane chain length distribution and isotopes have been studied in modern ecosystems as proxies to reconstruct vegetation climate of the past. However, most paleo-proxies focus on either concentrations or isotopes, whereas both carry complementary information mixing sources. We propose a multi-source model Bayesian framework that evaluates distributions simultaneously. The consists priors include user-defined source groups their associated parametric concentration δ13C. process involves newly defined fractions such fractional leaf mass contribution (FLMC) can be used reconstruction. Markov Chain Monte Carlo is generate samples from posterior these parameters conditioned data types. present three case studies distinct settings. first n-C27, n-C29, n-C31 alkanes lake surface sediments Lake Qinghai, China. provides more specific interpretations input aquatic sources than conventional Paq proxy. second n-C31, n-C33 Cameroon, western Africa. produces forest C3, savanna C4 plants, offering additional dominant biomes compared traditional two-end-member regime. third couples hydrogen isotope component, using biome-specific apparent fractionation factors (εa) estimate δ2H mean annual precipitation. By leveraging distribution, δ13C, four chains, estimated precipitation with relatively small uncertainty limits. new shows promise for interpretation paleo-data but could further improved by including processes turnover transport, integration into sedimentary archives. Future plants catchment systems will critical develop calibration datasets advance strength utility framework.