Preprints
https://doi.org/10.5194/egusphere-2022-23
https://doi.org/10.5194/egusphere-2022-23
 
04 Mar 2022
04 Mar 2022

Vegetation reconstruction using plant wax n-alkane chain length distribution and δ13C of multiple chains: A multi-source mixing model using Bayesian framework

Deming Yang and Gabriel Bowen Deming Yang and Gabriel Bowen
  • Department of Geology and Geophysics, University of Utah, Salt Lake City, UT 84112, United States

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.

Deming Yang and Gabriel Bowen

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-23', Anonymous Referee #1, 20 Apr 2022
    • AC1: 'Reply on RC1', Deming Yang, 31 May 2022
  • RC2: 'Comment on egusphere-2022-23', Anonymous Referee #2, 11 Jul 2022
    • AC2: 'Reply on RC2', Deming Yang, 13 Jul 2022
      • RC3: 'Reply on AC2', Anonymous Referee #2, 14 Jul 2022
        • AC3: 'Reply on RC3', Deming Yang, 14 Jul 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-23', Anonymous Referee #1, 20 Apr 2022
    • AC1: 'Reply on RC1', Deming Yang, 31 May 2022
  • RC2: 'Comment on egusphere-2022-23', Anonymous Referee #2, 11 Jul 2022
    • AC2: 'Reply on RC2', Deming Yang, 13 Jul 2022
      • RC3: 'Reply on AC2', Anonymous Referee #2, 14 Jul 2022
        • AC3: 'Reply on RC3', Deming Yang, 14 Jul 2022

Deming Yang and Gabriel Bowen

Model code and software

SPATIAL-Lab/LipidMM: Arugula Deming Yang https://doi.org/10.5281/zenodo.6236846

Deming Yang and Gabriel Bowen

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Short summary
Plant wax lipid ratios and their isotopes are used in vegetation reconstruction. While studies often use either the ratios or the isotopes, both can inform the mixing pattern of source plants. We developed a statistic model that evaluates both lines of evidence together. Through case studies, we showed that the approach allows more detailed interpretations of vegetation composition than traditional methods. This evolving framework can include more geochemical tracers to inform paleoclimate.