Phenolic compounds as unambiguous chemical markers for the identification of keystone plant species in the bale mountains, ethiopia

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Bruk Lemma - , Martin-Luther-Universität Halle-Wittenberg, Forest and Rangeland Biodiversity Directorate (Autor:in)
  • Claudius Grehl - , Martin-Luther-Universität Halle-Wittenberg (Autor:in)
  • Michael Zech - , Institut für Geographie, Professur für Landschaftslehre und Geoökologie, Martin-Luther-Universität Halle-Wittenberg, Technische Universität Dresden (Autor:in)
  • Betelhem Mekonnen - , Martin-Luther-Universität Halle-Wittenberg, Misrak Polytechnic College (Autor:in)
  • Wolfgang Zech - , Universität Bayreuth (Autor:in)
  • Sileshi Nemomissa - , Addis Ababa University (Autor:in)
  • Tamrat Bekele - , Addis Ababa University (Autor:in)
  • Bruno Glaser - , Martin-Luther-Universität Halle-Wittenberg (Autor:in)

Abstract

Despite the fact that the vegetation pattern and history of the Bale Mountains in Ethiopia were reconstructed using pollen, little is known about the former extent of Erica species. The main objective of the present study is to identify unambiguous chemical proxies from plant-derived phenolic compounds to characterize Erica and other keystone species. Mild alkaline CuO oxidation has been used to extract sixteen phenolic compounds. After removal of undesired impurities, individual phenols were separated by gas chromatography and were detected by mass spectrometry. While conventional phenol ratios such as syringyl vs. vanillyl and cinnamyl vs. vanillyl and hierarchical cluster analysis of phenols failed for unambiguous Erica identification, the relative abundance of coumaryl phenols (>0.20) and benzoic acids (0.05—0.12) can be used as a proxy to distinguish Erica from other plant species. Moreover, a Random Forest decision tree based on syringyl phenols, benzoic acids (>0.06), coumaryl phenols (<0.21), hydroxybenzoic acids, and vanillyl phenols (>0.3) could be established for unambiguous Erica identification. In conclusion, serious caution should be given before interpreting this calibration study in paleovegetation reconstruction in respect of degradation and underground inputs of soil organic matter.

Details

OriginalspracheEnglisch
Aufsatznummer228
FachzeitschriftPlants
Jahrgang8
Ausgabenummer7
PublikationsstatusVeröffentlicht - Juli 2019
Peer-Review-StatusJa

Externe IDs

ORCID /0000-0002-9586-0390/work/170107070

Schlagworte

Schlagwörter

  • Biomarkers, Erica, Machine learning, Oxidation, Paleoclimate, Paleovegetation, Phenols, Pollen