8Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany
9Institute of Geography, Chair of Physical Geography, Friedrich-Schiller University of Jena, Löbdergraben 32, D-07743 Jena, Germany
10Institute of Geography, Heisenberg Chair of Physical Geography with focus on paleoenvironmental research, Technische Universität Dresden, Helmholtzstrasse 10, D-01062 Dresden, Germany
apresent address: Chair of Geomorphology and BayCEER, University of Bayreuth, Universitätsstrasse 30, D-95440 Bayreuth, Germany
cpresent address: Institute of Geography, Chair of Physical Geography, Friedrich-Schiller University of Jena, Löbdergraben 32, D-07743 Jena, Germany
dpresent address: Institute of Geography, Heisenberg Chair of Physical Geography with focus on paleoenvironmental research, Technische Universität Dresden, Helmholtzstrasse 10, D-01062 Dresden, Germany
1Chair of Geomorphology and BayCEER, University of Bayreuth, Universitätsstrasse 30, D-95440 Bayreuth, Germany
2Institute of Agronomy and Nutritional Sciences, Soil Biogeochemistry, Martin-Luther-University Halle-Wittenberg, Von-Seckendorff-Platz 3, D-06120 Halle (Saale), Germany
3Institute of Geography, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 15, D-91058 Erlangen, Germany
4GeoBio-Center & Earth and Environmental Sciences, Ludwig-Maximilian University Munich, Richard- Wagner-Str. 10, D-80333 München, Germany
5Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059 Kraków, Poland
6Institute of Geography and Oeschger Centre for Climate Research, University of Bern, Hallerstrasse 12, CH-3012 Bern, Switzerland
8Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany
9Institute of Geography, Chair of Physical Geography, Friedrich-Schiller University of Jena, Löbdergraben 32, D-07743 Jena, Germany
10Institute of Geography, Heisenberg Chair of Physical Geography with focus on paleoenvironmental research, Technische Universität Dresden, Helmholtzstrasse 10, D-01062 Dresden, Germany
apresent address: Chair of Geomorphology and BayCEER, University of Bayreuth, Universitätsstrasse 30, D-95440 Bayreuth, Germany
cpresent address: Institute of Geography, Chair of Physical Geography, Friedrich-Schiller University of Jena, Löbdergraben 32, D-07743 Jena, Germany
dpresent address: Institute of Geography, Heisenberg Chair of Physical Geography with focus on paleoenvironmental research, Technische Universität Dresden, Helmholtzstrasse 10, D-01062 Dresden, Germany
Received: 20 Nov 2020 – Accepted for review: 17 Dec 2020 – Discussion started: 22 Dec 2020
Abstract. The hydrogen isotopic composition of leaf wax-derived biomarkers, e.g. long chain n-alkanes (δ2Hn-alkane), is widely applied in paleoclimatology research. However, a direct reconstruction of the isotopic composition of source water based on δ2Hn-alkane alone can be challenging due to the alteration of the soil water isotopic signal by leaf-water heavy-isotope enrichment. The coupling of δ2Hn-alkane with δ18O of hemicellulose-derived sugars (δ18Osugar) has the potential to disentangle this effect and additionally to allow relative humidity reconstructions. Here, we present δ2Hn-alkane as well as δ18Osugar results obtained from leaves of the plant species Eucalyptus globulus, Vicia faba var. minor and Brassica oleracea var. medullosa, which grew under controlled conditions. We addressed the questions (i) do δ2Hn-alkane and δ18Osugar values allow precise reconstructions of leaf water isotope composition, (ii) how accurately does the reconstructed leaf-water-isotope composition enables relative humidity (RH) reconstruction in which the plants grew, and (iii) does the coupling of δ2Hn-alkane and δ18Osugar enable a robust source water calculation?
For all investigated species, the alkane n-C29 was most abundant and therefore used for compound-specific δ2H measurements. For Vicia faba, additionally the δ2H values of n-C31 could be evaluated robustly. With regard to hemicellulose-derived monosaccharides, arabinose and xylose were most abundant and their δ18O values were therefore used to calculate weighted mean leaf δ18Osugar values. Both δ2Hn-alkane and δ18Osugar yielded significant correlations with δ2Hleaf-water and δ18Oleaf-water, respectively (r2 = 0.45 and 0.85, respectively; p < 0.001, n = 24). Mean fractionation factors between biomarkers and leaf water were found to be −156 ‰ (ranging from −133 to −192 ‰) for εn-alkane/leaf-water and +27.3 ‰ (ranging from +23.0 to 32.3 ‰) for εsugar/leaf-water, respectively. Modelled RHair values from a Craig-Gordon model using measured Tair, δ2Hleaf-water and δ18Oleaf-water as input correlate highly significantly with measured RHair values (R2 = 0.84, p < 0.001, RMSE = 6 %). When coupling δ2Hn-alkane and δ18Osugar values the correlation of modelled RHair values with measured RHair values is weaker but still highly significant with R2 = 0.54 (p < 0.001, RMSE = 10 %). Finally, the reconstructed source water isotope composition (δ2Hs and δ18Os) as calculated from the coupled approach matches the source water in the climate chamber experiment (δ2Htank-water and δ18Otank-water). This highlights the great potential of the coupled δ2Hn-alkane-δ18Osugar paleohygrometer approach for paleoclimate and relative humidity reconstructions.