Reconstructing relative humidity from plant δ18O and δD as deuterium deviations from the global meteoric water line

Authors


  • Corresponding Editor (ad hoc): B. R. Helliker.

Abstract

Cellulose δ18O and δD can provide insights on climates and hydrological cycling in the distant past and how these factors differ spatially. However, most studies of plant cellulose have used only one isotope, most commonly δ18O, resulting in difficulties partitioning variation in δ18O of precipitation vs. evaporative conditions that affect leaf water isotopic enrichment. Moreover, observations of pronounced diurnal differences from conventional steady-state model predictions of leaf water isotopic fractionation have cast some doubt on single isotope modeling approaches for separating precipitation and evaporation drivers of cellulose δ18O or δD. We explore a dual isotope approach akin to the concept of deuterium-excess (d), to establish deuterium deviations from the global meteoric water line in leaf water (Δdl) as driven by relative humidity (RH). To demonstrate this concept, we survey studies of leaf water δ18O and δD in hardwood vs. conifer trees. We then apply the concept to cellulose δ18O and δD using a mechanistic model of cellulose δ18O and δD to reconstruct deuterium deviations from the global meteoric water line (Δdc) in Quercus macrocarpa, Q. robur, and Pseudotsuga menziesii. For each species, Δdc showed strong correlations with RH across sites. Δdc agreed well with steady-state predictions for Q. macrocarpa, while for Q. robur, the relationship with RH was steeper than expected. The slope of Δdc vs. RH of P. menziesii was also close to steady-state predictions, but Δdc were more enriched than predicted. This is in agreement with our leaf water survey showing conifer Δdl was more enriched than predicted. Our data reveal that applications of this method should be appropriate for reconstructing RH from cellulose δ18O and δD after accounting for differences between hardwoods and conifers. Hence, Δdc should be useful for understanding variability in RH associated with past climatic cycles, across regional climates, or across complex terrain where climate modeling is challenging. Furthermore, Δdc and inferred RH values should help in constraining variation in source water δ18O.

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