期刊
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
卷 124, 期 7, 页码 2107-2125出版社
AMER GEOPHYSICAL UNION
DOI: 10.1029/2018JG004708
关键词
leaf waxes; proxy system models; paleoclimate; data-model comparison; hydrogen isotopes; biomarkers
资金
- NSF AGS-PRF award [1433408]
- NSF-P2C2 award [1502806]
- University of Texas at Austin, Institute for Geophysics Postdoctoral Fellowship
The D/H ratio of epicuticular plant waxes (delta D-wax) preserved in sedimentary archives is a powerful tool for paleoclimate reconstruction, but comparisons to other proxy records or to climate model simulations requires a proxy system model (PSM) that accounts for transformations between delta D-precip and delta D-wax. Here we present a new, publicly available PSM for plant waxes, WaxPSM. WaxPSM predicts delta D-wax from observational data or any isotope-enabled modern, paleo, or future climate model experiment. delta D values of the C-29 n-alkane are calculated based on precipitation or soil water delta D and observed apparent fractionation values, adjusted for plant-type differences. Using WaxPSM, we assess three key uncertainties in delta D-wax records: the degree to which variations in delta D may reflect changes in vegetation rather than climate, structural uncertainties that arise from limited water isotopic observations, and the impacts of land cover change on climate reconstructions during the Last Glacial Maximum and the Preindustrial period. Parametric and structural uncertainties can cause delta D-wax variations up to 50 parts per thousand, but in most cases, the differences are similar to 10-30 parts per thousand. The drier subtropics are additionally impacted by the incorrect structural assumption that plants' source water, delta D-soil, is isotopically similar to the climate variable of interest, delta D-precip. We recommend a coordinated, systematic effort to elevate observational constraints on delta D-precip, delta D-soil, and the delta D of multiple compound classes, which would dramatically reduce parametric and structural uncertainties and allow further complexity to be built into the model.
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