Joint 56th Annual North-Central/ 71st Annual Southeastern Section Meeting - 2022

Paper No. 2-11
Presentation Time: 10:50 AM


LUKENS, William, Department of Geology and Environmental Science, James Madison University, Harrisonburg, VA 22807-1004 and FOX, David L., Department of Earth Sciences, University of Minnesota, Minneapolis, MN 55455

The Neogene C3-C4 transition is one of the most profound ecological reorganization in the Cenozoic Era. The causes behind C4 plant proliferation remain actively debated, but are likely due to combined effects from climate, biogeography, and ecological processes. Nearly all modern trees, shrubs, and cool-growing-season gasses use the C3 (Calvin cycle) photosynthetic pathway to fix atmospheric CO2, which strongly favors 12C over 13C and results in very low δ13C values of plant tissue. In contrast, modern warm-growing season grasses use C4 (Hatch-Slack) photosynthesis, which has a lower discrimination against 13C and results in plant tissues with higher δ13C values. Because the C4 pathway is advantageous in times of low atmospheric pCO2 and conditions of water stress, the relative proportion of C3 to C4 biomass from past landscapes is widely used as a paleoclimate proxy. Current methods used to estimate the fraction of C4 biomass (fC4) from pedogenic archives involve calculating simple linear mass-balance from representative endmember δ13C values for C3 and C4 plants, but this technique lacks robust uncertainty analysis. We developed a Monte Carlo resampling approach in order to incorporate uncertainties in calculating fC4 from paleosols. This method includes realistic C3 and C4 plant δ13C distributions based on modern plants, uncertainty in past atmospheric CO2 δ13C value, variation within measured substrates, uncertainty in temperature-dependent 13C/12C fractionation during carbonate precipitation, and laboratory analysis uncertainty. Applying this approach on paleosols from Miocene paleosols in North America and eastern Africa resulted in very large but realistic uncertainties in fC4 estimates, despite efforts to cull input data based on a priori estimates of past rainfall levels. We argue that the Monte Carlo approach is an improved method for reporting fC4 from paleosol substrates and will help to guide ongoing work seeking to improve paleovegetation reconstructions.