T12 Advances in Using Sedimentary Data to Constrain the Timing and Rates of Geologic Events and Processes I

Sunday, 22 September 2019
8:00 AM - 12:00 PM
Room 222BC, North Building

CHEMOSTRATIGRAPHIC CORRELATION FROM A REPRODUCIBLE DYNAMIC PROGRAMMING ALGORITHM

Paper number: T12-7
Program: Technical Sessions
Time: 9:20 AM – 9:35 AM

Authors

Abstract

Dynamic programming algorithms objectively align time-series of Plio–Pleistocene paleoclimate data subject to uncertainties in temporal overlap and relative accumulation (e.g., Lisiecki and Lisiecki, 2002; Channell et al., 2009); applications of this technique to pre-Cenozoic correlation problems are more limited (Sadler, 2004). We describe a dynamic programming method for obtaining least-squares optimal alignments between chemostratigraphic records (here δ13Ccarbonate ) for the purpose of extrapolating an age model developed at a radiometrically calibrated stratigraphic section to one lacking an absolute chronology (see Hay et al., Geology, 2019, for the open-source algorithm). For case studies undertaken to date, including Cambrian Series 1–2 δ13Ccarb records (Maloof et al., 2010), dynamic programming produces a library of plausible δ13Ccarb alignments arising from various assumptions about the insertion of depositional hiatuses and the total temporal overlap of the two records (Hay et al, 2019). Since each dynamic programming-determined δ13Ccarb alignment produces a sub-variant on the reference age model, this method commonly yields a range of plausible ages for a reference event (datum), such as a fossil first/last appearance or the age of a stratigraphic bed/surface, or rates of geologic processes. As such, geological ages (or rates) derived from dynamic programming algorithms should be reported as a confidence interval.

Geological Society of America Abstracts with Programs. Vol. 51, No. 5

doi: 10.1130/abs/2019AM-337753

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