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Published July 2020 | Supplemental Material + Published
Journal Article Open

Ooid Cortical Stratigraphy Reveals Common Histories of Individual Co-occurring Sedimentary Grains

Abstract

Ooids are a common type of carbonate sand grain that form through a combination of constructive and destructive mechanisms: growth via precipitation and diminution via physical abrasion. Because growth and abrasion obey distinct morphometric rules, we developed an approach to quantitatively constrain the history of growth and abrasion of individual ooid grains using the record of evolving particle shape preserved by their cortical layers. We designed a model to simulate >10⁶ possible growth‐abrasion histories for each pair of cortical layer bounding surfaces in an individual ooid. Estimates for the durations of growth and abrasion of each cortical layer were obtained by identifying the simulated history that best fit the observed particle shape. We applied this approach to thin sections of "modern" lacustrine ooids collected from several locations in the Great Salt Lake (GSL), UT, to assess the spatial and temporal variability of environmental conditions from the perspective of individual grains within a single deposit. We found that GSL ooids do not all share the same histories: Clustering ooid histories by a Fréchet distance metric revealed commonalities between grains found together locally within a deposit but distinct differences between subpopulations shared among localities across the GSL. These results support the tacit view that carbonate sedimentary grains found together in the environment do reflect a common history of sediment transport. This general approach to invert ooid cortical stratigraphy can be applied to characterize environmental variability over <1,000 year timescales in both marine and lacustrine ooid grainstones of any geologic age.

Additional Information

© 2020 American Geophysical Union. Received 26 NOV 2019; Accepted 26 MAY 2020. We thank A. Sipos and D. Sumner for constructive reviews that improved the manuscript. E. J. T. acknowledges support from the Agouron Institute Geobiology Postdoctoral Fellowship and NSF EAR Award 1826850. This study was made possible in part due to the data made available by the governmental agencies, commercial firms, and educational institutions participating in MesoWest. W. W. F. acknowledges the support of American Chemical Society Petroleum Research Fund Grant 56757‐ND8 and Caltech RI². Data Availability Statement: Individual ooid images, cortical layer boundary vectors, best fit model cortical layer boundary vectors, and full Fréchet distance matrix are archived at: http://doi.org/10.17605/OSF.IO/DSPRH. Matlab code designed to aid in identification of cortical layer boundaries from thin section images, run growth‐abrasion simulations and identify best fit histories, and plot model outputs (overlays over thin section images, growth‐abrasion stair‐step plots) are archived at http://doi.org/10.5281/zenodo.3547886.

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Published - 2019JF005452.pdf

Supplemental Material - jgrf21211-sup-0001-figure_si-s01.docx

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Created:
August 22, 2023
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