AUTOMATED SEQUENCING OF THE FOSSIL RECORD: IMPROVED METHODS AND INSIGHTS FROM MOHAWKIAN (ORDOVICIAN) GEOCHRONOLOGY, TEPHROCHRONOLOGY, AND BIOSTRATIGRAPHY

Time slices from the Taconic magmatic arc, across the ancient Appalachian basin, and into the cratonic interior provide a framework within which to connect events at the plate margin with consequences in the plate interior and thereby, to investigate both the history of these regions and the processes that link them. The construction of such time slices requires the integration of data from traditional biostratigraphy and geochronology. A greater diversity of conodonts favored shallow water environments and graptolites similarly favored deeper water environments. Stratigraphic sequences are of great value but can be masked by regional tectonic events. These differences result in a very serious challenge in terms of correlating different sedimentary rock units that were deposited in different environments. Thus, it is important to develop new tools to aid in stratigraphic correlation. We are linking these disparate successions using the numerous K-bentonites that occur throughout eastern Laurentia in the Upper Ordovician. These key marker horizons to allow correlating the sedimentary units by geochemical fingerprints, high precision U-Pb radiometric dating. We are also collecting conodonts from graptolite shale surfaces. The full set of geochemical, geochronological, and paleontological events can then be arranged into an optimal time sequence by computer algorithms that consider all the local evidence of relative age including local event beds. Our intent is to use the new high-resolution age constraints to improve our ability to determine whether faunas differ because of environment or because of age. By translating these insights into increasingly sophisticated algorithms the results will dramatically improve the resolving power of geologic time scales that can be built from large geologic databases. Such databases are already being compiled by major geological community groups and our new algorithms could significantly assist their efforts.