23 D15. Paleontology (Posters)

Friday, 20 March 2020
1:30 PM - 5:30 PM
Grand Ballroom A–D

CAN WE TEACH OLD DATA A NEW TRICK? RE-DISCOVERING CENTURY OLD DATA TO RECONSTRUCT BIVALVE DISTRIBUTIONS IN THE DEVONIAN OF NEW YORK

Paper number: 23-15
Program: Technical Sessions
Time: 1:30 PM – 5:30 PM

Authors

Abstract

Over more than a century, the Paleozoic of NY State has been in the focus of many geological and paleontological studies. The Devonian units of the Appalachian basin in particular have provided the samples on which many landmark studies have been based. This project is setting out to use more than a century old geographic, stratigraphic and taxonomic data of Devonian bivalve occurrences in the units of the Appalachian basin and with GIS to make these visually accessible.

From the literature, which is often more than 100 years old, we record all occurrences of bivalve species throughout the Devonian of the Appalachian basin. Over 60 bivalve genera from mostly New York State localities have been noted so far. Our data base currently includes over 2000 occurrences and this number is steadily increasing. The literature that describes bivalves from the Devonian of New York are mainly old mapping reports and monographs describing the fauna of specific units or beds. Many of these publications are the direct results of State Geologist and Paleontologists fieldwork. All stratigraphic and taxonomic information is updated and many historical location descriptions have to be researched and verified. The resulting database of bivalve taxa occurrences from the Devonian of New York are mapped spatially and temporally using GIS. We aim to be able to use this data and its visual representation to examine species distribution patterns in relationship to, for example, sea level changes and/or compare the distributions of different taxa to each other through time. We hope that our work will enable us to fully utilize this treasure trough of data collected more than a century ago.

Geological Society of America Abstracts with Programs. Vol. 52, No. 2

doi: 10.1130/abs/2020SE-345033

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