Big Data, Deep Time: Statistics applied to fossil datasets for paleoceanographic investigations

Session ID#: 23477

Session Description:
The use of statistics as applied to fossil datasets is not a new concept, as macrofossil paleontologists have used these methods for decades to infer biogeography and speciation processes. However, the use of statistics in paleontological datasets to infer paleoceanographic conditions has been muted in the past, in part due to slow computational times and inaccessibility of large datasets. Today, with improved accessibility to large amounts of data and faster statistical programs, analyses can be conducted quickly and efficiently. This session will highlight the statistical-based research conducted in the paleoceanographic community as applied to fossil datasets, namely micro- and molecular fossils. These data are powerful means by which to infer paleoceanographic conditions, such as depositional environments, water column structures, sea level changes, and changes in ocean chemistry. Although this session is intended to highlight research conducted with microfossils in deep time, we welcome all fossil datasets from any time period.
Primary Convener:  Raquel Bryant, University of Massachusetts Amherst, Amherst, MA, United States
Convener:  Adriane Renee Lam, University of Massachusetts Amherst, Department of Geosciences, Amherst, MA, United States

  • B - Biogeosciences
  • OS - Ocean Sciences
Index Terms:

Abstracts Submitted to this Session:

Yoshiyuki Ishitani, University of Tsukuba, Tsukuba, Japan
Thibault de Garidel-Thoron1, Ross Marchant1, Eric Soto2, Yves Gally1, Luc Beaufort1, Clara T Bolton1, Michael Bouslama2, Laetitia Licari1, Jean-Charles Mazur1, Jean-Marc Brutti2 and Francis Norsa2, (1)CEREGE : CNRS, Aix-Marseille Univ., IRD, CdF, Aix-en-Provence, France, (2)ATG Technologies, Avignon, France
Raquel Bryant, University of Massachusetts Amherst, Amherst, MA, United States
Elizabeth C Sibert, Harvard University, Earth and Planetary Sciences & Harvard Society of Fellows, Cambridge, MA, United States
Thomas M Marchitto Jr1, Ritayan Mitra2, Boxuan Zhong3, Qian Ge3, Bhargav Kanakiya3 and Edgar Lobaton3, (1)University of Colorado, INSTAAR & Geological Sciences, Boulder, CO, United States, (2)University of Colorado, INSTAAR, Boulder, CO, United States, (3)North Carolina State University, Dept. of Electrical and Computer Engineering, Raleigh, NC, United States
Andrew Fraass, National Museum of Natural History, Washington, DC, United States, Brian T Huber, National Museum of Natural History, Department of Paleobiology, Washington, DC, United States and Daniel Clay Kelly, University of Wisconsin Madison, Madison, WI, United States