277-5 Spatial Prediction of Paleoenvironments Using GIS

See more from this Division: General Discipline Sessions
See more from this Session: Paleontology III - Paleoecology, Geochronology, and Education

Wednesday, 8 October 2008: 9:00 AM
George R. Brown Convention Center, 330B

Susan L. Barbour Wood1, Ronald W. Davis1, Matthew Kerfonta1 and Gwen M. Daley2, (1)Geosciences and Natural Resources, Western Carolina University, Cullowhee, NC
(2)Department of Chemistry, Physics, and Geology, Winthrop University, Rock Hill, SC
Abstract:
In modern ecologic studies, the delineation of faunal gradients, ecological relationships, species diversity, and virtually any other characteristic of fauna and/or flora in a landscape requires an understanding of potential species interactions as well as habitat and environment conditions. The use of paleontological death assemblages to recreate ancient ecosystems is more difficult, posing a greater risk of error from such factors as taphonomic bias, temporal mixing, improper sampling and associated sampling issues and human error.

Geographic information systems (GIS) are widely applied in modeling modern species-habitat relationships, and we investigated the use of GIS in modeling ecosystem conditions for a hypothetical depositional paleoenvironment of the upper Miocene Eastover and Pliocene Yorktown formations. The model was based on parameters recovered during over a decade of bulk field sampling of the Atlantic Coastal Plain in Virginia. Truly random sampling of paleoenvironments is improbable due to outcrop limitations, so a sampling transect was created in the model based on an "ideal" continuous outcrop.

Kriging is a geostatistical interpolation technique that generates an estimated surface, substrate muddiness in our model, from a set of points with known values. A set of 60 points along the modeled outcrop were used to develop the reference surface. The substrate value (percent mud) for each sampling point was depicted along an environmental substrate gradient in the model based on actual sieve analyses of 44 samples of bulk field material, which ranged from 0.74% to 36% mud. Points were iteratively removed from the model to estimate the sensitivity of sampling rates to the recovery of the known (modeled) landscape. This analytical technique can, in turn, be combined with faunal or other data to create predictive paleoenvironmental maps via interpolation between sampling points. Models of the suitability of kriging at different scales will be discussed.

See more from this Division: General Discipline Sessions
See more from this Session: Paleontology III - Paleoecology, Geochronology, and Education