2008 Joint Meeting of The Geological Society of America, Soil Science Society of America, American Society of Agronomy, Crop Science Society of America, Gulf Coast Association of Geological Societies with the Gulf Coast Section of SEPM

Paper No. 1
Presentation Time: 8:00 AM

The Taxon-Free Approach to Paleobotanical Meta Analysis

GREEN, Walton A., Department of Paleobiology, National Museum of Natural History, Smithsonian Institution [NHB, MRC 121], P.O. Box 37012, Washington, DC 20013-7012, wagreen@bricol.net

The traditional taxonomic approach in paleobotany (and in other biological fields) relies on recognizing Linnaean groups---primarily minimal Linnaean groups, or species---as basic units of analysis and then on keeping track of the distribution of these units in space and time. This practice of subsuming a great deal of variation in a system of classification has the advantage of making book-keeping easier, but the disadvantage of depending heavily on how the classification is done.

The introduction of the microcomputer has provided the opportunity for paleobotanists to keep track of vastly more information than was possible with non-electronic methods, making book-keeping easier than it has ever been in the past. One way to exploit this technological advance is the taxon-free approach. Instead of taking the species as a the basic unit, this essentially takes the character as the unit of recording, storage, and analysis. Instead of measuring species diversity, therefore (the number of species in a particular geographic area in a window of time), the taxon-free approach measures the number of observational units (usually specimens or species) sharing a character. Leaf architectural data provides an example of how this can supplement or replace the traditional taxonomic approach, especially when the questions being asked are fundamentally ecological rather than phylogenetic. Wider application of taxon-free methods along with the incorporation of morphological fields into current paleontological data-bases, and large-scale electronic data sharing will allow us more fully to apply the power that the computers have provided to questions of biological interest.