GSA Annual Meeting in Indianapolis, Indiana, USA - 2018

Paper No. 39-14
Presentation Time: 9:00 AM-5:30 PM

DELINEATING SPECIES OF RAFINESQUINA IN THE TYPE CINCINNATIAN (ORDOVICIAN): A MORPHOMETRIC APPROACH


FORSYTHE, Ian J., Department of Geological Sciences, Ohio University, 316 Clippinger Lab, Athens, OH 45701 and STIGALL, Alycia L., Department of Geological Sciences and Ohio Center for Ecology and Evolutionary Studies, Ohio University, 316 Clippinger Lab, Athens, OH 45701

Fossils of the Upper Ordovician strata of the Cincinnati, Ohio region have been intensively studied for well over a century. During this interval, numerous species and subspecies of the strophomenid brachiopod Rafinesquina have been described. These taxa were erected using a typological species concept, and most modern paleontologists agree that the lineage has been over-split. Yet there is little scientific consensus about how population variation in morphology relates to biologically meaningful species in this clade. In this study, we apply geometric morphometric analysis to a large collection of Rafinesquina specimens with detailed geographic and stratigraphic occurrence data to test whether valve shape can be used to differentiate biologically meaningful species.

The great abundance of available fossils makes the genus Rafinesquina an ideal subject on which to test the efficacy of geometric morphometrics as a method of species delineation. Two-dimensional geometric morphometrics was used to determine the number of Rafinesquina species present in the Type Cincinnatian. Dorsal and ventral valve exteriors of 13 previously named species from the Cincinnatian Series were digitized and analyzed using a combination of landmark, semi-landmark and outline based analyses.

Landmark and outline data were captured using ImageJ. The landmark data were analyzed with Geomorph, and the outline data were analyzed with SHAPE v1.3. General Procrustes Analysis (GPA) was performed on both data sets to remove size as a variable. Principal Component Analysis (PCA) was used to rotate the data onto major axes and remove correlation between variables and identify the Principal Components (shape variables) for further analysis. The principal components with the highest loading (PC1 and PC2) were visualized using regression methods. Statistical analyses were then used to identify discrete species morphologies within morphospace.

Based on results of this study, two-dimensional geometric morphometrics is a successful tool for identifying distinct species of Rafinesquina in the study region. These analyses can provide the basis for differentiating population-level variation from species-level distinctions required for future systematic revision of the genus.