Murray State Theses and Dissertations

Abstract

The Atlantic Coastal Plain has long been recognized as a natural laboratory useful for testing hypotheses about various environmental and ecological effects on marine fauna. For studies such as these to continue being conducted in a rigorous and easily repeatable manner, a reliable taxonomy must be established for genera within this physiographic province. The bivalve genus, Astarte, is a cosmopolitan genus that is commonly found within the Atlantic Coastal Plain. This genus has many formally recognized species, even though it lacks many features that would encourage diversification, marking it as a taxonomic group in need of potential revision. The complexity of bivalve shells, such as Astarte, yield numerous possible landmarks, making them great candidates for a study using geometric morphometrics to discriminate species.

A morphometric analysis of 918 shells representing ten different taxa from the Pliocene of the Atlantic Coastal Plain was conducted. A total of nine homologous landmarks and five pseudo-landmarks were collected from scaled digital photographs. Procrustes transformation and Principal Components Analysis (PCA) were performed on the collected dataset. PCA was also performed on allometric residuals and outline harmonics to fully understand the variability of morphologies present.

All PCA results show large amounts of overlap between all species. Astarte concentrica and Astarte undulata exhibit the most morphological variation and encompass all possible shape variants present within this study. These two species were most likely “trash bins” in which unknown specimens have been dumped throughout the years and suggest there are species within Astarte that should be synonymized.

Year manuscript completed

2018

Year degree awarded

2018

Author's Keywords

Paleontology, Morphometrics, Astarte, Taxonomy

Thesis Advisor

Michelle M. Casey

Committee Chair

Michelle M. Casey

Committee Member

Gary E. Stinchcomb

Committee Member

Craig Collins

Committee Member

Bassil El Masri

Document Type

Thesis

AppendixA_RawData.pdf (2530 kB)
Raw Data for Thesis

Available for download on Tuesday, April 16, 2019

Share

COinS