AbstractA traditional typological approach to taxonomy often does not adequately account for intraspecific variation and can result in taxonomic oversplitting. For many groups, including ammonoids of thePlacenticerasgenus, intraspecific variation documented in recent studies (e.g., ontogenetic changes, sexual dimorphism, polymorphism) challenges the historic proliferation of species names. Here, we used a population approach to taxonomy and quantitatively evaluated morphometric variation in a sample of Late Cretaceous (Santonian–Campanian)Placenticerasfrom Alabama and adjacent counties.We used linear mixed models (LMMs) to characterize how morphological variables scale with conch size across the sample, exploiting mixed longitudinal data to evaluate individual variation in growth and inform interpretations of multivariate analyses. Extended LMMs incorporating geological formation evaluated morphological changes through time. Principal component analysis and clustering analysis were then used to evaluate the number of distinct clusters that emerged in multivariate morphospace independent of previous taxon name assignments.Discontinuous scaling relationships and distinct clusters in multivariate space suggest sexual dimorphism characterized by differences in adult size and, secondarily, shape. PreviousStantonocerasandPlacenticerasassignments broadly overlap in our morphospace, failing to justify this historic distinction (as sexual dimorphs or as genera or subgenera).Placenticerasconch morphology and ornament placement changed through time, suggesting a potential utility for coarse (stage-level) biostratigraphy. However, temporal changes were not associated with distinct clusters in morphospace, and our data fail to support the plethora of reported species names. As few as one or two (successive) species may be present in our sample (representing 130 years of collection effort). In addition to highlighting the need for a significant taxonomic revision of thePlacenticerasgenus, this study demonstrates the utility of LMMs for distinguishing between different sources of morphological variation, improving interpretations of morphospace under a population approach to taxonomy, and maximizing the amount of ontogenetic information that can be obtained nondestructively.
Read full abstract