2015 GSA Annual Meeting in Baltimore, Maryland, USA (1-4 November 2015)

Paper No. 176-16
Presentation Time: 11:45 AM

MORPHOLOGICAL PREDICTORS OF BACKGROUND EXTINCTION RISK FOR AMMONITES THROUGH THE CRETACEOUS


CHANG, Lucy, FINNEGAN, Seth and MARSHALL, Charles R., Department of Integrative Biology and Museum of Paleontology, University of California, Berkeley, Valley Life Sciences Building, Berkeley, CA 94720-4780, luchang@berkeley.edu

Ecological differences may play an important role in determining extinction rate but are often difficult to infer. Here, using morphology as a proxy for ecology, we ask for ammonites how their conch shape, and their place and distinctiveness in morphospace with respect to their contemporaries, affect their extinction risks. Further, we ask whether these relationships remain constant across time.

We focus on the ammonites of the Cretaceous - a richly diverse group of animals whose variety of shell shapes are associated with specific ecological roles and life habits. Shape and size measurements were collected using a custom-built web applet from published figures of exemplar specimens for over 1,100 genera represented in the Treatise of Invertebrate Paleontology. Coiling parameters, inspired by Raup's (1967) framework, were used to characterize the shape of each specimen's shell. These include conch width, whorl width, umbilical width, and whorl expansion rate. Using these parameters, and the stratigraphic range of each genus described in the Treatise, we generated an ammonite morphospace for the entire Cretaceous. Stage-level morphospaces were then used to calculate several metrics for describing the morphological position and distinctiveness for each genus (e.g., average distance to progressively more inclusive sets of neighbors), as well as characteristics of its family and superfamily (e.g., maximum variation in shape).

These metrics were then incorporated into regression models as potential predictors of genus-level extinction for each interval. We tested the consistency of the prediction strengths across time by training interval-specific models and using them to predict extinction in the adjacent stages. These methods allow us to identify individual and clade level characteristics involving conch shape that correlate with extinction risk and detect periods of time in which extinction may operate on the range of ammonite morphologies in previously unpredictable ways.