GSA Annual Meeting in Denver, Colorado, USA - 2016

Paper No. 137-1
Presentation Time: 1:35 PM


PAYNE, Jonathan L., Geological and Environmental Sciences, Stanford University, 450 Serra Mall, Bldg. 320, Stanford, CA 94305, BUSH, Andrew M., Ecology and Evolutionary Biology & Center for Integrative Geosciences, University of Connecticut, 75 N. Eagleville Road, Unit 3043, Storrs, CT 06269, CHANG, Ellen T., Division of Epidemiology, Stanford University School of Medicine, Stanford, CA 94305, HEIM, Noel A., Department of Geological Sciences, Stanford University, 450 Serra Mall, Building 320, Stanford, CA 94305, KNOPE, Matthew L., Biology Department, University of Hawaii at Hilo, Hilo, HI 96720 and PRUSS, Sara B., Department of Geosciences, Smith College, Northampton, MA 01063,

The macroevolutionary effects of extinction derive from both intensity of taxonomic losses (e.g., percent extinction) and selectivity of losses with respect to ecology, physiology, and/or clade membership. Increasingly, paleontologists are using logistic regression to quantify extinction selectivity because the selectivity metric is independent of extinction intensity and multiple predictor variables (e.g., abundance, geographic range, motility) can be assessed simultaneously. We illustrate the use of logistic regression with an analysis of physiological buffering capacity and extinction risk in the Phanerozoic marine fossil record. We propose the geometric mean of extinction intensity and selectivity as a simple, quantitative metric for the influence of extinction events. In addition to providing a quantitative measure of influence to compare among past events, this approach provides an avenue for quantifying the risk posed by the emerging biodiversity crisis that goes beyond a simple projection of taxonomic losses.