Abstract
Paleontological reconstructions of phenotypic evolution are generally based on morphological measurements from stratigraphic successions of fossil samples, referred to as stratophenetic series. This talk presents an analytical method that recognizes stratophenetic series as a highly incomplete stratigraphic rendition of an underlying time series and evaluates the uncertainty involved in its reconstruction. I will briefly highlight some results from numerical experiments that show the detrimental effects of sampling and depositional architecture on observed patterns, and the inability of common statistical tests to correctly identify evolutionary mode. I then move on to formulating the inference of pattern from stratophenetic series as an inverse problem, the solution to which is defined as a posterior probability distribution obtained by direct Monte Carlo sampling of the parameter space, and evaluated with Bayesian integrals. Finally, I expand the Bayesian inversion to do model comparison (quantifying the relative merit of multiple working hypotheses), and apply the technique to a stratophenetic series of Miocene Pseudononion pizarrensis from sedimentary cores. This evolutionary "image reconstruction" approach is able to identify subtle changes in the mean outline shape of P. pizarrensis, associated with final whorl expansion. Some important caveats and future applications will be outlined.
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The CEES seminar room has a coffee-machine – it is therefore recommended that you come a bit earlier and get yourself a good cup of coffee (for the price of 3 NOK).