In this Accomplishment Based Renewal proposal, Principal Investigator Sokal plans continued study of the various numerical approaches to reconstructing phylogenies (ancestor-descendant relationships) and their associated classifications of organisms. Sokal's past work has sought to establish the accuracy and stability of three different methods for ordering relationships among taxa (Wagner parsimony trees, maximum likelihood estimation, and his own creation, UPGMA, a clustering technique). During the period of this project, computer simulations will be constructed for different hypotheses of evolutionary character change. Between six and eight real datasets will be compared to the simulated data, and both sets will be analyzed for stability and accuracy using the three methods listed. Systematics has witnessed the proliferation of approaches to data analysis in the past decade, and Sokal's past work on the relative merits of these approaches on simulated data has had a wide audience. Yet the practicing systematist is not yet able to predict a priori which approach is the most suitable for the real data at hand. The proposed simulations based on current models of character change, followed by comparisons with real data sets, will address this problem. If successful, it will fill the gap between real and simulated data and will thereby open an area of fruitful research.
