OIST Workshop on the Evolutionary Analysis of Morphology

Many of the most interesting questions in biology have to do with the origins, evolutionary history, and ecological function of morphological characters. The majority of these processes take place over time periods too long to study experimentally. As a result, much of our understanding of these processes comes from studies in which we quantify some aspect of the morphology of an organism and then employ statistical methods to infer patterns and processes that have shaped the evolution of those phenotypes in the context of a phylogenetic tree.  The analysis of morphological data and phylogenetic comparative methods are each accompanied by a unique set of statistical issues, and a great number of tools have been developed for these types of data.  This course will introduce the methodology for the quantification and statistical analysis of morphology (shape & size), and provide the pipeline for performing a comparative research study on any taxonomic system using cutting-edge quantitative methods.


Biological structures are complex and varied, and the course will first provide an overview of modern analytical tools available to measure and study them, including imaging techniques, and working with linear measures and ratios, landmarks and coordinates, outlines, and surfaces. The course will then cover the statistical methods used to test evolutionary hypotheses, with a focus on modern phylogenetic comparative methods.  These methods use a phylogeny to study the process and pattern of evolutionary change through time and among taxa.  This workshop will teach students the theory, implementation, and use of phylogenetic comparative methods, with particular attention to methods implemented for the R statistical computing environment.  Several of the instructors are responsible for originating many of the analytical methods and software packages that will be presented, providing a rare opportunity for students to interact with world-leading researchers in the field.  Students with their own data are encouraged to bring it along for advice and practice.

If you would like to attend, please fill out the application form.