RUI: Collaborative Research: Extending phylogenetic comparative methods for evaluating within-species trends in a macroevolutionary context

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How do evolutionary changes within species translate into broad patterns across a group of related species? This question is at the heart of evolutionary ecology, but has been very difficult to answer. A major problem is that current analytical approaches, known as phylogenetic comparative methods, require that a single value be used to represent a trait for an entire species. As a result, valuable information on differences among individuals within a species can't be used. This limits the types of questions that these comparative methods can address. The main goal of this project is to develop new analytical software that accounts for trait variation within species, which will result in a much more powerful computational tool. The newly developed software will be tested using experimental data from salamanders and fish. This award will have multiple broader impacts. This new tool will let a whole new set of hypotheses be tested and will be widely used by scientists doing evolutionary ecology research. Undergraduate students will receive hands-on training in mathematical modeling and software development. Educational outreach activities include a research-education exchange between a regional undergraduate university and a large research university. National and international teaching workshops will help train the next generation of students and scientists from around the world.Analyses of phenotypic data tend to remain distinctly different enterprises between microevolutionary and macroevolutionary studies. Consequently, we still do not know how microevolutionary trends from ecological selection associate to macroevolutionary trends across phylogenies. Phylogenetic comparative methods (PCMs) measure the amount of phylogenetic signal in a set of data or account for the phylogenetic relatedness among observations when evaluating ecological variation, but currently work only with single values for species. Thus, large amounts of within-species data are disregarded when using PCMs, which limits their inferential capability. This project will develop an analytical solution to this problem, and provide a framework for extending PCMs to large data sets comprising microevolutionary data. The methods developed will allow scientists to evaluate the consistency of small-scale and large scale evolutionary relationships in a comparative framework. This project will incorporate both theoretical and empirical components. Statistical research will evaluate the statistical power and inferential error rates of "expanded-PCM" to varied analytical designs, phenotypic variables, tree topologies, and data balance. These methods will be applied empirically to two vertebrate systems to study the phylogenetic relatedness of intra-species morphological variation, as it is associated with intra- and interspecific ecological variation. Several educational outreach activities will also be conducted, including: a research-in-education exchange between a primarily undergraduate university and large research university, and teaching workshops in quantitative methods to train the next generation of students and scientists from around the world.