Phenotypic innovation through time and space

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The origins and maintenance of biodiversity are key to understanding and mitigating the effects of the current sixth mass extinction. One central aspect of biodiversity-change-through-time is how species' traits change in relation to changes in their environment. Macroevolutionary biologist have proposed two key mechanisms: elaboration, where traits can change over time with incremental modifications along a "line of evolutionary least resistance" (e.g. the gradual change of size across a geographical gradient) or innovation where new distinct traits arise rapidly and away from the line of evolutionary least resistance (e.g. species evolving new phenotypic features, for example on islands).While these mechanisms have been widely studied, we have no clear understanding of how innovation or elaboration impact biodiversity because research has been limited to specific groups at small spatio-temporal scales. We also lack a generalisable concept of innovation and elaboration and appropriate methods and datasets for understanding the relationship between phenotype and biodiversity across lineages and spatio-temporal scales. By proposing a novel conceptual and methodological approach to study trait evolution, I will answer the following key questions: 1) Does ecological opportunity generate innovation? 2) Is innovation predictable across space, time and lineages? and 3) Does innovation predict disparity and diversity across space, time, and lineages?I will achieve this by developing 1) a novel conceptual framework to evaluate the relative contribution of elaboration and innovation to trait evolution across different spatio-temporal scales; 2) a set of new methodological tools to measure elaboration and innovation and 3) two datasets spanning across different time scales and lineages provide generalisable answers. Specifically, I will: 1) Generalise the concepts of elaboration and innovation by defining them as, respectively, the mathematical projection and rejection of a species or a clade onto a "line of least evolutionary resistance" in any trait space, defining this line as the eigenvector of the traits variance-covariance matrix measured using phylogenetic generalised mixed effect models. 2) Apply this new concept and method to two contrasting datasets of living birds (8748 species) and fossil mammals (177 species) to answer the three questions above across different spatio-temporal scales. 3) Implement this approach as a package in R to make it applicable for answering multiple specific questions across different datasets. This will allow us to estimate how phenotypic innovation and elaboration has shaped biodiversity through time and space, shedding light on the mechanisms that lead to the amazing biodiversity we observe today.