The unprecedented amount of DNA sequence data made available by recent technological advances is changing how biologists approach questions. Such data have great power to reveal the history of species diversification by improving estimates of species relationships. However, the opportunities for improving estimates of species relationships are at risk because data collection is outpacing the development of analytical methods to handle the data. This project explores the power and limitations in recently developed methods to infer the history of "deep radiations" (events of rapid species diversifications that occurred in the distant past), which may be hampered by conflicting historical signal from different genomic regions. It will use computer simulations to not only evaluate key data properties affecting historical reconstructions, but also identify what combination of data and methodological practices are likely to improve estimates of species relationships. These simulations will be informed by examples from nature, assuring that biological realities, not just theoretical ideals, are jointly considered.
Deep radiations are of particular interest because they have had a major impact on present day diversity. Our inability to accurately infer the species relationships that define these events impedes our ability to link diversification with global events such as climate change and movements of the earth's continents. By identifying methodological properties and types of analyses that effectively utilize the genomic data now becoming available, this project will improve the foundation that many evolutionary and ecological questions depend upon -- a resolved history of species diversification.