Evolutionary patterns derived from 150 million years of morphological and functional evolution in neopterygian fishes

Neopterygian fishes represent over half of vertebrate richness in the Recent and display staggering phenotypic variety, yet little is known about the first 150 million years of their evolution. Furthermore, neopterygian richness and disparity is highly unevenly partitioned between teleost fishes, with ~29,000 species expressing a plethora of phenotypes, and holostean fishes, with 8 species and just two morphological styles. Fossil phenotypes have the unique ability to illuminate the assembly of neopterygian disparity, and can reveal the pattern by which the uneven partitioning of disparity arose. Morphology and function were quantified with landmarks and six functional traits, respectively, for 356 neopterygian species known globally throughout the first 150 million years of their history. The main axes of morphological and functional variation were derived and used to examine a series of evolutionary questions. Pertinently, they revealed how disparity was accumulated for 60% of the neopterygian radiation; morphological disparity increased through time, whereas functional disparity remained stable. The morphological dataset was expanded to include shape data for 398 species and size data for 471 species. Time scaled supertrees containing 671 mostly Mesozoic, but also living neopterygian species, were created. Together, the trees and traits were used to quantify evolutionary rates and innovation and test the predictions of genome duplication enhanced morphological diversification in teleosts, and the presence of 'living fossil' characteristics in holosteans. The analyses revealed higher rates and greater innovation in teleosts guaranteed to possess duplicated genomes, consistent with the predictions of genome duplication enhanced diversification. The only 'living fossil' characteristic of holosteans is their poor capacity for size innovation, yet they possess relatively high rates of shape evolution. However, estimates of rates and innovation are heavily influenced by timescale choice, emphasising the need for workers to perform their analyses on a variety of plausible timescales to determine the limits of their conclusions.