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Dryad

Macroevolutionary patterns of body plan canalization in euarthropods

Cite this dataset

Aria, Cédric (2020). Macroevolutionary patterns of body plan canalization in euarthropods [Dataset]. Dryad. https://doi.org/10.5061/dryad.vhhmgqnr8

Abstract

Reconstructing patterns of macroevolution has become a central endeavor in palaeobiology, because it offers insight into evolutionary models shaping the history of life. As the most diverse and abundant animals since the Cambrian period, arthropods provide copious data to elucidate the emergence of body plans in metazoan lineages. However, information provided by fossils on the tempo and mode of this phenomenon has lacked a recent synthesis. Here, I investigate macroevolutionary patterns of morphological evolution in Euarthropoda using a combined extinct and extant dataset optimized for multivariate analyses. Overall ordination patterns between the main morphogroups are consistent with another, independently-coded, extant-only dataset providing molecular and morphological rates of evolution. Based on a “deep split” phylogenetic framework, total-group Mandibulata and Arachnomorpha emerge as directional morpho-anatomical lineages, with basal fossil morphogroups showing heterogeneously spread-out occupations of the morphospace. In addition to a more homogeneous morphological variation, new morphogroups arose by successive reductions of translation distances; this pattern was interrupted only by terrestrialization events and the origin of pancrustaceans. A displaced optimum type of model is proposed to explain the fast assembly of canalized body plans during the Cambrian, with basal fossil morphogroups fitting intermediate fitness peaks in a moving adaptive landscape. Given time constraints imposed by the palaeontological evidence, and owing to the interplay between canalization and modularity, as well as a decoupling between molecular and morphological rates, the rise of euarthropods would support the view that the swiftness of the Cambrian explosion was mostly associated with the build-up of genetic regulatory networks.