Cranial modularity drives phenotypic diversification and adaptive radiation of Antarctic icefishes
- 1. Universidade Federal do Paraná
- 2. Rice University
- 3. University of Oklahoma
Description
Modularity among traits is thought to drive morphological evolution and diversification, with more modular species often showing greater disparity and faster evolutionary rates. However, recent studies suggest this pattern is not universal, as higher integration can sometimes be linked to faster rates of evolution. In adaptive radiation, modularity likely facilitates morphological divergence, but its specific role in trait diversification within these events remains uncertain. Antarctic icefishes (Perciformes: Notothenioidei) have undergone adaptive radiation in the frigid Southern Ocean, yet the role of modularity in their craniofacial evolution remains poorly understood. Emerging from a common ancestor 22 million years ago, these fishes developed unique morpho-physiological adaptations, such as antifreeze glycoproteins, that contributed to their evolutionary success, but the contribution of cranial modularity to their diversification is still unexplored. Here, we analyze skull shape across 172 perciform species using micro-CT scanning and geometric morphometrics to investigate the tempo and mode of skull evolution in 80 notothenioids versus 92 perciform relatives. Notothenioids exhibit considerable cranial shape diversity, with skull shapes ranging from short to long faces. Fast rates of skull shape evolution occurred in smaller subclades following the emergence of cranial elongation, a derived trait within notothenioids. They also exhibit elevated evolutionary modularity relative to their perciform relatives, with reduced covariation among skeletal elements over time, likely corresponding with Miocene cooling events and the formation of the Antarctic Circumpolar Current. We propose that greater phenotypic modularity in notothenioid skulls represents a pivotal innovation, facilitating their evolutionary response to new ecological opportunities in the Antarctic.
Notes
Funding provided by: U.S. National Science Foundation
ROR ID: https://ror.org/021nxhr62
Award Number: 1906574
Funding provided by: U.S. National Science Foundation
ROR ID: https://ror.org/021nxhr62
Award Number: 2237278
Methods
Morphological sampling and shape analyses. To investigate skull shape evolution in Notothenioidei, we quantified the skull shapes of 80 Notothenioidei species (representing approximately 51% of total clade diversity, with all seven families included) and 92 species from other Perciformes (encompassing 30 different families). This dataset includes a total of 172 species belonging to 37 families, covering 66% of the Perciformes families (SI Appendix, Table S4 and Fig. S1). We analyzed the three-dimensional skull morphology of each species through micro-computed tomography (μCT) scans. The specimens were scanned at both Rice University and the Natural History Museum of Los Angeles County (LACM) under the oVert and ScanAllFishes initiatives. Additionally, we obtained further scans from Morphosource (http://morphosource.org). These scans were processed in Amira v2.0.0 (Thermo Fisher Scientific, Waltham, MA) to isolate the skull by removing scales and other debris. The resulting skulls were converted into 3D meshes and saved as .ply files. We then digitized the mesh files with 145 three-dimensional landmarks (comprising both 55 fixed and 90 semi-sliding types; SI Appendix, Table S4) using the Checkpoint software (Stratovan, Davis, CA). All landmarks were consistently placed on the left side of the skull.
After digitization, to account for rotation and translation inherent in the highly kinetic articulating components of the fish skull, we first aligned each dataset using Generalized Procrustes Analysis (GPA) with the gpagen function in the geomorph package, version 4.0.8 (72) in R, version 4.4.1 (73). Next, a local superimposition was performed to standardize the positioning of the various skull elements. To analyze the shape evolution of individual bones, we subdivided our comprehensive skull shape dataset into smaller datasets for each bone, with the raw coordinates for each bone individually superimposed. Following the local superimposition, using the findmeanspecies function, we determined the mean species shape for each group (Notothenioidei and Other Perciformes). After performing the local superimposition, we conducted a principal components analysis (PCA) to explore the primary axes of skull shape variation. Additionally, we utilized the plotRefToTarget function in the geomorph package to illustrate the main axes of skull shape variation as ball-and-stick plots (SI Appendix, Fig. S3).
Phylomorphospace and morphological disparity. To visualize the major axes of shape variation and evolution of Notothenioidei, we employed a phylomorphospace approach using the first two principal components (PCs) of shape variation, which accounted for 56% of the total shape variance, and the pruned, time-calibrated phylogeny from Rabosky et al. We pruned the phylogeny using the drop.tip function in the *ape *package version 5.0 to only include the taxa present in our study.
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Additional details
Related works
- Is source of
- 10.5061/dryad.vq83bk44j (DOI)