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      Developmental origins of mosaic evolution in the avian cranium

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          Studies reconstructing morphological evolution have long relied on simple representations of organismal form or on limited sampling of species, hindering a comprehensive understanding of the factors shaping biological diversity. Here, we combine high-resolution 3D quantification of skull shape with dense taxonomic sampling across a major vertebrate clade, birds, to demonstrate that the avian skull is formed of multiple semi-independent regions that epitomize mosaic evolution, with cranial regions and major lineages evolving with distinct rates and modes. We further show that the evolvability of different cranial regions reflects their disparate embryonic origins. Finally, we present a hypothetical reconstruction of the ancestral bird skull using this high-resolution shape data to generate a detailed estimate of extinct forms in the absence of well-preserved three-dimensional fossils.

          Abstract

          Mosaic evolution, which results from multiple influences shaping morphological traits and can lead to the presence of a mixture of ancestral and derived characteristics, has been frequently invoked in describing evolutionary patterns in birds. Mosaicism implies the hierarchical organization of organismal traits into semiautonomous subsets, or modules, which reflect differential genetic and developmental origins. Here, we analyze mosaic evolution in the avian skull using high-dimensional 3D surface morphometric data across a broad phylogenetic sample encompassing nearly all extant families. We find that the avian cranium is highly modular, consisting of seven independently evolving anatomical regions. The face and cranial vault evolve faster than other regions, showing several bursts of rapid evolution. Other modules evolve more slowly following an early burst. Both the evolutionary rate and disparity of skull modules are associated with their developmental origin, with regions derived from the anterior mandibular-stream cranial neural crest or from multiple embryonic cell populations evolving most quickly and into a greater variety of forms. Strong integration of traits is also associated with low evolutionary rate and low disparity. Individual clades are characterized by disparate evolutionary rates among cranial regions. For example, Psittaciformes (parrots) exhibit high evolutionary rates throughout the skull, but their close relatives, Falconiformes, exhibit rapid evolution in only the rostrum. Our dense sampling of cranial shape variation demonstrates that the bird skull has evolved in a mosaic fashion reflecting the developmental origins of cranial regions, with a semi-independent tempo and mode of evolution across phenotypic modules facilitating this hyperdiverse evolutionary radiation.

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          A generalized K statistic for estimating phylogenetic signal from shape and other high-dimensional multivariate data.

          Phylogenetic signal is the tendency for closely related species to display similar trait values due to their common ancestry. Several methods have been developed for quantifying phylogenetic signal in univariate traits and for sets of traits treated simultaneously, and the statistical properties of these approaches have been extensively studied. However, methods for assessing phylogenetic signal in high-dimensional multivariate traits like shape are less well developed, and their statistical performance is not well characterized. In this article, I describe a generalization of the K statistic of Blomberg et al. that is useful for quantifying and evaluating phylogenetic signal in highly dimensional multivariate data. The method (K(mult)) is found from the equivalency between statistical methods based on covariance matrices and those based on distance matrices. Using computer simulations based on Brownian motion, I demonstrate that the expected value of K(mult) remains at 1.0 as trait variation among species is increased or decreased, and as the number of trait dimensions is increased. By contrast, estimates of phylogenetic signal found with a squared-change parsimony procedure for multivariate data change with increasing trait variation among species and with increasing numbers of trait dimensions, confounding biological interpretations. I also evaluate the statistical performance of hypothesis testing procedures based on K(mult) and find that the method displays appropriate Type I error and high statistical power for detecting phylogenetic signal in high-dimensional data. Statistical properties of K(mult) were consistent for simulations using bifurcating and random phylogenies, for simulations using different numbers of species, for simulations that varied the number of trait dimensions, and for different underlying models of trait covariance structure. Overall these findings demonstrate that K(mult) provides a useful means of evaluating phylogenetic signal in high-dimensional multivariate traits. Finally, I illustrate the utility of the new approach by evaluating the strength of phylogenetic signal for head shape in a lineage of Plethodon salamanders.
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            A new time tree reveals Earth history’s imprint on the evolution of modern birds

            Estimates of the timing of evolution of modern birds reveals the influence of paleogeography and paleoclimate on diversification.
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              Mega-evolutionary dynamics of the adaptive radiation of birds

              The origin and expansion of biological diversity is regulated by both developmental trajectories1,2 and limits on available ecological niches3–7. As lineages diversify an early, often rapid, phase of species and trait proliferation gives way to evolutionary slowdowns as new species pack into ever more densely occupied regions of ecological niche space6,8. Small clades such as Darwin’s finches demonstrate that natural selection is the driving force of adaptive radiations, but how microevolutionary processes scale up to shape the expansion of phenotypic diversity over much longer evolutionary timescales is unclear9. Here we address this problem on a global scale by analysing a novel crowd-sourced dataset of 3D-scanned bill morphology from >2000 species. We find that bill diversity expanded early in extant avian evolutionary history before transitioning to a phase dominated by morphospace packing. However, this early phenotypic diversification is decoupled from temporal variation in evolutionary rate: rates of bill evolution vary among lineages but are comparatively stable through time. We find that rare but major discontinuities in phenotype emerge from rapid increases in rate along single branches, sometimes leading to depauperate clades with unusual bill morphologies. Despite these jumps between groups, the major axes of within-group bill shape evolution are remarkably consistent across birds. We reveal that macroevolutionary processes underlying global-scale adaptive radiations support Darwinian9 and Simpsonian4 ideas of microevolution within adaptive zones and accelerated evolution between distinct adaptive peaks.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                16 January 2018
                26 December 2017
                26 December 2017
                : 115
                : 3
                : 555-560
                Affiliations
                [1] aDepartment of Genetics, Evolution, and Environment, University College London , London WC1E 6BT, United Kingdom;
                [2] bDepartment of Life Sciences, The Natural History Museum , London SW7 5DB, United Kingdom;
                [3] cDepartment of Earth Sciences, University College London , London WC1E 6BT, United Kingdom
                Author notes
                1To whom correspondence should be addressed. Email: ryanfelice@ 123456gmail.com .

                Edited by Neil H. Shubin, The University of Chicago, Chicago, IL, and approved December 1, 2017 (received for review September 18, 2017)

                Author contributions: R.N.F. and A.G. designed research, performed research, analyzed data, and wrote the paper.

                Author information
                http://orcid.org/0000-0002-9201-9213
                Article
                201716437
                10.1073/pnas.1716437115
                5776993
                29279399
                ce5aab29-4d5a-4623-bdd6-b7de0ca510fc
                Copyright © 2018 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                Page count
                Pages: 6
                Funding
                Funded by: EC | H2020 | H2020 Priority Excellent Science | H2020 European Research Council (ERC) 100010663
                Award ID: STG-2014-637171
                Funded by: SYNTHESYS
                Award ID: FR-TAF-5635
                Categories
                Biological Sciences
                Evolution
                From the Cover

                evolutionary rates,evolutionary development,modularity,morphological diversity,morphometrics

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