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Environmental signal in the evolutionary diversification of bird skeletons

Abstract

Characterizing how variation in the tempo and mode of evolution has structured the phenotypic diversity of extant species is a central goal of macroevolution1,2,3. However, studies are typically limited to a handful of traits4,5,6, providing incomplete information. We analyse morphological diversification in living birds, an ecologically diverse group7, documenting structural scales from ‘pan-skeletal’ proportions down to the localized three-dimensional shape changes of individual bones. We find substantial variation in evolutionary modes among avian subgroups and among skeletal parts, indicating widespread mosaicism and possible differences in the structure of the macroevolutionary landscape across Earth’s main environments. Water-linked groups, especially Aequorlitornithes (waterbirds), have repeatedly explored a large portion of their total morphospace, emphasizing variation in body proportions and in the shape of bones close to the body core, which are functionally related to the mechanics of locomotion8. By contrast, landbirds (Inopinaves) evolved distinct, group-specific body forms early in the aftermath of the K-Pg and subsequently emphasized local shape variation, especially in the head and distal limb bones, which interact more directly with the environment. Passerines, which comprise more than half of all bird species, show a conservative evolutionary dynamic that resulted in low disparity across all skeletal parts. Evidence for early establishment of the morphospace of living birds is clear for some skeletal parts, including beaks and the combined skeletal morphology. However, we find little evidence for early partitioning of that morphospace, contrary to more specific predictions of ‘niche-filling’ models1,9. Nevertheless, early divergence among broad environmental types may have caused an early divergence of evolutionary modes, suggesting an important role for environmental divergence in structuring the radiation of crown-group birds.

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Fig. 1: Early establishment of the morphospace for skeletal form and beak shape during the diversification of Neornithes.
Fig. 2: Whole skeletal subclade disparity–age plotted across avian phylogeny and through time.
Fig. 3: Tests of early partitioning of avian skeletal space using the MDI.
Fig. 4: Deviations of group-specific disparities from the disparity expected if all birds were evolving under a uniform Brownian motion model of evolution.

Data availability

Raw landmark coordinates can be accessed as Supplementary Files linked to this article and accessing our project in OSF Public Repository following this link: https://osf.io/wjk3m/. All three-dimensional meshes can be freely downloaded following the links to Morphosource in Supplementary Materials Table 1.

Code availability

Custom code can be accessed in our project in OSF Public Repository following this link: https://osf.io/wjk3m/.

References

  1. Simpson, G. G. The Major Features of Evolution (Columbia Univ. Press, 1953).

  2. Gould, S. J. Ontogeny and Phylogeny (Harvard Univ. Press, 1985).

  3. Jablonski, D. Approaches to macroevolution: 2. Sorting of variation, some overarching issues, and general conclusions. Evol. Biol. 44, 451–475 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Cooney, C. R. et al. Mega-evolutionary dynamics of the adaptive radiation of birds. Nature 542, 344–347 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  5. Felice, R. N. & Goswami, A. Developmental origins of mosaic evolution in the avian cranium. Proc. Natl Acad. Sci. USA 115, 201716437 (2018).

  6. Navalón, G., Marugán-Lobón, J., Bright, J. A., Cooney, C. R. & Rayfield, E. J. The consequences of craniofacial integration for the adaptive radiations of Darwin’s finches and Hawaiian honeycreepers. Nat. Ecol. Evol. 4, 270–278 (2020).

    Article  PubMed  Google Scholar 

  7. Gill, F. B. Ornithology (Macmillan, 1995).

  8. Kardong, K. V. Vertebrates: Comparative Anatomy, Function, Evolution (Heinle and Heinle Publishers, 1997).

  9. Schluter, D. The Ecology of Adaptive Radiation (Oxford Univ. Press, 2000).

  10. Losos, J. B. Adaptive radiation, ecological opportunity, and evolutionary determinism: American Society of Naturalists EO Wilson Award address. The American Naturalist 175, 623–639 (2010).

    Article  PubMed  Google Scholar 

  11. Harmon, L. J., Schulte, J. A., Larson, A. & Losos, J. B. Tempo and mode of evolutionary radiation in iguanian lizards. Science 301, 961–964 (2003).

    Article  ADS  CAS  PubMed  Google Scholar 

  12. Hughes, M., Gerber, S. & Wills, M. A. Clades reach highest morphological disparity early in their evolution. Proc. Natl Acad. Sci. USA 110, 13875–13879 (2013).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  13. Ackerly, D., Schwilk, D. & Webb, C. Niche evolution and adaptive radiation: testing the order of trait divergence. Ecology 87, S50–S61 (2006).

    Article  CAS  PubMed  Google Scholar 

  14. Gatesy, S. M. & Dial, K. P. Locomotor modules and the evolution of avian flight. Evolution 50, 331–340 (1996).

  15. Dececchi, T. A. & Larsson, H. C. Body and limb size dissociation at the origin of birds: uncoupling allometric constraints across a macroevolutionary transition. Evolution 67, 2741–2752 (2013).

    Article  PubMed  Google Scholar 

  16. Clarke, J. A. & Middleton, K. M. Mosaicism, modules, and the evolution of birds: results from a Bayesian approach to the study of morphological evolution using discrete character data. Syst. Biol. 57, 185–201 (2008).

    Article  PubMed  Google Scholar 

  17. Prum, R. O. et al. A comprehensive phylogeny of birds (Aves) using targeted next-generation DNA sequencing. Nature 526, 569–573 (2015).

    Article  ADS  CAS  PubMed  Google Scholar 

  18. Oliveros, C. H. et al. Earth history and the passerine superradiation. Proc. Natl Acad. Sci. USA 116, 7916–7925 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  19. Field, D. J. et al. Early evolution of modern birds structured by global forest collapse at the end-Cretaceous mass extinction. Curr. Biol. 28, 1825–1831. e1822 (2018).

    Article  CAS  PubMed  Google Scholar 

  20. Benito, J. et al. 40 new specimens of Ichthyornis provide unprecedented insight into the postcranial morphology of crownward stem group birds. PeerJ 10, e13919 (2022).

  21. Field, D. J. et al. Timing the extant avian radiation: the rise of modern birds, and the importance of modeling molecular rate variation. Bull. Am. Mus. Nat. Hist. 440, 159–181 (2020).

  22. Feduccia, A. ‘Big bang’ for tertiary birds? Trends Ecol. Evol. 18, 172–176 (2003).

    Article  Google Scholar 

  23. Chiappe, L. M. & Qingjin, M. Birds of Stone: Chinese Avian Fossils from the Age of Dinosaurs (JHU Press, 2016).

  24. Saupe, E. E. et al. Climatic shifts drove major contractions in avian latitudinal distributions throughout the Cenozoic. Proc. Natl Acad. Sci. USA 116, 12895–12900 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  25. Nudds, R., Dyke, G. & Rayner, J. Forelimb proportions and the evolutionary radiation of Neornithes. Proc. R. Soc. London Ser. B Biol. Sci. 271, S324–S327 (2004).

    Article  Google Scholar 

  26. Wang, X. & Clarke, J. A. Phylogeny and forelimb disparity in waterbirds. Evolution 68, 2847–2860 (2014).

    Article  PubMed  Google Scholar 

  27. Crouch, N. M. & Ricklefs, R. E. Speciation rate is independent of the rate of evolution of morphological size, shape, and absolute morphological specialization in a large clade of birds. Am. Naturalist 193, E78–E91 (2019).

    Article  Google Scholar 

  28. Brocklehurst, N., Panciroli, E., Benevento, G. L. & Benson, R. B. Mammaliaform extinctions as a driver of the morphological radiation of Cenozoic mammals. Curr. Biol. 31, 2955–2963.e4 (2021).

    Article  CAS  PubMed  Google Scholar 

  29. Osborn, H. F. The law of adaptive radiation. Am. Naturalist 36, 353–363 (1902).

    Article  Google Scholar 

  30. Felice, R. N. et al. Decelerated dinosaur skull evolution with the origin of birds. PLoS Biol. 18, e3000801 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Felice, R. N., Tobias, J. A., Pigot, A. L. & Goswami, A. Dietary niche and the evolution of cranial morphology in birds. Proc. R. Soc. B 286, 20182677 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Orkney, A., Bjarnason, A., Tronrud, B. C. & Benson, R. B. Patterns of skeletal integration in birds reveal that adaptation of element shapes enables coordinated evolution between anatomical modules. N. Ecol. Evol. 5, 1250–1258 (2021).

    Article  Google Scholar 

  33. Chira, A. M. & Thomas, G. H. The impact of rate heterogeneity on inference of phylogenetic models of trait evolution. J. Evol. Biol. 29, 2502–2518 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Rombaut, L. M. et al. Allometric conservatism in the evolution of bird beaks. Evolution Lett. 6, 83–91 (2022).

    Article  Google Scholar 

  35. Navalón, G., Bright, J. A., Marugán‐Lobón, J. & Rayfield, E. J. The evolutionary relationship among beak shape, mechanical advantage, and feeding ecology in modern birds. Evolution 73, 422–435 (2019).

    Article  PubMed  Google Scholar 

  36. Mayr, G. Avian Evolution: The Fossil Record of Birds and its Paleobiological Significance (John Wiley & Sons, 2016).

  37. Foote, M. The evolution of morphological diversity. Ann. Rev. Ecol. Systematics 28, 129–152 (1997).

    Article  Google Scholar 

  38. Bribiesca-Contreras, F., Parslew, B. & Sellers, W. I. Functional morphology of the forelimb musculature reflects flight and foraging styles in aquatic birds. J. Ornithol. 162, 779–793 (2021).

  39. Phillimore, A. B. et al. Sympatric speciation in birds is rare: insights from range data and simulations. Am. Naturalist 171, 646–657 (2008).

    Article  Google Scholar 

  40. MacArthur, R. H. Population ecology of some warblers of northeastern coniferous forests. Ecology 39, 599–619 (1958).

    Article  Google Scholar 

  41. Cooney, C. R. et al. Sexual selection predicts the rate and direction of colour divergence in a large avian radiation. Nat. Commun. 10, 1773 (2019).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  42. Tobias, J. A. et al. Species coexistence and the dynamics of phenotypic evolution in adaptive radiation. Nature 506, 359 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  43. Del Hoyo, J. et al. Handbook of the Birds of the World Alive (Lynx Editions, 2017).

  44. Botelho, J. F., Smith-Paredes, D. & Vargas, A. O. Altriciality and the evolution of toe orientation in birds. Evolution. Biol. 42, 502–510 (2015).

    Article  Google Scholar 

  45. Natale, R. & Slater, G. J. The effects of foraging ecology and allometry on avian skull shape vary across levels of phylogeny. https://doi.org/10.1086/720745 (2022).

  46. Pigot, A. L. et al. Macroevolutionary convergence connects morphological form to ecological function in birds. Nat. Ecol. Evol. 4, 230–239 (2020).

    Article  PubMed  Google Scholar 

  47. Slater, G. J. Iterative adaptive radiations of fossil canids show no evidence for diversity-dependent trait evolution. Proc. Natl Acad. Sci. USA 112, 4897–4902 (2015).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  48. Rabosky, D. L. & Lovette, I. J. Density-dependent diversification in North American wood warblers. Proc. R. Soc. B. Biol. Sci. 275, 2363–2371 (2008).

    Article  Google Scholar 

  49. Friedman, S., Collyer, M., Price, S. & Wainwright, P. Divergent processes drive parallel evolution in marine and freshwater fishes. Syst. Biol. 4, syab080 (2021).

    Google Scholar 

  50. Jetz, W., Thomas, G., Joy, J., Hartmann, K. & Mooers, A. The global diversity of birds in space and time. Nature 491, 444–448 (2012).

    Article  ADS  CAS  PubMed  Google Scholar 

  51. Bjarnason, A. & Benson, R. A 3D geometric morphometric dataset quantifying skeletal variation in birds. MorphoMuseuM 7, e125 (2021).

  52. Abourachid, A., Fabre, A. C., Cornette, R. & Höfling, E. Foot shape in arboreal birds: two morphological patterns for the same pincer‐like tool. J. Anatomy 231, 1–11 (2017).

    Article  Google Scholar 

  53. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019); https://www.R-project.org/

  54. Adams, D., Collyer, M., Kaliontzopoulou, A. & Baken, E. Geomorph: Software for geometric morphometric analyses. R package version 4.0.4. https://cran.r-project.org/package=geomorph (2022).

  55. Collyer, M., Adams, D. & Collyer, M. M. Package ‘RRPP’. RRPP: Linear Model Evaluation with Randomized Residuals in a Permutation Procedure, R package version 1.1.2. https://cran.r-project.org/package=RRPP (2021).

  56. Harmon, L. et al. Package ‘geiger’. R package version 2 (R Foundation for Statistical Computing, 2020).

  57. Bookstein, F. L. in Advances in Morphometrics (eds Marcus, L. F. et al.) 131–151 (Springer, 1996).

  58. Gunz, P. & Mitteroecker, P. Semilandmarks: a method for quantifying curves and surfaces. Hystrix 24, 103–109 (2013).

    Google Scholar 

  59. Collyer, M. L., Davis, M. A. & Adams, D. C. Making heads or tails of combined landmark configurations in geometric morphometric data. Evolution. Biol. 47, 193–205 (2020).

    Article  Google Scholar 

  60. Ciampaglio, C. N., Kemp, M. & McShea, D. W. Detecting changes in morphospace occupation patterns in the fossil record: characterization and analysis of measures of disparity. Paleobiology 27, 695–715 (2001).

    Article  Google Scholar 

  61. Wills, M. A., Briggs, D. E. & Fortey, R. A. Disparity as an evolutionary index: a comparison of Cambrian and Recent arthropods. Paleobiology 20, 93–130 (1994).

    Article  Google Scholar 

  62. Clavel, J., Escarguel, G. & Merceron, G. mvMORPH: an R package for fitting multivariate evolutionary models to morphometric data. Meth. Ecol. Evol. 6, 1311–1319 (2015).

    Article  Google Scholar 

  63. Paradis, E. & Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).

    Article  CAS  PubMed  Google Scholar 

  64. Revell, L. J. phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2011).

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Acknowledgements

For access to specimens, we thank J. White and J. Cooper (NHMUK), J. Hinshaw (UMMZ), M. Lowe and M. Brooke (UMZC), M. Carnall and E. Westwig (OUMNH), K. Zyskowski (YPM), and B. Marks and J. Bates (FMNH). For access to CT scanning facilities, we thank K. Smithson (Cambridge Biotomography Centre); T. Davies, B. Moon and L. Martin-Silverstone (University of Bristol); V. Fernandez (Natural History Museum); A. Neander and Z.-X. Luo (University of Chicago PaleoCT) and M. Friedman (University of Michigan). We thank E. Griffiths, S. Wright, S. Poindexter, A. Wolniewicz and S. Evers for segmenting digital bone models from the CT scan data. We are grateful to A. Martin-Serra, J. L. Cantalapiedra, F. Blanco, M. Fabbri, I. Menéndez, S.M. Nebreda, J. Clavel, E.M. Steell, J. Marugán-Lobón and C. Navalón for enlightening discussion on contents, narrative and analytical approaches. We thank L. Balsa Pascual and Ó. Sanisidro for discussion on design choices. This work was supported by the European Union’s Horizon 2020 research and innovation programme 2014–2018 under grant agreement no. 677774 (European Research Council Starting grant no. TEMPO). Grant no. 677774 applies to the work of G.N., A.B. and R.B.J.B. G.N. acknowledges support from UKRI Future Leaders Fellowship no. MR/S032177/1.

Author information

Authors and Affiliations

Authors

Contributions

G.N. and R.B.J.B. conceptualized the study and designed the analytical approach. G.N., A.B., E.G. and R.B.J.B. collected and curated the data. G.N. and R.B.J.B. undertook the formal analyses. G.N. and R.B.J.B. wrote the manuscript. G.N. made the figures. G.N., A.B., E.G. and R.B.J.B. edited the text. R.B.J.B. acquired the funding used for this research.

Corresponding authors

Correspondence to Guillermo Navalón or Roger B. J. Benson.

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Competing interests

The authors declare no competing interests.

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Nature thanks Gavin Thomas and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Infographic displaying the data and the methods’ pipeline used in this study.

A detailed account of the Material and Methods used in our study can be found in the main text.

Extended Data Fig. 2 Diagram showing how subclade disparity through time is calculated as test of early partitioning of morphospace, showing idealized contrasting patterns of morphological evolution.

a) Example time-calibrated phylogeny and points in time (cladogenesis events) for which b) subclade disparities values are calculated for a Brownian model of diffusive evolution and two alternative modes of morphological evolution. c) Corresponding patterns in morphospace exploration over time for two idealised patterns of morphological evolution: early partitioning of trait space (morphospace) in which morphological evolution is constrained at the level of subclades, and a non-partitioned pattern in which constraints are similar in the total group and within subclades.

Extended Data Fig. 3 Tests of early-partitioning of avian allometry-free shape and local shape variation of the individual elements in Aequorlithornithes, Inopinaves and Passeriformes.

See Extended Data Fig. 2 for a detailed account of the idealised patterns associated with each mode of evolution of disparity through time.

Extended Data Fig. 4 Deviations of group-specific disparities from the disparity expected if all birds were evolving under a uniform Brownian motion model of evolution for additional groups of water-based (Gruiformes, Anseriformes) and land-based (non-landbird terrestrial Neoaves, Galliformes) birds.

Boxplots summarize the distribution of delta disparities, calculated as empirical disparities minus disparities for the 200 simulated values for each of the three target clades. All partitions and data types are displayed, namely, the whole skeleton, three main skeletal regions and individual bones and the four different aspects of morphological variation in the three target lineages of birds. Arrows highlight the lineage/partition/data type which shows particularly high (up pointing arrows) or low (down pointing arrows) values. Values are normalised by interquartile range.

Extended Data Fig. 5 Subclade disparity–age plots for the whole skeleton and body regions for Aequorlitornithes (waterbirds).

X axes represent subclade disparities while y axes represent time in millions of years from the present time. Solid coloured lines represent mean empirical disparities through time, dashed lines represent mean BM-simulated disparities through time, shaded polygons display the space between 95% percentile and 5% percentiles of disparities through time for BM-simulated data. Colour code of individual subclade disparities (dots) as in Fig. 2.

Extended Data Fig. 6 Subclade disparity–age plots for the whole skeleton and body regions for Inopinaves (landbirds).

X axes represent subclade disparities while y axes represent time in millions of years from the present time. Solid coloured lines represent mean empirical disparities through time, dashed lines represent mean BM-simulated disparities through time, shaded polygons display the space between 95% percentile and 5% percentiles of disparities through time for BM-simulated data. Colour code of individual subclade disparities (dots) as in Fig. 2.

Extended Data Fig. 7 Subclade disparity–age plots for the whole skeleton and body regions for Passeriformes (passerines).

X axes represent subclade disparities while y axes represent time in millions of years from the present time. Solid coloured lines represent mean empirical disparities through time, dashed lines represent mean BM-simulated disparities through time, shaded polygons display the space between 95% percentile and 5% percentiles of disparities through time for BM-simulated data. Colour code of individual subclade disparities (dots) as in Fig. 2.

Extended Data Fig. 8 Subclade disparity–age plots for the individual elements for Aequorlitornithes (waterbirds).

X axes represent subclade disparities while y axes represent time in millions of years from the present time. Solid coloured lines represent mean empirical disparities through time, dashed lines represent mean BM-simulated disparities through time, shaded polygons display the space between 95% percentile and 5% percentiles of disparities through time for BM-simulated data. Colour code of individual subclade disparities (dots) as in Fig. 2.

Extended Data Fig. 9 Subclade disparity–age plots for the individual elements for Inopinaves (landbirds).

X axes represent subclade disparities while y axes represent time in millions of years from the present time. Solid coloured lines represent mean empirical disparities through time, dashed lines represent mean BM-simulated disparities through time, shaded polygons display the space between 95% percentile and 5% percentiles of disparities through time for BM-simulated data. Colour code of individual subclade disparities (dots) as in Fig. 2.

Extended Data Fig. 10 Subclade disparity–age plots for the individual elements for Passeriformes (passerines).

X axes represent subclade disparities while y axes represent time in millions of years from the present time. Solid coloured lines represent mean empirical disparities through time, dashed lines represent mean BM-simulated disparities through time, shaded polygons display the space between 95% percentile and 5% percentiles of disparities through time for BM-simulated data. Colour code of individual subclade disparities (dots) as in Fig. 2.

Supplementary information

Supplementary Information

This file contains Supplementary Figs. 1–37 and References.

Reporting Summary

Peer Review File

Supplementary Table 1

List of specimens used in this study.

Supplementary Table 2

ANOVA tables used for proportions-normalizing individual elements.

Supplementary Table 3

Pairs of landmarks used to calculate maximum distances in each of the spatial axes.

Supplementary File 1

Bird_landmarks_Navalon_2022. Raw landmark coordinates for all specimens used in this study.

Supplementary File 2

Read_bird_landmarks_Navalon_2022. R code to read the raw landmarks coordinates in Supplementary File 1.

Supplementary File 3

Bird_processed_landmarks_Navalon_2022. Allometry-free and proportions free landmark coordinates for all specimens used in this study.

Supplementary File 4

Read_bird_processed_landmarks_Navalon_2022. R code to read the raw landmarks coordinates in Supplementary File 3.

Supplementary File 5

Combined phylogeny used in this study.

Supplementary File 6

Custom R functions used in this study.

Supplementary File 7

Custom R code used in this study.

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Navalón, G., Bjarnason, A., Griffiths, E. et al. Environmental signal in the evolutionary diversification of bird skeletons. Nature 611, 306–311 (2022). https://doi.org/10.1038/s41586-022-05372-y

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