Jablonski, D., Roy, K. & Valentine, J. W. Out of the tropics: evolutionary dynamics of the latitudinal diversity gradient. Science 314, 102–106 (2006).
Weir, J. T. & Schluter, D. The latitudinal gradient in recent speciation and extinction rates of birds and mammals. Science 315, 1574–1576 (2007).
Mittelbach, G. G. et al. Evolution and the latitudinal diversity gradient: speciation, extinction and biogeography. Ecol. Lett. 10, 315–331 (2007).
Simpson, G. G. The Major Features of Evolution (Columbia Univ. Press, 1953).
Simpson, G. G. Tempo and Mode in Evolution (Columbia Univ. Press, 1944).
Schluter, D. The Ecology of Adaptive Radiation (OUP Oxford, 2000).
Schluter, D. Speciation, ecological opportunity, and latitude. Am. Nat. 187, 1–18 (2016).
Quintero, I. The diffused evolutionary dynamics of morphological novelty. Proc. Natl Acad. Sci. USA 122, e2425573122 (2025).
Saupe, E. E. et al. Extinction intensity during Ordovician and Cenozoic glaciations explained by cooling and palaeogeography. Nat. Geosci. 13, 65–70 (2020).
Eiserhardt, W. L., Borchsenius, F., Plum, C. M., Ordonez, A. & Svenning, J.-C. Climate-driven extinctions shape the phylogenetic structure of temperate tree floras. Ecol. Lett. 18, 263–272 (2015).
Quintero, I. & Wiens, J. J. Rates of projected climate change dramatically exceed past rates of climatic niche evolution among vertebrate species. Ecol. Lett. 16, 1095–1103 (2013).
Weeks, B. C. et al. Skeletal trait measurements for thousands of bird species. Sci. Data 12, 884 (2025).
Weeks, B. C. et al. A deep neural network for high-throughput measurement of functional traits on museum skeletal specimens. Methods Ecol. Evol. 14, 347–359 (2023).
Oliveros, C. H. et al. Earth history and the passerine superradiation. Proc. Natl Acad. Sci. USA 116, 7916–7925 (2019).
Mayr, G. Paleogene Fossil Birds 2nd edn (Springer Cham, 2022).
Lowi-Merri, T. M., Gjevori, M., Bochenski, Z. M., Wertz, K. & Claramunt, S. Total-evidence dating and the phylogenetic affinities of early fossil passerines. J. Syst. Paleontol. 22, 2356086 (2024).
Steell, E. M., Nguyen, J. M. T., Benson, R. B. J. & Field, D. J. Comparative anatomy of the passerine carpometacarpus helps illuminate the early fossil record of crown Passeriformes. J. Anat. 242, 495–509 (2023).
Claramunt, S. et al. A new time tree of birds reveals the interplay between dispersal, geographic range size, and diversification. Curr. Biol. 35, 1–13 (2025).
Stiller, J. et al. Complexity of avian evolution revealed by family-level genomes. Nature 629, 851–860 (2024).
Grant, P. R. & Grant, B. R. Evolution of character displacement in Darwin’s finches. Science 313, 224–226 (2006).
Prum, R. O. The Evolution of Beauty: How Darwin’s Forgotten Theory of Mate Choice Shapes the Animal World-and Us (Anchor, 2018).
Ricklefs, R. E. Species richness and morphological diversity of passerine birds. Proc. Natl Acad. Sci. USA 109, 14482–14487 (2012).
Price, T. D. et al. Niche filling slows the diversification of Himalayan songbirds. Nature 509, 222–225 (2014).
Claramunt, S. & Cracraft, J. A new time tree reveals Earth history’s imprint on the evolution of modern birds. Sci. Adv. 1, e1501005 (2015).
Navalón, G., Bjarnason, A., Griffiths, E. & Benson, R. B. J. Environmental signal in the evolutionary diversification of bird skeletons. Nature 611, 306–311 (2022).
Brinkworth, A. et al. Bird clades with less complex appendicular skeletons tend to have higher species richness. Nat. Commun. 14, 5817 (2023).
Chitwood, D. H. et al. Latent developmental and evolutionary shapes embedded within the grapevine leaf. New Phytol. 210, 343–355 (2016).
Klingenberg, C. P. Size, shape, and form: concepts of allometry in geometric morphometrics. Dev. Genes Evol. 226, 113–137 (2016).
Wagner, G. P. Homology, Genes, and Evolutionary Innovation (Princeton Univ. Press, 2014).
Pavlicev, M. & Hansen, T. F. Genotype-phenotype maps maximizing evolvability: modularity revisited. Evol. Biol. 38, 371–389 (2011).
Cavalli-Sforza, L. L. & Edwards, A. W. F. Phylogenetic analysis: models and estimation procedures. Evolution 21, 550–570 (1967).
Lande, R. Natural selection and random genetic drift in phenotypic evolution. Evolution 30, 314–334 (1976).
Felsenstein, J. Phylogenies and quantitative characters. Annu. Rev. Ecol. Syst. 19, 445–471 (1988).
Clavel, J., Aristide, L. & Morlon, H. A penalized likelihood framework for high-dimensional phylogenetic comparative methods and an application to new-world monkeys brain evolution. Syst. Biol. 68, 93–116 (2019).
Clavel, J., Escarguel, G. & Merceron, G. mvMORPH: an R package for fitting multivariate evolutionary models to morphometric data. Methods Ecol. Evol. 6, 1311–1319 (2015).
Berv, J. S. et al. Genome and life-history evolution link bird diversification to the end-Cretaceous mass extinction. Sci. Adv. 10, eadp0114 (2024).
Smith, S. A., Walker-Hale, N. & Parins-Fukuchi, C. T. Compositional shifts associated with major evolutionary transitions in plants. New Phytol. 239, 2404–2415 (2023).
Mitov, V., Bartoszek, K. & Stadler, T. Automatic generation of evolutionary hypotheses using mixed Gaussian phylogenetic models. Proc. Natl Acad. Sci. USA 116, 16921–16926 (2019).
Coles, S. An Introduction to Statistical Modeling of Extreme Values (Springer, 2001).
Gould, S. J. & Eldredge, N. Punctuated equilibrium comes of age. Nature 366, 223–227 (1993).
Uyeda, J. C., Hansen, T. F., Arnold, S. J. & Pienaar, J. The million-year wait for macroevolutionary bursts. Proc. Natl Acad. Sci. USA 108, 15908–15913 (2011).
Landis, M. J. & Schraiber, J. G. Pulsed evolution shaped modern vertebrate body sizes. Proc. Natl Acad. Sci. USA 114, 13224–13229 (2017).
Wagner, G. P. & Altenberg, L. Perspective: complex adaptations and the evolution of evolvability. Evolution 50, 967–976 (1996).
Wagner, P. J. Early bursts of disparity and the reorganization of character integration. Proc. R. Soc. B 285, 20181604 (2018).
Gatesy, S. M. & Dial, K. P. Locomotor modules and the evolution of avian flight. Evolution 50, 331–340 (1996).
Losos, J. B. Adaptive radiation, ecological opportunity, and evolutionary determinism. Am. Nat. 175, 623–639 (2010).
Eldredge, N. & Gould, S. J. in Models in Paleobiology (ed. Schopf, T. J. M.) 82–115 (Freeman, Cooper and Company, 1972).
Malmgren, B. A., Berggren, W. A. & Lohmann, G. P. Evidence for punctuated gradualism in the Late Neogene Globorotalia tumida lineage of planktonic foraminifera. Paleobiology 9, 377–389 (1983).
Brennan, I. G., Chapple, D. G., Keogh, J. S. & Donnellan, S. Evolutionary bursts drive morphological novelty in the world’s largest skinks. Curr. Biol. 34, 3905–3916.e3905 (2024).
Dufour, P., Sayol, F., Steinbauer, M. J., Cooke, R. & Faurby, S. Niche filling predicts evolutionary trajectories in insular bird communities. Funct. Ecol. 38, 2636–2647 (2024).
Rabosky, D. L. & Lovette, I. J. Density-dependent diversification in North American wood warblers. Proc. R. Soc. B 275, 2363–2371 (2008).
Cooney, C. R. et al. Mega-evolutionary dynamics of the adaptive radiation of birds. Nature 542, 344–347 (2017).
Jønsson, K. A. et al. Ecological and evolutionary determinants for the adaptive radiation of the Madagascan vangas. Proc. Natl Acad. Sci. USA 109, 6620–6625 (2012).
Vinciguerra, N. T. & Burns, K. J. Species diversification and ecomorphological evolution in the radiation of tanagers (Passeriformes: Thraupidae). Biol. J. Linn. Soc. 133, 920–930 (2021).
Harmon, L. J. et al. Early bursts of body size and shape evolution are rare in comparative data. Evolution 64, 2385–2396 (2010).
Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).
Phillimore, A. B. & Price, T. D. Density-dependent cladogenesis in birds. PLoS Biol. 6, e71 (2008).
Derryberry, E. P. et al. Lineage diversification and morphological evolution in a large-scale continental radiation: the neotropical ovenbirds and woodcreepers (Aves: Furnariidae). Evolution 65, 2973–2986 (2011).
Pennell, M. W., FitzJohn, R. G., Cornwell, W. K. & Harmon, L. J. Model adequacy and the macroevolution of angiosperm functional traits. Am. Nat. 186, E33–E50 (2015).
Rabosky, D. L. et al. Rates of speciation and morphological evolution are correlated across the largest vertebrate radiation. Nat. Commun. 4, 1958 (2013).
Slater, G. J. Phylogenetic evidence for a shift in the mode of mammalian body size evolution at the Cretaceous-Palaeogene boundary. Methods Ecol. Evol. 4, 734–744 (2013).
Uyeda, J. C., Caetano, D. S. & Pennell, M. W. Comparative analysis of principal components can be misleading. Syst. Biol. 64, 677–689 (2015).
Westerhold, T. et al. An astronomically dated record of Earth’s climate and its predictability over the last 66 million years. Science 369, 1383–1387 (2020).
Zachos, J., Pagani, M., Sloan, L., Thomas, E. & Billups, K. Trends, rhythms, and aberrations in global climate 65 Ma to present. Science 292, 686–693 (2001).
Prothero, D. R. & Berggren, W. A. in Princeton Series in Geology and Paleontology 582 (Princeton Univ. Press, 1992).
Steinthorsdottir, M. et al. The Miocene: the future of the past. Paleoceanogr. Paleoclimatol. 36, e2020PA004037 (2021).
Clavel, J. & Morlon, H. Accelerated body size evolution during cold climatic periods in the Cenozoic. Proc. Natl Acad. Sci. USA 114, 4183–4188 (2017).
Selvatti, A. P., Gonzaga, L. P. & Russo, C. A.dM. A Paleogene origin for crown passerines and the diversification of the Oscines in the New World. Mol. Phylogenet. Evol. 88, 1–15 (2015).
Rohde, K. Latitudinal gradients in species diversity: the search for the primary cause. Oikos 65, 514–527 (1992).
Quintero, I., Landis, M. J., Jetz, W. & Morlon, H. The build-up of the present-day tropical diversity of tetrapods. Proc. Natl Acad. Sci. USA 120, e2220672120 (2023).
Pulido-Santacruz, P. & Weir, J. T. Extinction as a driver of avian latitudinal diversity gradients. Evolution 70, 860–872 (2016).
Jablonski, D. et al. Out of the tropics, but how? Fossils, bridge species, and thermal ranges in the dynamics of the marine latitudinal diversity gradient. Proc. Natl Acad. Sci. USA 110, 10487–10494 (2013).
Dimitrov, D. et al. Diversification of flowering plants in space and time. Nat. Commun. 14, 7609 (2023).
Rabosky, D. L. et al. An inverse latitudinal gradient in speciation rate for marine fishes. Nature 559, 392–395 (2018).
Harvey, M. G. et al. The evolution of a tropical biodiversity hotspot. Science 370, 1343–1348 (2020).
Upham, N. S., Esselstyn, J. A. & Jetz, W. Ecological causes of uneven mammal diversity. Preprint at bioRxiv https://doi.org/10.1101/504803 (2023).
Lawson, A. M. & Weir, J. T. Latitudinal gradients in climatic-niche evolution accelerate trait evolution at high latitudes. Ecol. Lett. 17, 1427–1436 (2014).
Weir, J. T. & Wheatcroft, D. A latitudinal gradient in rates of evolution of avian syllable diversity and song length. Proc. R. Soc. B 278, 1713–1720 (2011).
Burns, M. D. et al. High-latitude ocean habitats are a crucible of fish body shape diversification. Evol. Lett. 8, 669–679 (2024).
Tietje, M. et al. Global variation in diversification rate and species richness are unlinked in plants. Proc. Natl Acad. Sci. USA 119, e2120662119 (2022).
Adams, D. C., Berns, C. M., Kozak, K. H. & Wiens, J. J. Are rates of species diversification correlated with rates of morphological evolution? Proc. R. Soc. B. 276, 2729–2738 (2009).
Cracraft, J. Historical Biogeography and Patterns of Differentiation within the South American Avifauna: Areas of Endemism. Ornithol. Monogr. 36, 49–84 (1985).
Knowles, L. L. Did the Pleistocene glaciations promote divergence? Tests of explicit refugial models in montane grasshoppers. Mol. Ecol. 10, 691–701 (2001).
Venditti, C., Meade, A. & Pagel, M. Multiple routes to mammalian diversity. Nature 479, 393–396 (2011).
Hansen, T. F. Is modularity necessary for evolvability?: Remarks on the relationship between pleiotropy and evolvability. Biosystems 69, 83–94 (2003).
Smith, B. T., Gehara, M. & Harvey, M. G. The demography of extinction in eastern North American birds. Proc. R. Soc. B 288, 20201945 (2021).
Santini, L., Tobias, J. A., Callaghan, C., Gallego-Zamorano, J. & Benítez-López, A. Global patterns and predictors of avian population density. Glob. Ecol. Biogeogr. 32, 1189–1204 (2023).
Puttick, M. N., Guillerme, T. & Wills, M. A. The complex effects of mass extinctions on morphological disparity. Evolution 74, 2207–2220 (2020).
Hull, P. Life in the aftermath of mass extinctions. Curr. Biol. 25, R941–R952 (2015).
Cole, S. R. & Hopkins, M. J. Selectivity and the effect of mass extinctions on disparity and functional ecology. Sci. Adv. 7, eabf4072 (2021).
Clauset, A., Newman, M. E. & Moore, C. Finding community structure in very large networks. Phys. Rev. E 70, 066111 (2004).
Cantwell-Jones, A. et al. Mapping trait versus species turnover reveals spatiotemporal variation in functional redundancy and network robustness in a plant-pollinator community. Funct. Ecol. 37, 748–762 (2023).
Kashtan, N., Parter, M., Dekel, E., Mayo, A. E. & Alon, U. Extinctions in heterogeneous environments and the evolution of modularity. Evolution 63, 1964–1975 (2009).
Melo, D. & Marroig, G. Directional selection can drive the evolution of modularity in complex traits. Proc. Natl Acad. Sci. USA 112, 470–475 (2015).
Wagner, G. P., Pavlicev, M. & Cheverud, J. M. The road to modularity. Nat. Rev. Genet. 8, 921–931 (2007).
Parter, M., Kashtan, N. & Alon, U. Environmental variability and modularity of bacterial metabolic networks. BMC Evol. Biol. 7, 169 (2007).
Kashtan, N. & Alon, U. Spontaneous evolution of modularity and network motifs. Proc. Natl Acad. Sci. USA 102, 13773–13778 (2005).
Ronneberger, O., Fischer, P. & Brox, T. U-Net: convolutional networks for biomedical image segmentation. in Medical Image Computing and Computer-Assisted Intervention (eds Navab N., Hornegger J., Wells W. M., & Frangi A. F.). 234–241 (Springer, 2015).
He, K., Gkioxari, G., Dollár, P. & Girshick, R. Mask R-CNN. in 2017 IEEE International Conference on Computer Vision (eds.). 2980–2988 (2017).
Goolsby, E. W., Bruggeman, J. & Ané, C. Rphylopars: fast multivariate phylogenetic comparative methods for missing data and within-species variation. Methods Ecol. Evol. 8, 22–27 (2017).
Marki, P. Z. et al. Supermatrix phylogeny and biogeography of the Australasian Meliphagides radiation (Aves: Passeriformes). Mol. Phylogenet. Evol. 107, 516–529 (2017).
McCullough, J. M. et al. Wallacean and Melanesian Islands promote higher rates of diversification within the global passerine radiation Corvides. Syst. Biol. 71, 1423–1439 (2022).
Cai, T. et al. Near-complete phylogeny and taxonomic revision of the world’s babblers (Aves: Passeriformes). Mol. Phylogenet. Evol. 130, 346–356 (2019).
Alström, P. et al. Systematics of the avian family Alaudidae using multilocus and genomic data. Avian Res. 14, 100095 (2023).
Shakya, S. B. & Sheldon, F. H. The phylogeny of the world’s bulbuls (Pycnonotidae) inferred using a supermatrix approach. Ibis 159, 498–509 (2017).
De Silva, T. N., Peterson, A. T. & Perktas, U. An extensive molecular phylogeny of weaverbirds (Aves: Ploceidae) unveils broad nonmonophyly of traditional genera and new relationships. Auk 136, ukz041 (2019).
Olsson, U. & Alström, P. A comprehensive phylogeny and taxonomic evaluation of the waxbills (Aves: Estrildidae). Mol. Phylogenet. Evol. 146, 106757 (2020).
Barker, F. K., Burns, K. J., Klicka, J., Lanyon, S. M. & Lovette, I. J. New insights into New World biogeography: an integrated view from the phylogeny of blackbirds, cardinals, sparrows, tanagers, warblers, and allies. Auk 132, 333–348 (2015).
Baum, B. R. Combining trees as a way of combining data sets for phylogenetic inference, and the desirability of combining gene trees. Taxon 41, 3–10 (1992).
Ragan, M. A. Phylogenetic inference based on matrix representation of trees. Mol. Phylogenet. Evol. 1, 53–58 (1992).
Schliep, K. P. phangorn: phylogenetic analysis in R. Bioinformatics 27, 592–593 (2011).
Weeks, B. C. et al. Shared morphological consequences of global warming in North American migratory birds. Ecol. Lett. 23, 316–325 (2020).
Eastman, J. M., Harmon, L. J. & Tank, D. C. Congruification: support for time scaling large phylogenetic trees. Methods Ecol. Evol. 4, 688–691 (2013).
Smith, S. A. & O’Meara, B. C. treePL: divergence time estimation using penalized likelihood for large phylogenies. Bioinformatics 28, 2689–2690 (2012).
Claramunt, S. et al. Calibrating the genomic clock of modern birds using fossils. Proc. Natl Acad. Sci. USA 121, e2405887121 (2024).
Claramunt, S. CladeDate: calibration information generator for divergence time estimation. Methods Ecol. Evol. 13, 2331–2338 (2022).
Parham, J. F. et al. Best practices for justifying fossil calibrations. Syst. Biol. 61, 346–359 (2012).
Prum, R. O. et al. A comprehensive phylogeny of birds (Aves) using targeted next-generation DNA sequencing. Nature 526, 569–573 (2015).
Jarvis, E. D. et al. Whole-genome analyses resolve early branches in the tree of life of modern birds. Science 346, 1320–1331 (2014).
Kimball, R. T. et al. A phylogenomic supertree of birds. Diversity 11, 109 (2019).
Felsenstein, J. Phylogenies and the comparative method. Am. Nat. 125, 1–15 (1985).
Hansen, T. F. & Martins, E. P. Translating between microevolutionary process and macroevolutionary patterns: the correlation structure of interspecific data. Evolution 50, 1404–1417 (1996).
Hansen, T. F. Stabilizing selection and the comparative analysis of adaptation. Evolution 51, 1341–1351 (1997).
Blomberg, S. P., Garland, T. Jr. & Ives, A. R. Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution 57, 717–745 (2003).
Jablonski, D. Background and mass extinctions: the alternation of macroevolutionary regimes. Science 231, 129–133 (1986).
O’Meara, B. C., Ané, C., Sanderson, M. J. & Wainwright, P. C. Testing for different rates of continuous trait evolution using likelihood. Evolution 60, 922–933 (2006).
Rabosky, D. L. Automatic detection of key innovations, rate shifts, and diversity-dependence on phylogenetic trees. PLoS ONE 9, e89543 (2014).
Uyeda, J. C., Zenil-Ferguson, R. & Pennell, M. W. Rethinking phylogenetic comparative methods. Syst. Biol. 67, 1091–1109 (2018).
Eastman, J. M., Alfaro, M. E., Joyce, P., Hipp, A. L. & Harmon, L. J. A novel comparative method for identifying shifts in the rate of character evolution on trees. Evolution 65, 3578–3589 (2011).
Revell, L. J., Mahler, D. L., Peres-Neto, P. R. & Redelings, B. D. A new phylogenetic method for identifying exceptional phenotypic diversification. Evolution 66, 135–146 (2012).
Uyeda, J. C. & Harmon, L. J. A novel Bayesian method for inferring and interpreting the dynamics of adaptive landscapes from phylogenetic comparative data. Syst. Biol. 63, 902–918 (2014).
Beaulieu, J. M., Jhwueng, D.-C., Boettiger, C. & O’Meara, B. C. Modeling stabilizing selection: expanding the Ornstein-Uhlenbeck model of adaptive evolution. Evolution 66, 2369–2383 (2012).
Landis, M. J., Schraiber, J. G. & Liang, M. Phylogenetic analysis using Lévy processes: finding jumps in the evolution of continuous traits. Syst. Biol. 62, 193–204 (2013).
Thomas, G. H. & Freckleton, R. P. MOTMOT: models of trait macroevolution on trees. Methods Ecol. Evol. 3, 145–151 (2012).
Khabbazian, M., Kriebel, R., Rohe, K. & Ané, C. Fast and accurate detection of evolutionary shifts in Ornstein–Uhlenbeck models. Methods Ecol. Evol. 7, 811–824 (2016).
Ingram, T. & Mahler, D. L. SURFACE: detecting convergent evolution from comparative data by fitting Ornstein-Uhlenbeck models with stepwise Akaike information criterion. Methods Ecol. Evol. 4, 416–425 (2013).
Bastide, P., Mariadassou, M. & Robin, S. Detection of adaptive shifts on phylogenies by using shifted stochastic processes on a tree. J. R. Stat. Soc. B 79, 1067–1093 (2017).
Revell, L. J. & Harmon, L. J. A discrete character evolution model for phylogenetic comparative biology with Γ-distributed rate heterogeneity among branches of the tree. Preprint at bioRxiv https://doi.org/10.1101/2024.05.25.595896 (2024).
Uyeda, J. C., Pennell, M. W., Miller, E. T., Maia, R. & McClain, C. R. The evolution of energetic scaling across the vertebrate tree of life. Am. Nat. 190, 185–199 (2017).
Bastide, P., Ané, C., Robin, S. & Mariadassou, M. Inference of adaptive shifts for multivariate correlated traits. Syst. Biol. 67, 662–680 (2018).
Bartoszek, K. et al. Fast mvSLOUCH: multivariate Ornstein–Uhlenbeck-based models of trait evolution on large phylogenies. Methods Ecol. Evol. 15, 1507–1515 (2024).
Gould, S. J., Lewontin, R. C., Maynard Smith, J. & Holliday, R. The spandrels of San Marco and the Panglossian paradigm: a critique of the adaptationist programme. Proc. R. Soc. Lond. B 205, 581–598 (1979).
Revell, L. J. Size-correction and principal components for interspecific comparative studies. Evolution 63, 3258–3268 (2009).
Bishop, C. M. Pattern Recognition and Machine Learning (Springer, 2006).
Clavel, J. & Morlon, H. Reliable phylogenetic regressions for multivariate comparative data: illustration with the MANOVA and application to the effect of diet on mandible morphology in phyllostomid bats. Syst. Biol. 69, 927–943 (2020).
Alfaro, M. E. et al. Nine exceptional radiations plus high turnover explain species diversity in jawed vertebrates. Proc. Natl Acad. Sci. USA 106, 13410–13414 (2009).
Phillips, P. C. & Arnold, S. J. Hierarchical comparison of genetic variance-covariance matrices. I. Using the Flury hierarchy. Evolution 53, 1506–1515 (1999).
Stepanova, N., Boyko, J. D., Lin, J., Davis Rabosky, A. R. & Rabosky, D. L. Punctuated versus gradual shifts in the multivariate evolutionary process: a test with paired radiations of scincid lizards. Syst. Biol. 74, 1–17 (2025).
Mahler, D. L., Revell, L. J., Glor, R. E. & Losos, J. B. Ecological opportunity and the rate of morphological evolution in the diversification of Greater Antillean anoles. Evolution 64, 2731–2745 (2010).
Konishi, S. & Kitagawa, G. Generalised information criteria in model selection. Biometrika 83, 875–890 (1996).
Schwarz, G. Estimating the dimension of a model. Ann. Stat. 6, 461–464 (1978).
Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).
Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach 2nd edn, Vol. 2 (Springer-Verlag, 2002).
Burnham, K. P. & Anderson, D. R. Multimodel inference: understanding AIC and BIC in model selection. Sociol. Methods Res. 33, 261–304 (2004).
Berv, J. S. et al. Supplementary code for: Rates of passerine body plan evolution in time and space. v1.0.0. Zenodo https://doi.org/10.5281/zenodo.19211076 (2026).
Spence, A. J. Scaling in biology. Curr. Biol. 19, R57–R61 (2009).
Wilcoxon, F. Individual comparisons by ranking methods. Biom. Bull. 1, 80–83 (1945).
Kolmogorov, A. N. Sulla determinazione empírica di uma legge di distribuzione. G. Ist. Ital. Attuari 4, 83–91 (1933).
Smirnov, N. Table for estimating the goodness of fit of empirical distributions. Ann. Math. Stat. 19, 279–281, 273 (1948).
Marsaglia, G., Tsang, W. W. & Wang, J. Evaluating Kolmogorov’s distribution. J. Stat. Softw. 8, 1–4 (2003).
Moss, J. univariateML: An R package for maximum likelihood estimation of univariate densities. J. Open Source Softw. 4, 1863 (2019).
Title, P. O. et al. The macroevolutionary singularity of snakes. Science 383, 918–923 (2024).
BirdLife International & Handbook of the Birds of the World. Bird Species Distribution Maps of the World. Version 2021.1 edn (BirdLife International, 2021).
Pebesma, E. Simple features for R: standardized support for spatial vector data. R J. 10, 439–446 (2018).
Pebesma, E. & Bivand, R. Spatial Data Science: With Applications in R. (Chapman and Hall/CRC, 2023).
H3: A Hexagonal Hierarchical Geospatial Indexing System (Uber Technologies, 2018).
O’Brien, L. h3jsr: Access Uber’s H3 Library (CRAN, 2024).
GBIF Secretariat. GBIF Backbone Taxonomy. Checklist dataset edn (GBIF Secretariat, 2023).
Redding, D. W. & Mooers, A. O. Incorporating evolutionary measures into conservation prioritization. Conserv. Biol. 20, 1670–1678 (2006).
Ord, K. Estimation methods for models of spatial interaction. J. Am. Stat. Assoc. 70, 120–126 (1975).
Bivand, R. & Piras, G. Comparing implementations of estimation methods for spatial econometrics. J. Stat. Softw. 63, 1–36 (2015).
Bivand, R., Hauke, J. & Kossowski, T. Computing the Jacobian in Gaussian spatial autoregressive models: an illustrated comparison of available methods. Geogr. Anal. 45, 150–179 (2013).
Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).
Shepard, D. A two-dimensional interpolation function for irregularly-spaced data. In Proc. 1968 23rd ACM National Conference, 517–524 (Association for Computing Machinery, 1968).
Moran, P. A. P. Notes on continuous stochastic phenomena. Biometrika 37, 17–23 (1950).
Willis, K. J. et al. The tempo of avian diversification during the Quaternary. Phil. Trans. R. Soc. Lond. B 359, 215–220 (2004).
Lovette, I. J. Glacial cycles and the tempo of avian speciation. Trends Ecol. Evol. 20, 57–59 (2005).
Nadachowska-Brzyska, K., Li, C., Smeds, L., Zhang, G. & Ellegren, H. Temporal dynamics of avian populations during Pleistocene revealed by whole-genome sequences. Curr. Biol. 25, 1375–1380 (2015).
Weir, J. T. & Schluter, D. Ice sheets promote speciation in boreal birds. Proc. R. Soc. Lond. B 271, 1881–1887 (2004).
Jablonski, D. Lessons from the past: evolutionary impacts of mass extinctions. Proc. Natl Acad. Sci. USA 98, 5393–5398 (2001).
Atchley, W. R. M-Statistics and morphometric divergence. Science 208, 1059–1060 (1980).
Huttegger, S. M. & Mitteroecker, P. Invariance and meaningfulness in phenotype spaces. Evol. Biol. 38, 335–351 (2011).
Csardi, G. & Nepusz, T. The igraph software package for complex network research. InterJ. Complex Syst. 1695, 1–9 (2006).
Schuurman, T. & Bruner, E. Modularity and community detection in human brain morphology. Anat. Rec. 307, 345–355 (2024).
Padi, M. & Quackenbush, J. Detecting phenotype-driven transitions in regulatory network structure. npj Syst. Biol. Appl. 4, 16 (2018).
Adams, D. C. A generalized K statistic for estimating phylogenetic signal from shape and other high-dimensional multivariate data. Syst. Biol. 63, 685–697 (2014).
Collyer, M. L., Baken, E. K. & Adams, D. C. A standardized effect size for evaluating and comparing the strength of phylogenetic signal. Methods Ecol. Evol. 13, 367–382 (2022).
Baken, E. K., Collyer, M. L., Kaliontzopoulou, A. & Adams, D. C. geomorph v4.0 and gmShiny: enhanced analytics and a new graphical interface for a comprehensive morphometric experience. Methods Ecol. Evol. 12, 2355–2363 (2021).
Benjamini, Y. & Yekutieli, D. The control of the false discovery rate in multiple testing under dependency. Ann. Stat. 29, 1165–1188 (2001).
Berv, J. et al. Supplementary data archive for Rates of passerine body plan evolution in time and space. v1.0.0. Zenodo https://doi.org/10.5281/zenodo.19198393 (2026).
Berv, J. S. et al. bifrost: an R package for scalable inference of phylogenetic shifts in multivariate evolutionary dynamics. Preprint at bioRxiv https://doi.org/10.64898/2026.04.12.718036 (2026).