References
Ackerly, D. 2009. Conservatism and diversification of plant functional traits: Evolutionary rates versus phylogenetic signal. Proc. Natl. Acad. Sci. 106: 19699–19706.
Adams, D. C. 2014. Quantifying and comparing phylogenetic evolutionary rates for shape and other high-dimensional phenotypic data. Syst. Biol. 63: 166–177.
Anderson, P. S. L., Friedman, M., Ruta, M. 2013. Late to the table: Diversification of tetrapod mandibular biomechanics lagged behind the evolution of terrestriality. Integr. Comp. Biol. 53: 197–208.
Ausich, W. I., Wright, D. F., Cole, S. R., Sevastopulo, G. D. 2020. Homology of posterior interray plates in crinoids: A review and new perspectives from phylogenetics, the fossil record and development. Palaeontology. 63: 525–545.
Bapst, D. W. 2012. Paleotree: An R package for paleontological and phylogenetic analyses of evolution. Methods Ecol. Evol. 3: 803–807.
Bapst, D. W. 2013a. A stochastic rate-calibrated method for time-scaling phylogenies of fossil taxa. Methods Ecol. Evol. 4: 724–733.
Bapst, D. W. 2013b. When can clades be potentially resolved with morphology? PLoS One. 8: e62312.
Bapst, D. W. 2014a. Assessing the effect of time-scaling methods on phylogeny-based analyses in the fossil record. Paleobiology. 40: 331–351.
Bapst, D. W. 2014b. Preparing palaeontological datasets for phylogenetic comparative methods. In: Garamszegi, L. Z., editor. Modern phylogenetic comparative methods and their application in evolutionary biology. Berlin, Heidelberg: Springer-Verlag. pp. 515–544.
Bapst, D. W., Hopkins, M. J. 2017. Comparing cal3 and other a posteriori time-scaling approaches in a case study with the pterocephaliid trilobites. Paleobiology. 43: 49–67.
Barido-Sottani, J., Pett, W., O’Reilly, J. E., Warnock, R. C. M. 2019. FossilSim: An R package for simulating fossil occurrence data under mechanistic models of preservation and recovery. Methods Ecol. Evol. 10: 835–840.
Barido-Sottani, J., Saupe, E., Smiley, T. M., Soul, L. C., Wright, A. M., Warnock, R. C. M. 2020. Seven rules for simulations in paleobiology. Paleobiology. 46(4): 435–444.
Barido-Sottani, J., Tiel, N. van, Hopkins, M. J., Wright, D. F., Stadler, T., Warnock, R. C. M. 2020. Ignoring fossil age uncertainty leads to inaccurate topology and divergence times in time calibrated tree inference. Frontiers in Ecology and Evolution, 8: 183
Baum, D. A., Smith, S. D. 2013. Tree thinking: An introduction to phylogenetic biology. Greenwood Village, CO: Roberts.
Benson, R. B. J., Choiniere, J. N. 2013. Rates of dinosaur limb evolution provide evidence for exceptional radiation in Mesozoic birds. Proc. R. Soc. B Biol. Sci. 280: 20131780.
Blomberg, S. P., Garland, T., Ives, A. R. 2003. Testing for phylogenetic signal in comparative data: Behavioral traits are more labile. Evolution. 57: 717–745.
Blomberg, S. P., Rathnayake, S. I., Moreau, C. M. 2020. Beyond Brownian motion and the Ornstein-Uhlenbeck process: Stochastic diffusion models for the evolution of quantitative characters. Am. Nat. 195: 145–165.
Blomberg, S. P., Lefevre, J. G., Wells, J. A., Waterhouse, M. 2012. Independent contrasts and PGLS regression estimators are equivalent. Syst. Biol. 61: 382–391.
Boettiger, C., Coop, G., Ralph, P. 2012. Is your phylogeny informative? Measuring the power of comparative methods. Evolution. 66: 2240–2251.
Boucher, F. C., Démery, V., Conti, E., Harmon, L. J., Uyeda, J. 2018. A general model for estimating macroevolutionary landscapes. Syst. Biol. 67: 304–319.
Brocklehurst, N., Brink, K. S. 2017. Selection towards larger body size in both herbivorous and carnivorous synapsids during the Carboniferous. Facets. 2: 68–84.
Butler, M. A., King, A. A. 2004. Phylogenetic comparative analysis: A modeling approach for adaptive evolution. Am. Nat. 164: 683–695.
Button, D. J., Barrett, P. M., Rayfield, E. J. 2017. Craniodental functional evolution in sauropodomorph dinosaurs. Paleobiology. 43: 435–462.
Clarke, J. T., Lloyd, G. T., Friedman, M. 2016. Little evidence for enhanced phenotypic evolution in early teleosts relative to their living fossil sister group. Proc. Natl. Acad. Sci. 113: 11531–11536.
Close, R. A., Friedman, M., Lloyd, G. T., Benson, R. B. J. 2015. Evidence for a mid-Jurassic adaptive radiation in mammals. Curr. Biol. 25: 2137–2142.
Cole, S. R., Wright, D. F., Ausich, W. I. 2019. Phylogenetic community paleoecology of one of the earliest complex crinoid faunas (Brechin Lagerstätte, Ordovician). Palaeogeogr. Palaeoclimatol. Palaeoecol. 521: 82–98.
Cooper, N., Thomas, G. H., FitzJohn, R. G. 2016. Shedding light on the “dark side” of phylogenetic comparative methods. Methods Ecol. Evol. 7: 693–699.
Darwin, C. R. 1859. On the origin of species by means of natural selection. London: John Murray.
Diniz-Filho, J. A. F., Alves, D. M. C. C., Villalobos, F., Sakamoto, M., Brusatte, S. L., Bini, L. M. 2015. Phylogenetic eigenvectors and nonstationarity in the evolution of theropod dinosaur skulls. J. Evol. Biol. 28: 1410–1416.
Drury, J., Clavel, J., Manceau, M., Morlon, H. 2016. Estimating the effect of competition on trait evolution using maximum likelihood inference. Syst. Biol. 65: 700–710.
Eastman, J. M., Alfaro, M. E., Joyce, P., Hipp, A. L., Harmon, L. J. 2011. A novel comparative method for identifying shifts in the rate of character evolution on trees. Evolution. 65: 3578–3589.
Erwin, D. H. 2007. Disparity: Morphological pattern and developmental context. Palaeontology. 50: 57–73.
Felsenstein, J. 1985. Phylogenies and the comparative method. Am. Nat. 125: 1–15.
Finarelli, J. A., Flynn, J. J. 2006. Ancestral state reconstruction of body size in the Caniformia (Carnivora, Mammalia): The effects of incorporating data from the fossil record. Syst. Biol. 55: 301–313.
Foote, M. 1996. On the probability of ancestors in the fossil record. Paleobiology. 22: 141–151.
Freckleton, R. P. 2009. The seven deadly sins of comparative analysis. J. Evol. Biol. 22: 1367–1375.
Garamszegi, L. Z. 2014. Modern phylogenetic comparative methods and their application in evolutionary biology. Berlin, Heidelberg: Springer-Verlag.
Garland, T., Ives, A. R. 2000. Using the past to predict the present: Confidence intervals for regression equations in phylogenetic comparative methods. Am. Nat. 155: 346–364.
Gascuel, O., Steel, M. 2014. Predicting the ancestral character changes in a tree is typically easier than predicting the root state. Syst. Biol. 63: 421–435.
Gavryushkina, A., Welch, D., Stadler, T., Drummond, A. 2014. Bayesian inference of sampled ancestor trees for epidemiology and fossil calibration. PLoS Comput. Biol. 10: e1003919.
Gavryushkina, A., Heath, T. A., Ksepka, D. T., Stadler, T., Welch, D., Drummond, A. J. 2017. Bayesian total-evidence dating reveals the recent crown radiation of penguins. Syst. Biol. 66: 57–73.
Gearty, W., Payne, J. L. 2020. Physiological constraints on body size distributions in Crocodyliformes. Evolution. 74: 245–255.
Halliday, T. J. D., Goswami, A. 2016. The impact of phylogenetic dating method on interpreting trait evolution: A case study of Cretaceous-Palaeogene eutherian body-size evolution. Biol. Lett. 12: 6–12.
Hansen, T. F. 1997. Stabilising selection and the comparative analysis of adaptation. Evolution. 51: 1342–1351.
Hansen, T. F., Martins, E. P. 1996. Translating between microevolutionary process and macroevolutionary patterns: The correlation structure of interspecific data. Evolution. 50: 1404–1417.
Harmon, Luke. 2019. “Phylogenetic Comparative Methods: Learning from Trees.” EcoEvoRxiv. May 20. doi:10.32942/osf.io/e3xnr. Harmon, L. J., Weir, J. T., Brock, C. D., Glor, R. E., Challenger, W. 2008. GEIGER: Investigating evolutionary radiations. Bioinformatics. 24: 129–131.
Harmon, L. J., Losos, J. B., Davies, T. J., Gillespie, R. G., Gittleman, J. L., Jennings, B. W., Kozak, K. H., McPeek, M. A., Moreno-Roark, F., Near, T. J., Purvis, A., Ricklefs, R. E., Schluter, D., Schulte, II J. A., Seehausen, O., Sidlauskas, B. L., Torres-Carvajal, O., Weir, J. T., Mooers, A. Ø. 2010. Early bursts of body size and shape evolution are rare in comparative data. Evolution. 64: 2385–2396.
Harrison, L. B., Larsson, H. C. E. 2015. Among-character rate variation distributions in phylogenetic analysis of discrete morphological characters. Syst. Biol. 64: 307–324.
Harvey, P. H., Read, A. F., Nee, S. 1995. Further remarks on the role of phylogeny in comparative ecology. J. Ecol. 83: 733.
Heath, T. A., Huelsenbeck, J. P., Stadler, T. 2014. The fossilized birth–death process for coherent calibration of divergence-time estimates. Proc. Natl. Acad. Sci. 111: E2957–E2966.
Hedman, M. M. 2010. Constraints on clade ages from fossil outgroups. Paleobiology. 36: 16–31.
Ho, L. S. T., Ané, C. 2014a. A linear-time algorithm for Gaussian and non-Gaussian trait evolution models. Syst. Biol. 63: 397–408.
Ho, L. S. T., Ané, C. 2014b. Intrinsic inference difficulties for trait evolution with Ornstein-Uhlenbeck models. Methods Ecol. Evol. 5: 1133–1146.
Hopkins, M. J., Smith, A. B. 2015. Dynamic evolutionary change in post-Paleozoic echinoids and the importance of scale when interpreting changes in rates of evolution. Proc. Natl. Acad. Sci. U.S.A. 112: 3758–3763.
Hunt, G. 2012. Measuring rates of phenotypic evolution and the inseparability of tempo and mode. Paleobiology. 38: 351–373.
Hunt, G. 2013. Testing the link between phenotypic evolution and speciation: An integrated palaeontological and phylogenetic analysis. Methods Ecol. Evol. 4: 714–723.
Hunt, G., Carrano, M. T. 2010. Models and methods for analyzing phenotypic evolution in lineages and clades. Paleontol. Soc. Pap. 16: 245–269.
Hunt, G., Slater, G. 2016. Integrating paleontological and phylogenetic approaches to macroevolution. Annu. Rev. Ecol. Evol. Syst. 47: 189–213.
Kammer, T. W. 2008. Paedomorphosis as an adaptive response in pinnulate cladid crinoids from the Burlington limestone (Mississippian, Oseadean) of the Mississippi Valley. In: Webster, G. D., Maples, C. D., editors. Echinoderm paleobiology. Bloomington, IN: University of Indiana Press. pp. 177–195.
Lande, R. 1976. Natural selection and random genetic drift in phenotypic evolution. Evolution. 30: 314.
Landis, M. J. 2017. Biogeographic dating of speciation times using paleogeographically informed processes. Syst. Biol. 64: 307–324.
Landis, M., Schraiber, J. G. 2017. Pulsed evolution shaped modern vertebrate diversity. Proc. Natl. Acad. Sci. U.S.A. 114: 13224–13229.
Lewis, P. O. 2001. A likelihood approach to estimating phylogeny from discrete morphological character data. Syst. Biol. 50: 913–925.
Lloyd, G. T. 2016. Estimating morphological diversity and tempo with discrete character-taxon matrices: Implementation, challenges, progress, and future directions. Biol. J. Linn. Soc. 118: 131–151.
Lloyd, G. T., Wang, S. C., Brusatte, S. L. 2012. Identifying heterogeneity in rates of morphological evolution: Discrete character change in the evolution of lungfish (Sarcopterygii; Dipnoi). Evolution. 66: 330–348.
Manceau, M., Lambert, A., Morlon, H. 2017. A unifying comparative phylogenetic framework including traits coevolving across interacting lineages. Syst. Biol. 66: 551–568.
Matzke, N. J., Wright, A. 2016. Inferring node dates from tip dates in fossil Canidae: The importance of tree priors. Biol. Lett. 12: 1–4.
Mitov, V., Bartoszek, K., Stadler, T. 2019. Automatic generation of evolutionary hypotheses using mixed Gaussian phylogenetic models. Proc. Natl. Acad. Sci. 116: 16921–16926.
Morlon, H., Lewitus, E., Condamine, F. L., Manceau, M., Clavel, J., Drury, J. 2016. RPANDA: An R package for macroevolutionary analyses on phylogenetic trees. Methods Ecol. Evol. 7: 589–597.
Nielsen, R. 2002. Mapping mutations on phylogenies. Syst. Biol. 51: 729–739.
Nunn, C. L. 2011. The comparative approach in evolutionary anthropology and biology. Chicago: University of Chicago Press.
Nunn, C. L., Barton, R. A. 2001. Comparative methods for studying primate adaptation and allometry. Evol. Anthropol. 10: 81–98.
O’Meara, B. C., Ané, C., Sanderson, M. J., Wainwright, P. C. 2006. Testing for different rates of continuous trait evolution using likelihood. Evolution. 60: 922–933.
O’Reilly, J. E., Puttick, M. N., Parry, L., Tanner, A. R., Tarver, J. E., Fleming, J., Pisani, D., Donoghue, P. C. J. 2016. Bayesian methods outperform parsimony but at the expense of precision in the estimation of phylogeny from discrete morphological data. Biol. Lett. 12: 20160081.
Paradis, E., Claude, J., Strimmer, K. 2004. APE: Analyses of phylogenetics and evolution in R language. Bioinformatics. 20: 289–290.
Parins-Fukuchi, C. 2020. Detecting mosaic patterns in macroevolutionary disparity. Am. Nat. 195: 129–144.
Pennell, M. W., Fitzjohn, R. G., Cornwell, W. K., Harmon, L. J. 2015. Model adequacy and the macroevolution of angiosperm functional traits. Am. Nat. 186: E33–E50.
Pennell, M. W., Eastman, J. M., Slater, G. J., Brown, J. W., Uyeda, J. C., FitzJohn, R. G., Alfaro, M. E., Harmon, L. J. 2014. Geiger V2.0: An expanded suite of methods for fitting macroevolutionary models to phylogenetic trees. Bioinformatics. 30: 2216–2218.
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. 2019. nlme: Linear and nonlinear mixed effects models. R package version 3: 1–140.
Polly, P. D. 2019. Spatial processes and evolutionary models: A critical review. Palaeontology. 62: 175–195.
Price, S. A., Friedman, S. T., Wainwright, P. C. 2015. How predation shaped fish: The impact of fin spines on body form evolution across teleosts. Proc. R. Soc. B Biol. Sci. 282. https://doi.org/10.1098/rspb.2015.1428. Puttick, M. N. 2016. Partially incorrect fossil data augment analyses of discrete trait evolution in living species. Biol. Lett. 12: 20160392.
Puttick, M. N., Ingram, T., Clarke, M., Thomas, G. H. 2020. MOTMOT: Models of trait macroevolution on trees (an update). Methods Ecol. Evol. 11: 464–471.
Puttick, M. N., O’Reilly, J. E., Pisani, D., Donoghue, P. C. J. 2019. Probabilistic methods outperform parsimony in the phylogenetic analysis of data simulated without a probabilistic model. Palaeontology. 62: 1–17.
Revell, L.J. (2010), Phylogenetic signal and linear regression on species data. Methods in Ecology and Evolution, 1: 319–329.
Revell, L. J. 2012. phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3: 217–223.
Revell, L. J. 2013. Two new graphical methods for mapping trait evolution on phylogenies. Methods Ecol. Evol. 4: 754–759.
Revell, L. J. 2014. Ancestral character estimation under the threshold model from quantitative genetics. Evolution. 68: 743–759.
Revell, L. J., Schliep, K., Valderrama, E., Richardson, J. E. 2018. Graphs in phylogenetic comparative analysis: Anscombe’s quartet revisited. Methods Ecol. Evol. 9: 2145–2154.
Rohlf, F. J. 2006. A comment on phylogenetic correction. Evolution. 60: 1509.
Ruta, M., Krieger, J., Angielczyk, K. D., Wills, M. A. 2019. The evolution of the tetrapod humerus: Morphometrics, disparity, and evolutionary rates. Earth Environ. Sci. Trans. R. Soc. Edinburgh. 109: 351–369.
Sallan, L., Friedman, M., Sansom, R. S., Bird, C. M., Sansom, I. J. 2018. The nearshore cradle of early vertebrate diversification. Science. 464: 460–464.
Silvestro, D., Kostikova, A., Litsios, G., Pearman, P. B., Salamin, N. 2015. Measurement errors should always be incorporated in phylogenetic comparative analysis. Methods Ecol. Evol. 6: 340–346.
Simpson, G. G. 1944. Tempo and mode in evolution. New York: Columbia University Press.
Slater, G. J. 2013. Phylogenetic evidence for a shift in the mode of mammalian body size evolution at the Cretaceous-Palaeogene boundary. Methods Ecol. Evol. 4: 734–744.
Slater, G. J. 2014. Correction to “Phylogenetic evidence for a shift in the mode of mammalian body size evolution at the Cretaceous-Palaeogene boundary,” and a note on fitting macroevolutionary models to comparative paleontological data sets. Methods Ecol. Evol. 5: 714–718.
Slater, G. J., Pennell, M. W. 2014. Robust regression and posterior predictive simulation increase power to detect early bursts of trait evolution. Syst. Biol. 63: 293–308.
Slater, G. J., Harmon, L. J., Alfaro, M. E. 2012. Integrating fossils with molecular phylogenies improves inference of trait evolution. Evolution. 66: 3931–3944.
Soul, L. C., Benson, R. B. J. 2017. Developmental mechanisms of macroevolutionary change in the tetrapod axis: A case study of Sauropterygia. Evolution. 71: 1164–1177.
Soul, L. C., Friedman, M. 2015. Taxonomy and phylogeny can yield comparable results in comparative palaeontological analyses. Syst. Biol. 64: 608–620.
Soul, L. C., Friedman, M. 2017. Bias in phylogenetic measurements of extinction and a case study of end-Permian tetrapods. Palaeontology. 60: 169–185.
Speed, M. P., Arbuckle, K. 2017. Quantification provides a conceptual basis for convergent evolution. Biol. Rev. 92: 815–829.
Stadler, T. 2010. Sampling-through-time in birth-death trees. J. Theor. Biol. 267: 396–404.
Stadler, T., Gavryushkina, A., Warnock, R. C. M., Drummond, A. J., Heath, T. A. 2018. The fossilized birth-death model for the analysis of stratigraphic range data under different speciation modes. J. Theor. Biol. 447: 41–55.
Stayton, C. T. 2015. The definition, recognition, and interpretation of convergent evolution, and two new measures for quantifying and assessing the significance of convergence. Evolution. 69: 2140–2153.
Thomas, G. H., Freckleton, R. P. 2012. MOTMOT: Models of trait macroevolution on trees. Methods Ecol. Evol. 3: 145–151.
Uyeda, J. C., Zenil-Ferguson, R., Pennell, M. W. 2018. Rethinking phylogenetic comparative methods. Syst. Biol. 67: 1091–1109.
Voje, K. L., Starrfelt, J., Liow, L. H. 2018. Model adequacy and microevolutionary explanations for stasis in the fossil record. Am. Nat. 191: 509–523.
Wagner, P. J. 2012. Modelling rate distributions using character compatibility: implications for morphological evolution among fossil invertebrates. Biol. Lett. 8: 143–146.
Wagner, P. J., Marcot, J. D. 2010. Probabilistic phylogenetic inference in the fossil record: current and future applications. Paleontol. Soc. Pap. 16: 189–211.
Wagner, P.J. and Marcot, J.D., 2013. Modelling distributions of fossil sampling rates over time, space and taxa: assessment and implications for macroevolutionary studies. Methods in Ecology and Evolution, 4(8), pp.703–713.
Wesley-Hunt, G. D. 2005. The morphological diversification of carnivores in North America. Paleobiology. 31: 35–55.
Westoby, M., Leishman, M., Lord, J. 2016. Further remarks on phylogenetic correction. J. Ecol. 83: 727–729.
Wiley, E. O., Lieberman, B. S. 2011. Phylogenetics: Theory and practice of phylogenetic systematics. New York: John Wiley & Sons.
Wright, A. M. 2019. A systematist’s guide to estimating Bayesian phylogenies from morphological data. Insect Syst. Divers. 3: 2.
Wright, A. M., Hillis, D. M. 2014. Bayesian analysis using a simple likelihood model outperforms parsimony for estimation of phylogeny from discrete morphological data. PLoS One. 9: e109210.
Wright, A. M., Lloyd, G. T., Hillis, D. M. 2016. Modeling character change heterogeneity in phylogenetic analyses of morphology through the use of priors. Syst. Biol. 65: 602–611.
Wright, A. M., Wagner, P. J., Wright, D. F. 2020. Testing character evolution models in phylogenetic paleobiology: A case study with Cambrian echinoderms. EcoEvoRxiv. https://doi.org/10.32942/osf.io/ykzg5. Wright, D. F. 2015. Fossils, homology, and phylogenetic paleo-ontogeny: A reassessment of primary posterior plate homologies among fossil and living crinoids with insights from developmental biology. Paleobiology. 41: 570–591.
Wright, D. F. 2017a. Bayesian estimation of fossil phylogenies and the evolution of early to middle Paleozoic crinoids (Echinodermata). J. Paleontol. 91: 799–814.
Wright, D. F. 2017b. Phenotypic innovation and adaptive constraints in the evolutionary radiation of palaeozoic crinoids. Sci. Rep. 7: 1–10.
Wright, D. F., Toom, U. 2017. New crinoids from the Baltic region (Estonia): Fossil tip‐dating phylogenetics constrains the origin and Ordovician–Silurian diversification of the Flexibilia (Echinodermata). Palaeontology. 60: 893–910.
