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Heterogeneous relationships between rates of speciation and body size evolution across vertebrate clades

Nature Ecology & Evolution volume 5, pages 101–110 (2021)Cite this article

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Abstract

Several theories predict that rates of phenotypic evolution should be related to the rate at which new lineages arise. However, drawing general conclusions regarding the coupling between these fundamental evolutionary rates has been difficult due to the inconsistent nature of previous results combined with uncertainty over the most appropriate methodology with which to investigate such relationships. Here we propose and compare the performance of several different approaches for testing associations between lineage-specific rates of speciation and phenotypic evolution using phylogenetic data. We then use the best-performing method to test relationships between rates of speciation and body size evolution in five major vertebrate clades (amphibians, birds, mammals, ray-finned fish and squamate reptiles) at two phylogenetic scales. Our results provide support for the long-standing view that rates of speciation and morphological evolution are generally positively related at broad macroevolutionary scales, but they also reveal a substantial degree of heterogeneity in the strength and direction of these associations at finer scales across the vertebrate tree of life.

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Fig. 1: Comparison of performance of different approaches for testing correlations between rates of speciation and trait evolution.
Fig. 2: Correlated speciation and trait rates simulation (Cor-STRATES) framework.
Fig. 3: Phylogenetic patterns of evolutionary rate heterogeneity for five vertebrate clades.
Fig. 4: Relationship between rates of speciation and body size evolution for five vertebrate groups.
Fig. 5: Heterogeneity in relationship between rates of speciation and body size evolution among major vertebrate subclades.

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Data availability

All data used in the study is sourced from publicly assessible sources. Compiled datasets are available as Supplementary Data.

Code availability

R code is available at https://github.com/christophercooney/Cor-STRATES.

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Acknowledgements

We thank J. Brown, A. Chira, Y. He, E. Hughes and J. Kennedy for helpful discussion, and M. Pennell and D. Rabosky for constructive comments on the manuscript. This work was funded by the European Research Council (grant no. 615709 Project ‘ToLERates’), and by a Leverhulme Early Career Fellowship to C.R.C. (ECF-2018-101) and a Royal Society University Research Fellowship to G.H.T. (UF120016 and URF\R\180006).

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  1. Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield, UK

    Christopher R. Cooney & Gavin H. Thomas

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C.R.C. and G.H.T conceived and designed the research. C.R.C. collected data and conducted the analyses. C.R.C. and G.H.T. wrote the manuscript.

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Correspondence to Christopher R. Cooney.

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Extended data

Extended Data Fig. 1 The performance of different phylogenetic approaches for estimating rates of speciation (λ) and trait evolution (σ2).

Plots show the error, bias and correlation of estimated rates of speciation a, and trait evolution (b-c) compared to true (that is simulated) values. In b, results are based on comparing rates across all branches of the tree, whereas in c, results are based on comparing tip rates only. Results are based on fitting models to 100 simulated tree and trait datasets, each with 250 tips. Boxplots show the median value (thick line) and 0.25-0.75 (box) and 0.05-0.95 (whiskers) quantile ranges. BT, BayesTraits; ST, StableTraits.

Extended Data Fig. 2 Comparison of the performance of different approaches for testing correlations between rates of speciation and trait evolution.

Results are based on simulated datasets of 250-tip trees (n = 100) assuming strong correlations between rates (columns 1 and 2), with speciation rates estimated using BAMM (λBAMM) and trait rates also estimated using BAMM (σ2BAMM). See Methods for details of the simulation procedure, rate metrics and significance tests used. The grey shaded area indicates false discovery (Type I error) rates of <5%.

Extended Data Fig. 3 Comparison of mean standardised effect sizes derived from the ‘simulation + rescale’ approach using alternate rate metrics.

Speciation rates are estimated using BAMM (λBAMM) and trait rates are estimated using either BayesTraits (σ2BT) or BAMM (σ2BAMM). Results are based on applying the ‘tree-transformation + simulation’ method to datasets of 250-tip trees (n = 100) generated assuming strong correlations between rates (columns 1 and 2).

Extended Data Fig. 4 Comparison of the performance of the ‘simulation + rescale’ approach with varying tree size and simulated correlation strength.

Results are based on simulated datasets of 100 trees, with speciation rates estimated using BAMM (λBAMM) and trait rates estimated using BayesTraits (σ2BT). For the scenarios involving correlated rates, solid and dashed lines correspond to strong (r = ±1) and weaker (r = ± 0.5) simulated correlation strengths, respectively. (Note: realised correlation strengths associated with these scenarios are lower than implied by the generating values; see Extended Data Fig. 10). The grey shaded area indicates false discovery (Type I error) rates of <5%. ME, measurement error.

Extended Data Fig. 5 Comparison of the performance of the ‘simulation + rescale’ approach with decreasing sampling proportions.

Results are based on simulated datasets of 250-tip trees (n = 100) assuming strong correlations between rates (columns 1 and 2), with speciation rates estimated using BAMM (λBAMM) and trait rates estimated using BayesTraits (σ2BT). The grey shaded area indicates false discovery (Type I error) rates of <5%. ME, measurement error.

Extended Data Fig. 6 Comparison of the performance of the ‘simulation + rescale’ approach with increasing relative extinction (turnover) rates.

Results are based on simulated datasets of 250-tip trees (n = 100) assuming strong correlations between rates (columns 1 and 2), with speciation rates estimated using BAMM (λBAMM) and trait rates estimated using BayesTraits (σ2BT). The grey shaded area indicates false discovery (Type I error) rates of <5%. ME, measurement error.

Extended Data Fig. 7 Results for tests of the relationship between rates of speciation and body size evolution within five vertebrate taxa.

Results are based on speciation rates estimated using BAMM (λBAMM) and body size rates estimated using BayesTraits (σ2BT). N = total species richness; Nsamp = number of species sampled in rate analyses; phy. sig. = body size phylogenetic signal (Pagel’s lambda); ρobs = observed correlation coefficient (Spearman’s ρ); ρnull = null correlation coefficients derived from null simulations (n = 200); SES = standardised effect size.

Extended Data Fig. 8 Relationships between rates of speciation and body size evolution in vertebrate subclades.

Plots show the relationship between log-transformed tip rates of speciation (λBAMM) and body size evolution (σ2BT) in each clade. Colours reflect the five vertebrate groups (birds = blue, mammals = red, amphibians = green, squamates = purple, fish = orange). Inset numbers give the mean effect size for each relationship, with significant (P < 0.05) associations marked with an asterisk and highlighted in bold.

Extended Data Fig. 9 Multipredictor models of effect sizes measuring the strength of the association between rates of speciation and body size evolution in vertebrate subclades.

Results are based on speciation rates estimated using BAMM (λBAMM) and trait rates estimated using BayesTraits (σ2BT). All predictor variables were standardised (mean = 0, sd = 1) prior to analysis. SE = standard error. *, PMCMC < 0.05.

Extended Data Fig. 10 Mean (sd) correlation coefficients (Pearson’s r) for the realised relationship between simulated rates of speciation and trait evolution.

Realised rates of trait evolution are inferred by calculating the squared-trait distance between known simulated ancestral and descendent nodes in the tree, divided by phylogenetic branch length (that is time). Note: Pearson’s r values in the table header refer to the correlation strength between speciation and trait rates used in the stochastic model used to generate trait values. n = 100 trees in each case.

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Supplementary Data

Supplementary Data 1 (taxonomy and body size measurements) and 2 (subclade data and effect sizes).

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Cooney, C.R., Thomas, G.H. Heterogeneous relationships between rates of speciation and body size evolution across vertebrate clades. Nat Ecol Evol 5, 101–110 (2021). https://doi.org/10.1038/s41559-020-01321-y

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