Fossilization can mislead analyses of phenotypic disparity

Smith, Thomas J.; Sansom, Robert S.; Pisani, Davide; Donoghue, Philip C. J.

doi:10.1098/rspb.2023.0522

Cited by 3 publications

References 69 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Assessing the Adequacy of Morphological Models Using Posterior Predictive Simulations

Mulvey,

May,

Brown

et al. 2024

Systematic Biology

View full text Add to dashboard Cite

Reconstructing the evolutionary history of different groups of organisms provides insight into how life originated and diversified on Earth. Phylogenetic trees are commonly used to estimate this evolutionary history. Within Bayesian phylogenetics a major step in estimating a tree is in choosing an appropriate model of character evolution. While the most common character data used is molecular sequence data, morphological data remains a vital source of information. The use of morphological characters allows for the incorporation fossil taxa, and despite advances in molecular sequencing, continues to play a significant role in neontology. Moreover, it is the main data source that allows us to unite extinct and extant taxa directly under the same generating process. We therefore require suitable models of morphological character evolution, the most common being the Mk Lewis model. While it is frequently used in both palaeobiology and neontology, it is not known whether the simple Mk substitution model, or any extensions to it, provide a sufficiently good description of the process of morphological evolution. In this study we investigate the impact of different morphological models on empirical tetrapod data sets. Specifically, we compare unpartitioned Mk models with those where characters are partitioned by the number of observed states, both with and without allowing for rate variation across sites and accounting for ascertainment bias. We show that the choice of substitution model has an impact on both topology and branch lengths, highlighting the importance of model choice. Through simulations, we validate the use of the model adequacy approach, posterior predictive simulations, for choosing an appropriate model. Additionally, we compare the performance of model adequacy with Bayesian model selection. We demonstrate how model selection approaches based on marginal likelihoods are not appropriate for choosing between models with partition schemes that vary in character state space (i.e., that vary in Q-matrix state size). Using posterior predictive simulations, we found that current variations of the Mk model are often performing adequately in capturing the evolutionary dynamics that generated our data. We do not find any preference for a particular model extension across multiple data sets, indicating that there is no ‘one size fits all’ when it comes to morphological data and that careful consideration should be given to choosing models of discrete character evolution. By using suitable models of character evolution, we can increase our confidence in our phylogenetic estimates, which should in turn allow us to gain more accurate insights into the evolutionary history of both extinct and extant taxa.

show abstract

Assessing the Adequacy of Morphological Models Using Posterior Predictive Simulations

Mulvey,

May,

Brown

et al. 2024

Systematic Biology

View full text Add to dashboard Cite

show abstract

Fossilization can mislead analyses of phenotypic disparity

et al. 2023

Self Cite

View full text Add to dashboard Cite

Analyses of morphological disparity can incorporate living and fossil taxa to facilitate the exploration of how phenotypic variation changes through time. However, taphonomic processes introduce non-random patterns of data loss in fossil data and their impact on perceptions of disparity is unclear. To address this, we characterize how measures of disparity change when simulated and empirical data are degraded through random and structured data loss. We demonstrate that both types of data loss can distort the disparity of clades, and that the magnitude and direction of these changes varies between the most commonly employed distance metrics and disparity indices. The inclusion of extant taxa and exceptionally preserved fossils mitigates these distortions and clarifies the full extent of the data lost, most of which would otherwise go uncharacterized. This facilitates the use of ancestral state estimation and evolutionary simulations to further control for the effects of data loss. Where the addition of such reference taxa is not possible, we urge caution in the extrapolation of general patterns in disparity from datasets that characterize subsets of phenotype, which may represent no more than the traits that they sample.

show abstract

Assessing the Adequacy of Morphological Models used in Palaeobiology

Mulvey,

May,

Brown

et al. 2024

Preprint

View full text Add to dashboard Cite

Reconstructing the evolutionary history of different groups of organisms provides insight into how life originated and diversified on Earth. Phylogenetic trees are commonly used to estimate this evolutionary history, providing a hypothesis of the events. Within Bayesian phylogenetics a major step in estimating a tree is in choosing an appropriate model of character evolution. In the case of most extinct species, our only source of information to decipher their phylogenetic relationships is through the morphology of fossils. We therefore use a model of morphological character evolution, the most common of which being the Mk Lewis model. While it is frequently used in palaeobiology, it is not known whether the simple Mk substitution model, or any extensions to it, provide a sufficiently good description of the process of morphological evolution. To determine whether or not the Mk model is appropriate for fossil data we used posterior predictive simulations, a model adequacy approach, to estimate absolute fit of the model to morphological data sets. We first investigate the impact that different versions of the Mk model have on key parameter estimates using tetrapod data sets. We show that choice of substitution model has an impact on both topology and branch lengths, highlighting the importance of model choice. Next, we use simulations to investigate the power of posterior predictive simulations for morphology. Having validated this approach we show that current variations of the Mk model are in fact performing adequately in capturing the evolutionary dynamics that generated our data. We do not find any preference for a particular model extension across multiple data sets, indicating that there is no `one size fits all' when it comes to morphological data and that careful consideration should be given to choosing models of discrete character evolution. By using suitable models of character evolution, we can increase our confidence in our phylogenetic estimates, which should in turn allow us to gain more accurate insights into the evolutionary history of both extinct and extant taxa.

show abstract

Fossilization can mislead analyses of phenotypic disparity

Cited by 3 publications

References 69 publications

Assessing the Adequacy of Morphological Models Using Posterior Predictive Simulations

Assessing the Adequacy of Morphological Models Using Posterior Predictive Simulations

Fossilization can mislead analyses of phenotypic disparity

Assessing the Adequacy of Morphological Models used in Palaeobiology

Contact Info

Product

Resources

About