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1. COMPARATIVE EVOLUTIONARY TRENDS IN XIPHOSURA

   https://doi.org/10.1130/abs/2023AM-389733  

   Ocon, Samantha B.; Lamsdell, James C. (October 2023, Geological Society of America Abstracts with Programs)

   Horseshoe crabs (class Xiphosura) are a long-lived clade of aquatic chelicerate arthropods with a fossil record spanning approximately 480 million years. Though Xiphosura are often noted for their morphological stability, further investigation of evolutionary rate and paleoecological trends have revealed a remarkably dynamic clade, with both temporal and phylogenetic variability in evolutionary trends. Additionally, heterochrony has been revealed to be a strong driver behind xiphosuran evolution and the exploration of non-marine niches. Using combined geometric morphometric and evolutionary rate techniques, we further highlight the incongruency of the fossil record of xiphosurans with their designation as a “living fossil” or stabilomorph clade. Here, we compare the results of a geometric morphometric analysis with a discrete character evolutionary rate calculation performed using the R package Claddis. Both analyses incorporated 55 xiphosuran species, ranging temporally from the Ordovician Lunataspis aurora to all four modern species. Morphometric data was collected as 2Dlandmarks and semi-landmarks, with variable numbers of points due to varying levels of preservation amongst fossil specimens. These data were then used to produce a PCA for the visualization of morphospace. Both studies support a dynamic evolutionary history for Xiphosura. The discrete character analysis revealed peaks in discrete character evolution in the heterochronic non-marine clades, as well as an overall declining trend in evolutionary rate. Similarly, the clades with higher evolutionary rates occupy a wider portion of morphospace compared with the more morphologically stable clades. 

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2. A variable-rate quantitative trait evolution model using penalized-likelihood

   https://doi.org/10.7717/peerj.11997  

   Revell, Liam J. (January 2021, PeerJ)

   In recent years it has become increasingly popular to use phylogenetic comparative methods to investigate heterogeneity in the rate or process of quantitative trait evolution across the branches or clades of a phylogenetic tree. Here, I present a new method for modeling variability in the rate of evolution of a continuously-valued character trait on a reconstructed phylogeny. The underlying model of evolution is stochastic diffusion (Brownian motion), but in which the instantaneous diffusion rate (σ 2 ) also evolves by Brownian motion on a logarithmic scale. Unfortunately, it’s not possible to simultaneously estimate the rates of evolution along each edge of the tree and the rate of evolution of σ 2 itself using Maximum Likelihood. As such, I propose a penalized-likelihood method in which the penalty term is equal to the log-transformed probability density of the rates under a Brownian model, multiplied by a ‘smoothing’ coefficient, λ, selected by the user. λ determines the magnitude of penalty that’s applied to rate variation between edges. Lower values of λ penalize rate variation relatively little; whereas larger λ values result in minimal rate variation among edges of the tree in the fitted model, eventually converging on a single value of σ 2 for all of the branches of the tree. In addition to presenting this model here, I have also implemented it as part of my phytools R package in the function multirateBM . Using different values of the penalty coefficient, λ, I fit the model to simulated data with: Brownian rate variation among edges (the model assumption); uncorrelated rate variation; rate changes that occur in discrete places on the tree; and no rate variation at all among the branches of the phylogeny. I then compare the estimated values of σ 2 to their known true values. In addition, I use the method to analyze a simple empirical dataset of body mass evolution in mammals. Finally, I discuss the relationship between the method of this article and other models from the phylogenetic comparative methods and finance literature, as well as some applications and limitations of the approach. 

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3. A simple hierarchical model for heterogeneity in the evolutionary correlation on a phylogenetic tree

   https://doi.org/10.7717/peerj.13910  

   Revell, Liam J.; Toyama, Ken S.; Mahler, D. Luke (January 2022, PeerJ)

   Numerous questions in phylogenetic comparative biology revolve around the correlated evolution of two or more phenotypic traits on a phylogeny. In many cases, it may be sufficient to assume a constant value for the evolutionary correlation between characters across all the clades and branches of the tree. Under other circumstances, however, it is desirable or necessary to account for the possibility that the evolutionary correlation differs through time or in different sections of the phylogeny. Here, we present a method designed to fit a hierarchical series of models for heterogeneity in the evolutionary rates and correlation of two quantitative traits on a phylogenetic tree. We apply the method to two datasets: one for different attributes of the buccal morphology in sunfishes (Centrarchidae); and a second for overall body length and relative body depth in rock- and non-rock-dwelling South American iguanian lizards. We also examine the performance of the method for parameter estimation and model selection using a small set of numerical simulations. 

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4. Assessing the Adequacy of Morphological Models Using Posterior Predictive Simulations

   https://doi.org/10.1093/sysbio/syae055  

   Mulvey, Laura P_A; May, Michael R; Brown, Jeremy M; Höhna, Sebastian; Wright, April M; Warnock, Rachel C_M (October 2024, Systematic Biology)

   Klopfstein, Seraina (Ed.)

   Abstract 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 datasets. 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 datasets, 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. 

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5. Linking mode of seed dispersal and climatic niche evolution in flowering plants

   https://doi.org/10.1111/jbi.14292  

   Vasconcelos, Thais; Boyko, James D.; Beaulieu, Jeremy M. (December 2021, Journal of Biogeography)

   Abstract AimDue to the sessile nature of flowering plants, movements to new geographical areas occur mainly during seed dispersal. Frugivores tend to be efficient dispersers because animals move within the boundaries of their preferable niches, so seeds are more likely to be transported to environments that are similar to where the parent plant occurs. However, this efficiency can result in less opportunity for niche shifts over macroevolutionary time, ‘trapping’ plant lineages in particular climatic conditions. Here we test this hypothesis by analysing the role that the interaction with frugivores play in changing dynamics of climatic niche evolution in five clades of flowering plants. LocationGlobal. TaxonThe flowering plant families Apocynaceae, Ericaceae, Melastomataceae, Rosaceae and Solanaceae. MethodsWe model climatic niche evolution as a variable parameter Ornstein–Uhlenbeck process. However, rather than assuming regimes a priori, we use a hidden Markov model (HMM) to infer the complex evolutionary history associated with different modes of seed dispersal. In addition to allowing for a more accurate picture of the regimes, the use of HMMs allows partitioning the variance of climatic niche evolution to include dynamics independent of our focal character. ResultsLineages dispersed by frugivores tend to have warmer and wetter climatic optima and are generally associated with areas where potential for vegetation growth is higher. However, lineages distributed in more mesic habitats, such as rainforests, are generally associated with slower rates of climatic niche evolution regardless of their mode of seed dispersal. Main ConclusionsCharacteristics of the abiotic environment may facilitate the evolution of some types of plant–animal interactions. Association with frugivores is an important modulator of how plants move in space, but its impact on their climatic niche evolution appears to be indirect. Seed dispersal by frugivores may facilitate the establishment of lineages in closed canopy biomes, but the general slower rates of climatic niche evolution in these habitats are possibly related to other general aspects of the ‘mesic syndrome’ rather than the behaviour of the animals that disperse their seeds. 

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