Bayesian placement of fossils on phylogenies using quantitative morphometric data

Parins‐Fukuchi, Caroline

doi:10.1111/evo.13516

Cited by 46 publications

(56 citation statements)

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“…Since the evolutionary relationships between the extant taxa represented in the morphological dataset have all been extensively studied and are well‐resolved, I used these as a fixed scaffolding to place the fossil taxa. Fossil placements were inferred from the continuous trait dataset using the cophymaru program (Parins‐Fukuchi ). I used the “binary weights” procedure to filter out reliable traits from ones likely to mislead by using the extant tree as a fixed point of reference.…”

Section: Methodsmentioning

confidence: 99%

Mosaic evolution, preadaptation, and the evolution of evolvability in apes

Parins‐Fukuchi

2020

Evolution

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A major goal in postsynthesis evolutionary biology has been to better understand how complex interactions between traits drive movement along and facilitate the formation of distinct evolutionary pathways. I present analyses of a character matrix sampled across the haplorrhine skeleton that revealed several modules of characters displaying distinct patterns in macroevolutionary disparity. Comparison of these patterns to those in neurological development showed that early ape evolution was characterized by an intense regime of evolutionary and developmental flexibility. Shifting and reduced constraint in apes was met with episodic bursts in phenotypic innovation that built a wide array of functional diversity over a foundation of shared developmental and anatomical structure. Shifts in modularity drove dramatic evolutionary changes across the ape body plan in two distinct ways: (1) an episode of relaxed integration early in hominoid evolution coincided with bursts in evolutionary rate across multiple character suites; (2) the formation of two new trait modules along the branch leading to chimps and humans preceded rapid and dramatic evolutionary shifts in the carpus and pelvis. Changes to the structure of evolutionary mosaicism may correspond to enhanced evolvability that has a “preadaptive” effect by catalyzing later episodes of dramatic morphological remodeling.

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Section: Methodsmentioning

confidence: 99%

Mosaic evolution, preadaptation, and the evolution of evolvability in apes

Parins‐Fukuchi

2020

Evolution

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“…In addition to being biologically interesting in their own right, the mosaic suites identified by my approach will be useful in methods for inferring phylogeny and divergence times. Several recent articles have demonstrated the strong potential for continuous traits as an alternative to discrete traits when reconstructing phylogeny (Parins-Fukuchi 2018b,a) and divergence times (Alvarez-Carretero et al . 2018).…”

Section: Resultsmentioning

confidence: 99%

Detecting mosaic patterns in macroevolutionary disparity

Parins‐Fukuchi

2018

Preprint

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8Evolutionary biologists have long sought to understand the full complexity in pattern and 9 process that shapes organismal diversity. Although phylogenetic comparative methods are often 10 used to reconstruct complex evolutionary dynamics, they are typically limited to a single 11 phenotypic trait. Extensions that accommodate multiple traits lack the ability to partition 12 multidimensional datasets into a set of mosaic suites of evolutionarily linked characters. I 13 introduce a comparative framework that identifies heterogeneity in evolutionary patterns across 14 large datasets of continuous traits. Using a model of continuous trait evolution based on the 15 differential accumulation of disparity across lineages in a phylogeny, the approach 16 algorithmically partitions traits into a set of character suites that best explains the data, where 17 each suite displays a distinct pattern in phylogenetic morphological disparity. When applied to 18 empirical data, the approach revealed a mosaic pattern predicted by developmental biology. The 19 evolutionary distinctiveness of individual suites can be investigated in more detail, either by 20 fitting conventional comparative models or by directly studying the phylogenetic patterns in 21 disparity recovered during the analysis. This framework can supplement existing comparative 22 approaches by inferring the complex, integrated patterns that shape evolution across the body plan 23 from disparate developmental, morphometric, and environmental sources of phenotypic data. 24Introduction: Characterizing the ways in which phenotypic disparity and evolutionary rates 25 differ across lineages and throughout time has long been a central goal in evolutionary biology. 26 Shifts in the rate of phenotypic change often coincide with the rapid diversification and ecological 27 innovation of diverse lineages (Rabosky and Adams 2012; Rabosky et al. 2013). In addition, 28 studying fluctuations in the tempo of evolutionary change can shed light on our knowledge of 29 important evolution processes, such as adaptation and evolutionary constraint. Over the past 30 several decades, the development and application of phylogenetic comparative methods (PCMs) 31 that identify patterns of phenotypic change using phylogenies (Harvey and Pagel 1991; Hansen 32 1997a; Butler and King 2004; O'Meara et al. 2006; Eastman et al. 2011; Beaulieu et al. 2012). 33 Modern PCMs enable researchers to infer shifts in evolutionary rate, constraint, and disparity 34 throughout time by applying stochastic models of trait evolution to comparative phenotypic data 35 using phylogenetic trees. These approaches have helped to answer important questions 36 concerning the tempo and mode of phenotypic evolution across deep timescales (Harmon et al. 37 2003; Scales et al. 2009; Harmon et al. 2010; Rohlfs et al. 2013; Slater 2013). 38 Paleobiological and comparative studies have typically examined univariate evolutionary 39 patterns. This has perhaps grown from the tendency of early comparative work ...

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“…Models of continuous trait evolution can be used to infer topology (Parins-Fukuchi, 2017) and divergence times (Alvarez-Carretero et al, 2019). Continuous data has also been shown to capture higher phylogenetic signal compared to discrete characters and can result in more accurate trees (Parins-Fukuchi, 2018). It is worth noting that >30% of the characters in our empirical example using brachiopods are continuous characters broken down into discrete states.…”

Section: Discussionmentioning

confidence: 99%

Ignoring fossil age uncertainty leads to inaccurate topology and divergence times in time calibrated tree inference

Barido‐Sottani

Tiel

Hopkins

et al. 2020

Preprint

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15Time calibrated trees are challenging to estimate for many extinct groups of species due to the 16 incompleteness of the rock and fossil records. Additionally, the precise age of a sample is typically 17 not known as it may have occurred at any time during the time interval spanned by the rock layer. 18 1 Bayesian phylogenetic approaches provide a coherent framework for incorporating multiple sources 19 of evidence and uncertainty. In this study, we simulate datasets with characteristics typical of 20 Palaeozoic marine invertebrates, in terms of character and taxon sampling. We use these datasets 21 to examine the impact of different age handling methods on estimated topologies and divergence 22 times obtained using the fossilized birth-death process. Our results reiterate the importance of 23 modeling fossil age uncertainty, although we find that the overall impact of fossil age uncertainty 24 depends on both fossil taxon sampling and character sampling. When character sampling is low, 25 different approaches to handling fossil age uncertainty make little to no difference in the accuracy 26 and precision of the results. However, when character sampling is high, sampling the fossil ages 27 as part of the inference gives topology and divergence times estimates that are as good as those 28 obtained by fixing ages to the truth, whereas fixing fossil ages to incorrect values results in higher 29 error and lower coverage. Modeling fossil age uncertainty is thus critical, as fixing incorrect fossil 30 ages will negate the benefits of improved fossil and character sampling. 31 Introduction 32Estimating phylogenetic relationships and divergence times among species are key components of 33 piecing together evolutionary and geological history. Approaches to building time trees in paleo-34 biology have traditionally involved estimating the topology and branch lengths scaled to time in 35 separate, sequential analyses (Bapst and Hopkins, 2017). Bayesian phylogenetic models make it 36 possible to estimate these parameters in combination. An advantage of this joint inference is that 37 temporal evidence can be used to inform the tree topology, in combination with character data, 38 and the posterior output will better reflect the uncertainty associated with the results (Ronquist 39 et al., 2012).40Statistically coherent models for incorporating extinct species into time calibrated tree inference 41 only recently became available. In particular, the fossilized birth-death (FBD) process provides a 42 joint description of the diversification and fossil sampling processes (Stadler, 2010; Heath et al., 43 2014). Under this model, extinct dated samples are considered as part of the tree, therefore con-44 2 tributing temporal information, and their phylogenetic position can be recovered, either as terminal 45 branches (tips) or ancestral to other samples (sampled ancestors). This modeling framework has 46 created enormous potential for incorporating more paleontological data into divergence time analy-47 ses and we are on...

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Bayesian placement of fossils on phylogenies using quantitative morphometric data

Cited by 46 publications

References 67 publications

Mosaic evolution, preadaptation, and the evolution of evolvability in apes

Mosaic evolution, preadaptation, and the evolution of evolvability in apes

Detecting mosaic patterns in macroevolutionary disparity

Ignoring fossil age uncertainty leads to inaccurate topology and divergence times in time calibrated tree inference

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