scholarly journals On the probabilities of branch durations and stratigraphic gaps in phylogenies of fossil taxa when rates of diversification and sampling vary over time

Paleobiology ◽  
2019 ◽  
Vol 45 (1) ◽  
pp. 30-55 ◽  
Author(s):  
Peter J. Wagner

AbstractThe time separating the first appearances of species from their divergences from related taxa affects assessments of macroevolutionary hypotheses about rates of anatomical or ecological change. Branch durations necessarily posit stratigraphic gaps in sampling within a clade over which we have failed to sample predecessors (ancestors) and over which there are no divergences leading to sampled relatives (sister taxa). The former reflects only sampling rates, whereas the latter reflects sampling, origination, and extinction rates. Because all three rates vary over time, the probability of a branch duration of any particular length will differ depending on when in the Phanerozoic that branch duration spans. Here, I present a birth–death-sampling model allowing interval-to-interval variation in diversification and sampling rates. Increasing either origination or sampling rates increases the probability of finding sister taxa that diverge both during and before intervals of high sampling/origination. Conversely, elevated extinction reduces the probability of divergences from sampled sister taxa before and during intervals of elevated extinction. In the case of total extinction, a Signor-Lipps will reduce expected sister taxa leading up to the extinction, with the possible effect stretching back many millions of years when sampling is low. Simulations indicate that this approach provides reasonable estimates of branch duration probabilities under a variety of circumstances. Because current probability models for describing morphological evolution are less advanced than methods for inferring diversification and sampling rates, branch duration priors allowing for time-varying diversification could be a potent tool for phylogenetic inference with fossil data.

Author(s):  
José Novoa ◽  
Jorge Wuth ◽  
Juan Pablo Escudero ◽  
Josué Fredes ◽  
Rodrigo Mahu ◽  
...  

2018 ◽  
Vol 5 (3) ◽  
pp. 1322-1334 ◽  
Author(s):  
Philip E. Pare ◽  
Carolyn L. Beck ◽  
Angelia Nedic

2021 ◽  
pp. 095679762097055
Author(s):  
Catriona Silvey ◽  
Özlem Ece Demir-Lira ◽  
Susan Goldin-Meadow ◽  
Stephen W. Raudenbush

Early linguistic input is a powerful predictor of children’s language outcomes. We investigated two novel questions about this relationship: Does the impact of language input vary over time, and does the impact of time-varying language input on child outcomes differ for vocabulary and for syntax? Using methods from epidemiology to account for baseline and time-varying confounding, we predicted 64 children’s outcomes on standardized tests of vocabulary and syntax in kindergarten from their parents’ vocabulary and syntax input when the children were 14 and 30 months old. For vocabulary, children whose parents provided diverse input earlier as well as later in development were predicted to have the highest outcomes. For syntax, children whose parents’ input substantially increased in syntactic complexity over time were predicted to have the highest outcomes. The optimal sequence of parents’ linguistic input for supporting children’s language acquisition thus varies for vocabulary and for syntax.


2020 ◽  
Vol 70 (1) ◽  
pp. 181-189
Author(s):  
Guy Baele ◽  
Mandev S Gill ◽  
Paul Bastide ◽  
Philippe Lemey ◽  
Marc A Suchard

Abstract Markov models of character substitution on phylogenies form the foundation of phylogenetic inference frameworks. Early models made the simplifying assumption that the substitution process is homogeneous over time and across sites in the molecular sequence alignment. While standard practice adopts extensions that accommodate heterogeneity of substitution rates across sites, heterogeneity in the process over time in a site-specific manner remains frequently overlooked. This is problematic, as evolutionary processes that act at the molecular level are highly variable, subjecting different sites to different selective constraints over time, impacting their substitution behavior. We propose incorporating time variability through Markov-modulated models (MMMs), which extend covarion-like models and allow the substitution process (including relative character exchange rates as well as the overall substitution rate) at individual sites to vary across lineages. We implement a general MMM framework in BEAST, a popular Bayesian phylogenetic inference software package, allowing researchers to compose a wide range of MMMs through flexible XML specification. Using examples from bacterial, viral, and plastid genome evolution, we show that MMMs impact phylogenetic tree estimation and can substantially improve model fit compared to standard substitution models. Through simulations, we show that marginal likelihood estimation accurately identifies the generative model and does not systematically prefer the more parameter-rich MMMs. To mitigate the increased computational demands associated with MMMs, our implementation exploits recent developments in BEAGLE, a high-performance computational library for phylogenetic inference. [Bayesian inference; BEAGLE; BEAST; covarion, heterotachy; Markov-modulated models; phylogenetics.]


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