Literature DB >> 23103589

Estimating speciation and extinction rates for phylogenies of higher taxa.

Tanja Stadler1, Folmer Bokma.   

Abstract

Speciation and extinction rates can be estimated from molecular phylogenies. Recently, a number of methods have been published showing that these rates can be estimated even if the phylogeny is incomplete, that is, if not all extant species are included. We show that the accuracy of such methods strongly depends on making the correct assumptions about how the sampling process was performed. We focus on phylogenies that are incomplete because some subclades (e.g., genera and families) are each represented as a single lineage. We show that previous methods implicitly assumed that such subclades are defined by randomly (or in an extreme deterministic way) choosing the edges that define the subclades from the complete species phylogeny. We show that these methods produce biased results if higher taxa are defined in a different manner. We introduce strict higher level phylogenies where subclades are defined so that the phylogeny is fully resolved from its origin to time x(cut), and fully unresolved thereafter, so that for all subclades, stem age > x(cut) > crown age. We present estimates of speciation and extinction rates from a phylogeny of birds in which this subclade definition was applied. However, for most higher level phylogenies in the literature, it is unclear how higher taxa were defined, but often such phylogenies can be easily transformed into strict higher level phylogenies, as we illustrate by estimating speciation and extinction rates from a near-complete but only partly resolved species-level phylogeny of mammals. The accuracy of our methods is verified using simulations.

Mesh:

Year:  2012        PMID: 23103589     DOI: 10.1093/sysbio/sys087

Source DB:  PubMed          Journal:  Syst Biol        ISSN: 1063-5157            Impact factor:   15.683


  12 in total

1.  Total-Evidence Dating under the Fossilized Birth-Death Process.

Authors:  Chi Zhang; Tanja Stadler; Seraina Klopfstein; Tracy A Heath; Fredrik Ronquist
Journal:  Syst Biol       Date:  2015-10-22       Impact factor: 15.683

2.  An engine for global plant diversity: highest evolutionary turnover and emigration in the American tropics.

Authors:  Alexandre Antonelli; Alexander Zizka; Daniele Silvestro; Ruud Scharn; Borja Cascales-Miñana; Christine D Bacon
Journal:  Front Genet       Date:  2015-04-08       Impact factor: 4.599

3.  Likelihood inference of non-constant diversification rates with incomplete taxon sampling.

Authors:  Sebastian Höhna
Journal:  PLoS One       Date:  2014-01-06       Impact factor: 3.240

4.  Measuring Stratigraphic Congruence Across Trees, Higher Taxa, and Time.

Authors:  Anne O'Connor; Matthew A Wills
Journal:  Syst Biol       Date:  2016-05-06       Impact factor: 15.683

5.  Estimating shifts in diversification rates based on higher-level phylogenies.

Authors:  Tanja Stadler; Jana Smrckova
Journal:  Biol Lett       Date:  2016-10       Impact factor: 3.703

6.  Microhabitat change drives diversification in pholcid spiders.

Authors:  Jonas Eberle; Dimitar Dimitrov; Alejandro Valdez-Mondragón; Bernhard A Huber
Journal:  BMC Evol Biol       Date:  2018-09-19       Impact factor: 3.260

7.  Exploring the power of Bayesian birth-death skyline models to detect mass extinction events from phylogenies with only extant taxa.

Authors:  Victoria Culshaw; Tanja Stadler; Isabel Sanmartín
Journal:  Evolution       Date:  2019-05-09       Impact factor: 3.694

8.  Detecting patterns of species diversification in the presence of both rate shifts and mass extinctions.

Authors:  Sacha Laurent; Marc Robinson-Rechavi; Nicolas Salamin
Journal:  BMC Evol Biol       Date:  2015-08-11       Impact factor: 3.260

9.  History is written by the victors: The effect of the push of the past on the fossil record.

Authors:  Graham E Budd; Richard P Mann
Journal:  Evolution       Date:  2018-09-26       Impact factor: 3.694

10.  Bayesian estimation of speciation and extinction from incomplete fossil occurrence data.

Authors:  Daniele Silvestro; Jan Schnitzler; Lee Hsiang Liow; Alexandre Antonelli; Nicolas Salamin
Journal:  Syst Biol       Date:  2014-02-08       Impact factor: 15.683

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