Literature DB >> 34865153

Analyzing Disparity and Rates of Morphological Evolution with Model-Based Phylogenetic Comparative Methods.

Thomas F Hansen1, Geir H Bolstad2, Masahito Tsuboi1,3.   

Abstract

Understanding variation in rates of evolution and morphological disparity is a goal of macroevolutionary research. In a phylogenetic comparative methods framework, we present three explicit models for linking the rate of evolution of a trait to the state of another evolving trait. This allows testing hypotheses about causal influences on rates of phenotypic evolution with phylogenetic comparative data. We develop a statistical framework for fitting the models with generalized least-squares regression and use this to discuss issues and limitations in the study of rates of evolution more generally. We show that the power to detect effects on rates of evolution is low in that even strong causal effects are unlikely to explain more than a few percent of observed variance in disparity. We illustrate the models and issues by testing if rates of beak-shape evolution in birds are influenced by brain size, as may be predicted from a Baldwin effect in which presumptively more behaviorally flexible large-brained species generate more novel selection on themselves leading to higher rates of evolution. From an analysis of morphometric data for 645 species, we find evidence that both macro- and microevolution of the beak are faster in birds with larger brains, but with the caveat that there are no consistent effects of relative brain size.[Baldwin effect; beak shape; behavioral drive; bird; brain size; disparity; phylogenetic comparative method; rate of evolution.].
© The Author(s) 2021. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

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Year:  2022        PMID: 34865153      PMCID: PMC9366461          DOI: 10.1093/sysbio/syab079

Source DB:  PubMed          Journal:  Syst Biol        ISSN: 1063-5157            Impact factor:   9.160


  58 in total

Review 1.  Rates of evolution on the time scale of the evolutionary process.

Authors:  P D Gingerich
Journal:  Genetica       Date:  2001       Impact factor: 1.082

2.  The phylogenetic mixed model.

Authors:  Elizabeth A Housworth; Emília P Martins; Michael Lynch
Journal:  Am Nat       Date:  2004-01-28       Impact factor: 3.926

3.  Interpreting the evolutionary regression: the interplay between observational and biological errors in phylogenetic comparative studies.

Authors:  Thomas F Hansen; Krzysztof Bartoszek
Journal:  Syst Biol       Date:  2012-01-02       Impact factor: 15.683

4.  Model Adequacy and the Macroevolution of Angiosperm Functional Traits.

Authors:  Matthew W Pennell; Richard G FitzJohn; William K Cornwell; Luke J Harmon
Journal:  Am Nat       Date:  2015-06-12       Impact factor: 3.926

5.  Comparative analyses of the influence of developmental mode on phenotypic diversification rates in shorebirds.

Authors:  Gavin H Thomas; Robert P Freckleton; Tamás Székely
Journal:  Proc Biol Sci       Date:  2006-07-07       Impact factor: 5.349

6.  The million-year wait for macroevolutionary bursts.

Authors:  Josef C Uyeda; Thomas F Hansen; Stevan J Arnold; Jason Pienaar
Journal:  Proc Natl Acad Sci U S A       Date:  2011-08-23       Impact factor: 11.205

7.  MORPHOLOGICAL EVOLUTION MEDIATED BY BEHAVIOR IN THE DAMSELFLIES OF TWO COMMUNITIES.

Authors:  Mark A McPeek
Journal:  Evolution       Date:  1995-08       Impact factor: 3.694

8.  TRANSLATING BETWEEN MICROEVOLUTIONARY PROCESS AND MACROEVOLUTIONARY PATTERNS: THE CORRELATION STRUCTURE OF INTERSPECIFIC DATA.

Authors:  Thomas F Hansen; Emília P Martins
Journal:  Evolution       Date:  1996-08       Impact factor: 3.694

9.  Global distribution and conservation of evolutionary distinctness in birds.

Authors:  Walter Jetz; Gavin H Thomas; Jeffrey B Joy; David W Redding; Klaas Hartmann; Arne O Mooers
Journal:  Curr Biol       Date:  2014-04-10       Impact factor: 10.834

10.  The molecular basis of evolution.

Authors:  A C Wilson
Journal:  Sci Am       Date:  1985-10       Impact factor: 2.142

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