A Bayesian extension of phylogenetic generalized least squares: Incorporating uncertainty in the comparative study of trait relationships and evolutionary rates. (2nd January 2020)
- Record Type:
- Journal Article
- Title:
- A Bayesian extension of phylogenetic generalized least squares: Incorporating uncertainty in the comparative study of trait relationships and evolutionary rates. (2nd January 2020)
- Main Title:
- A Bayesian extension of phylogenetic generalized least squares: Incorporating uncertainty in the comparative study of trait relationships and evolutionary rates
- Authors:
- Fuentes‐G., Jesualdo A.
Polly, Paul David
Martins, Emília P. - Abstract:
- Abstract: Phylogenetic comparative methods use tree topology, branch lengths, and models of phenotypic change to take into account nonindependence in statistical analysis. However, these methods normally assume that trees and models are known without error. Approaches relying on evolutionary regimes also assume specific distributions of character states across a tree, which often result from ancestral state reconstructions that are subject to uncertainty. Several methods have been proposed to deal with some of these sources of uncertainty, but approaches accounting for all of them are less common. Here, we show how Bayesian statistics facilitates this task while relaxing the homogeneous rate assumption of the well‐known phylogenetic generalized least squares (PGLS) framework. This Bayesian formulation allows uncertainty about phylogeny, evolutionary regimes, or other statistical parameters to be taken into account for studies as simple as testing for coevolution in two traits or as complex as testing whether bursts of phenotypic change are associated with evolutionary shifts in intertrait correlations. A mixture of validation approaches indicates that the approach has good inferential properties and predictive performance. We provide suggestions for implementation and show its usefulness by exploring the coevolution of ankle posture and forefoot proportions in Carnivora.
- Is Part Of:
- Evolution. Volume 74:Number 2(2020)
- Journal:
- Evolution
- Issue:
- Volume 74:Number 2(2020)
- Issue Display:
- Volume 74, Issue 2 (2020)
- Year:
- 2020
- Volume:
- 74
- Issue:
- 2
- Issue Sort Value:
- 2020-0074-0002-0000
- Page Start:
- 311
- Page End:
- 325
- Publication Date:
- 2020-01-02
- Subjects:
- Bayesian statistics -- Carnivora -- evolutionary regimes -- phylogenetic comparative methods -- phylogenetic generalized least squares -- uncertainty
Evolution -- Periodicals
Heredity -- Periodicals
Évolution (Biologie) -- Périodiques
Hérédité -- Périodiques
338.47004094 - Journal URLs:
- http://evol.allenpress.com/evolonline/?request=index-html ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1558-5646 ↗
http://www.jstor.org/journals/00143820.html ↗
http://www.bioone.org/bioone/?request=get-journals-list&issn=0014-3820 ↗
https://academic.oup.com/evolut ↗
http://onlinelibrary.wiley.com/ ↗
http://firstsearch.oclc.org ↗
http://firstsearch.oclc.org/journal=0014-3820;screen=info;ECOIP ↗ - DOI:
- 10.1111/evo.13899 ↗
- Languages:
- English
- ISSNs:
- 0014-3820
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3834.000000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 14581.xml