A comparison of metrics for estimating phylogenetic signal under alternative evolutionary models

Genetics and Molecular Biology

José Alexandre F. Diniz-filho²  Thiago Santos¹  Thiago Fernando Rangel²  Luis Mauricio Bini² 

[1] ,Universidade Federal de Goiás Instituto de Ciências Biológicas Departamento de EcologiaGoiânia GO ,Brazil

关键词: autocorrelation;    Blomberg's K;    Pagel's lambda;    autoregressive method;    Moran's I;    phylogenetic eigenvector regression;   

DOI  :  10.1590/S1415-47572012005000053

来源: SciELO

【 摘 要 】

Several metrics have been developed for estimating phylogenetic signal in comparative data. These may be important both in guiding future studies on correlated evolution and for inferring broad-scale evolutionary and ecological processes (e.g., phylogenetic niche conservatism). Notwithstanding, the validity of some of these metrics is under debate, especially after the development of more sophisticated model-based approaches that estimate departure from particular evolutionary models (i.e., Brownian motion). Here, two of these model-based metrics (Blomberg's K-statistics and Pagel's λ) are compared with three statistical approaches [Moran's I autocorrelation coefficient, coefficients of determination from the autoregressive method (ARM), and phylogenetic eigenvector regression (PVR)]. Based on simulations of a trait evolving under Brownian motion for a phylogeny with 209 species, we showed that all metrics are strongly, although non-linearly, correlated to each other. Our analyses revealed that statistical approaches provide valid results and may be still particularly useful when detailed phylogenies are unavailable or when trait variation among species is difficult to describe by more standard Brownian or O-U evolutionary models.

【 授权许可】

CC BY   
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