4.5 Article

ASSESSING PHYLOGENETIC SIGNAL WITH MEASUREMENT ERROR: A COMPARISON OF MANTEL TESTS, BLOMBERG ET AL.'S K, AND PHYLOGENETIC DISTOGRAMS

Journal

EVOLUTION
Volume 66, Issue 8, Pages 2614-2621

Publisher

OXFORD UNIV PRESS
DOI: 10.1111/j.1558-5646.2012.01623.x

Keywords

Abouheif proximity; Euclidean distance; intraspecific variability; Mantel test; measurement error; phylogenetic distogram; phylogenetic signal

Funding

  1. [F.4.519.10.F]

Ask authors/readers for more resources

In macroevolutionary studies, different approaches are commonly used to measure phylogenetic signalthe tendency of related taxa to resemble one anotherincluding the K statistic and the Mantel test. The latter was recently criticized for lacking statistical power. Using new simulations, we show that the power of the Mantel test depends on the metrics used to define trait distances and phylogenetic distances between species. Increasing power is obtained by lowering variance and increasing negative skewness in interspecific distances, as obtained using Euclidean trait distances and the complement of Abouheif proximity as a phylogenetic distance. We show realistic situations involving measurement error due to intraspecific variability where the Mantel test is more powerful to detect a phylogenetic signal than a permutation test based on the K statistic. We highlight limitations of the K-statistic (univariate measure) and show that its application should take into account measurement errors using repeated measures per species to avoid estimation bias. Finally, we argue that phylogenetic distograms representing Euclidean trait distance as a function of the square root of patristic distance provide an insightful representation of the phylogenetic signal that can be used to assess both the impact of measurement error and the departure from a Brownian evolution model.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available