I’m calculating lambda (as a measure of phylogenetic signal) for a dataset
of bird plumage color traits across a clade of ~400 species. However, for a
few of the traits, the lambda estimate is 1.000000. This happens both with
phytools::phylosginal and with geiger::fitContinuous(model=‘lambda’),
although for a couple additional traits in phytools.
I realize that these implementations set a hard upper bound of 1 for
lambda, so the “real” lambda for these traits may actually be higher than
1. I also realize that lambda>1 can be interpreted as meaning that close
relatives are more similar to each other than expected under BM. But when I
look at the trait values, and especially based on my familiarity with the
taxa in this tree, that interpretation doesn’t feel right to me. The traits
don't look particularly conserved.
I also wonder if measurement error could be playing a role in this, since
it is fairly high in this dataset, and when I run the analyses without
measurement error, I don’t get lambdas of 1 anymore (although still in the
I also calculated Blomberg’s K and didn’t get values near 1 for any traits.
And there doesn’t seem to be an obvious correlation between values of K and
lambda for each trait.
Hopefully someone may be able to illuminate my with a guess as to what
might be happening here.
Thank you all very much,
*Rafael Sobral Marcondes*
PhD Candidate (Systematics, Ecology and Evolution/Ornithology)
Museum of Natural Science <http://sites01.lsu.edu/wp/mns/>
Louisiana State University
119 Foster Hall
Baton Rouge, LA 70803, USA
Twitter: @rafmarcondes <https://twitter.com/rafmarcondes>
[[alternative HTML version deleted]]
R-sig-phylo mailing list - Remail@example.com
Searchable archive at http://firstname.lastname@example.org/