Good evening, Apologies for the delayed response.
> Contml was originally designed for inferring phylogenies from gene frequency > data in closely related populations, under the assumption that the mechanism > of change is genetic drift. Then it is roughly possible to assume > independent Brownian Motions of allele frequencies, with equal variances of > change. > > For quantitative characters all these assumptions are highly dubious. I try > to point out to the questioner that they cannot assume that the characters > are independent, and that they change with equal variances. The questioners > rarely react with enthusiasm to this. This appears to be the issue with all proposed methods for analyzing GM data, save perhaps the PC-based methods. Proposed parsimony-based methods of accounting for inapplicability and interdependence in discrete characters (e.g. Brazeau et al., 2019 <https://academic.oup.com/sysbio/article/68/4/619/5238046>; Hopkins & St. John, 2021 <https://academic.oup.com/sysbio/article/70/6/1163/6131693>; Goloboff et al., 2021 <https://onlinelibrary.wiley.com/doi/full/10.1111/cla.12456>; Wheeler, 2023 <https://onlinelibrary.wiley.com/doi/full/10.1111/cla.12553>; Goloboff & De Laet, in press <https://onlinelibrary.wiley.com/doi/full/10.1111/cla.12564>) aren’t easily applicable to continuously varying data (see review by Goloboff, 2022), and I’ve yet to encounter a likelihoodist alternative. > I would encourage people to try going the PCM route: getting a tree for > living species and using it to infer covariances of changes in characters. I > have mentioned in a few places that from that one might even use the > resulting inference to place fossil species on a tree (perhaps Liam Revell > has published that suggestion too). I’m assuming you mean Revell et al. (2015) <https://academic.oup.com/evolut/article/69/4/1027/6852435>. I imagine this procedure is easily workable when the molecular “backbone” topology is robustly supported, and the developmental constraints of morphometric characters are well-known for both extant and extinct taxa, e.g., size and shape of mammalian teeth. I don’t know if it’s workable for taxa without any molecular dats, without close modern relatives, and with non-modern-analog morphology and ontogeny, e.g., graptolites or vendobionts. > I would also note that there is a program, Threshml, distributed by my lab, > that uses Sewall Wright's "threshold model" to model discrete character > evolution, and to treat both continuous and discrete characters in the same > analysis. I did not know this. Thanks! Jacqueline S. Silviria The Last King of the Jungle Department of Earth & Space Science University of Washington Seattle, WA, USA [email protected] <mailto:[email protected]>, [email protected] <mailto:[email protected]> ResearchGate profile <https://www.researchgate.net/profile/J_Silviria> Twitter: @JSilviria Sent from my iPhone > On Feb 5, 2024, at 6:33 PM, Joe Felsenstein <[email protected]> wrote: > > > Morphmet people -- > > I want to concur with Jacqueline Silviria and with Chris Klingenberg about > the difficulties of using morphometric analyses to infer phylogenies. Just > to "violently agree": This is a more general problem with quantitative > characters of any kind. I often get asked how to use the > continuous-character maximum likelihood program Contml in my package PHYLIP > to infer a phylogeny from quantitative characters such as morphological > measurements. Contml was originally designed for inferring phylogenies from > gene frequency data in closely related populations, under the assumption that > the mechanism of change is genetic drift. Then it is roughly possible to > assume independent Brownian Motions of allele frequencies, with equal > variances of change. > > For quantitative characters all these assumptions are highly dubious. I try > to point out to the questioner that they cannot assume that the characters > are independent, and that they change with equal variances. The questioners > rarely react with enthusiasm to this. > > Of course there is a literature (Phylogenetic Comparative Methods) where we > have methods (which I guess we should call "Phylogenetic Comparative Methods > methods") that take a tree that is presumed known, or a cloud of trees from > bootstrapping or a sampled Bayesian posterior, and work the other way. > Namely they infer the covariances between changes in a multivariate Brownian > Motion, given the tree. > > I know that in the brilliant theory of Kendall, there are theorems showing > that if the individual landmark (x,y) coordinates have equal and isotropic > i.i.d. variances, then so will the coordinates in the shape space. But what > that is doing is assuming that the differences we see are all measurement > error. It does not guarantee independent i.i.d. Brownian Motion when the > changes along the branches of the tree are themselves covarying among > characters and with unequal variances. > > I would encourage people to try going the PCM route: getting a tree for > living species and using it to infer covariances of changes in characters. I > have mentioned in a few places that from that one might even use the > resulting inference to place fossil species on a tree (perhaps Liam Revell > has published that suggestion too). > > I would also note that there is a program, Threshml, distributed by my lab, > that uses Sewall Wright's "threshold model" to model discrete character > evolution, and to treat both continuous and discrete characters in the same > analysis. > > Joe > ---- > Joe Felsenstein [email protected] <mailto:[email protected]>, > [email protected] <mailto:[email protected]> > Department of Genome Sciences and Department of Biology, > University of Washington, Box 355065, Seattle, WA 98195-5065 USA > ----- > PS: please do not use [email protected] > <mailto:[email protected]>, which is an alias > that some mail systems now mistake as indicating spam. > > -- You received this message because you are subscribed to the Google Groups "Morphmet" group. 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