Dear Sim�n,
Typically people do this by �painting� regimes on the tree using the discrete
trait and then trying different OU models for the different regimes. For
example, does being in the island regime lead to a higher rate of evolution
(bigger sigma in the BMS model) than being in the mainland? Is rate difference
large enough in magnitude to be biologically relevant? The discrete trait
reconstruction can be done using likelihood (using stochastic character maps or
a joint or marginal reconstruction) or parsimony. This does have problems: the
discrete reconstruction is done �greedily� ignoring its effect on the
continuous trait, and like all ancestral state reconstruction it can have error
(so, for example, some branches painted �island� are actually �mainland�). See
Revell (2003) (https://doi.org/10.1093/sysbio/sys084) for more about the
potential deleterious effects. There�s work on fixing it (watch for a talk by
James Boyko at Evolution in June, though James� work does more than just �fix�).
There are a couple of other issues you might encounter. First, OU/BM models
aren�t great for proportions. They assume that a trait can increase or decrease
by, say, 17, no matter its current value [though with OU, the probability of
the change will vary based on where the trait is relative to theta]. If
proportions are near the bounds, the bounds affect the motion: no species can
spend 110% of its time on head bob displays. If they�re near the lower bound
and don�t �feel� the upper bound, then perhaps just log transforming it as for
other zero bounded traits is appropriate enough.
The second is the data set size of just 8 taxa. It could be enough if you have
a ton of independent traits that evolve under the same model, but if not,
you�re looking at something like 8 datapoints for fitting a model of, if say
OUM with two regimes, 5 parameters. OUwie will give you warnings about this but
still let you run it, but expect at best enormous uncertainty in parameter
estimates, and possibly unidentifiability (OUwie now warns about some
unidentifiability, but not all).
Best,
Brian
_______________________________________________________________________
Brian O'Meara
Professor, Dept. of Ecology & Evolutionary Biology, UT Knoxville
Associate Head, Dept. of Ecology & Evolutionary Biology, UT Knoxville
President-Elect, Society of Systematic Biologists
He/Him/His
From: R-sig-phylo <r-sig-phylo-boun...@r-project.org> on behalf of Simon Lobos
<lobossi...@gmail.com>
Date: Sunday, May 16, 2021 at 9:39 PM
To: r-sig-phylo@r-project.org <r-sig-phylo@r-project.org>
Subject: [R-sig-phylo] Fitting models with continous characteres
Dear all,
I am writing to seek for any advice with my phylogenetic comparative
analysis in behavioural traits.
I am trying to run an evolutionary model that contains other information
rather than BW, OU or EB. The variables I am using are continuous (time
proportion) and I want to fit them in a model that contains three different
scenarios: island effect, colonization time and sexual size dimorphism
(SSD).
I know I can do this kind of analysis with OUwie package from R, but I am
not so familiar with it, so I am having some issues setting up the
evolutionary model. I am working with eight species (2 from mainland and 6
from island). I am using this information to set up the island effect model
(1=island, 0=mainland), while for the colonization time I am using previous
published information (0=west, 1=east, 2=mainland). For the SSD model, I
plan to use my own morphological data collected from all my fieldwork
seasons (one value per species based on the SVL).
However, I am not sure how to include this information in the model using
OUwie package.
If any of you could help me with this I will really appreciate it.
--
Sim�n
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