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 [[alternative HTML version deleted]] _______________________________________________ R-sig-phylo mailing list - R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo Searchable archive at http://www.mail-archive.com/r-sig-phylo@r-project.org/ [[alternative HTML version deleted]]
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