Dear r-sig-phylo participants,

I have data set where tips are assigned to 3 discrete states (aquatic, semi-aquatic and terrestrial). Because the definition of "semi-aquatic" is quite arbitrary and some species in the tree lack field observations of their ecology, I decided to use a matrix of state priors for stochastic mapping in the phytools package. That approach will allow me to account for uncertainties/lack of information for some tips in the phylogeny. I fitted 3 models (ER, SYM, and ARD) where Q was empirically estimated and nsim was set to 1000. According to AIC value, the SYM model was the best-fitted one. Describe.simmap showed that mean total time spent in the state "semi-aquatic" was 0. Thus, all mapped trees were actually binary and I was able to employ the densityMap function to obtain an object, let's say "obj", which contains a single tree with the posterior density for the "aquatic" and "terrestrial" states from 1000 stochastic maps.

Here is the question:
Is it straightforward idea to paint back the obj$tree with just two colors where colors are determined by a threshold value of posterior probability (indicated as a legend bar in the bottom left part of the graph)? For instance, is it appropriate to paint a tree edges with a color A if PP is lower or equal than 0.5 and color B if PP is greater than 0.5?

Some R packages for model fitting allow simmap tree as input, but if my question makes sense, it would be better to provide consensus tree from n stochastic maps instead to use one stochastic map as input.

Thank you for your time.
Kind regards,

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