I have built a phylogenetic tree using categorical functional traits, such as pollination and dispersion syndromes, phenology, etc. Now, I can see the dicotomies and the points in which the plant species diverge, lineages, and so on. However, the interpretation itself seems to be a little tricky because I want to go with quantitative and qualitative discussion but don't know where to start from.
It is hard. Remember too that phylogeny is philosophical because it is based on on evolutionary assumptions, which are unprovable :)
As I understand you are trying to make the analysis of a character phylogeny. If it is so, then you can find many papers for which you can use in following google scholar search: https://scholar.google.com.tr/scholar?&q=character+phylogenies
You have to keep in mind that a lot of functional traits do not necessarily assume that shared trait values are due to shared ancestry. For example, if different species have the same value for some categorical trait that captures something about phenology then it is by no means a given that those species are actually closely related to one another.
You will probably also see this on your tree in that there is a relatively large amount of homoplasy compared to characters that are traditionally used to construction morphological species phylogenies.
As such, you have to consider that your tree actually isn't a phylogeny at all. Rather, it's a dendrogram that shows clustering by functional similarity. Perhaps you shouldn't even build the tree using methods that are based on evolutionary assumptions (e.g. maximum parsimony). Perhaps you should use something like the gower distance across the data set, and then build a dendrogram using something like neighbor-joining.
Subsequently, your interpretation might be along the lines of, qualitatively, distinguishing clusters of functional similarity. You might even do a hierarchical clustering where you specify how many clusters you want produced, and then you can discuss what each of these clusters means in functional terms.
As for quantitative interpretation, you might look at the distances between clusters, such that some are more similar to each other than others, e.g. in terms of patristic distance.
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