We recently published a computer program called PhyloM that constructs a tree based on measurement data—such as morphological, metabolic, or physiological traits—collected from a group of species or other taxa. The tree is inferred from pairwise distances computed directly from the observed trait data. These distances are analogous to uncorrected p-distances from sequence alignments, which are effective when divergence times are low. However, as divergence increases, p-distances become saturated and no longer reflect true evolutionary distances. In molecular phylogenetics, this problem is addressed using substitution models that account for hidden changes.

In a similar spirit, I would like to incorporate evolutionary models of continuous trait change—starting with simple models such as Brownian Motion and the Ornstein–Uhlenbeck process—to better model trait divergence over time. However, developing and implementing such models lies outside my current mathematical expertise.

I am therefore seeking collaborators, particularly early-career evolutionary biologists with an interest in mathematical modeling, to help take PhyloM in this new direction. There is a possibility of funding travel to support this collaboration through an active opportunity.

If this sounds interesting, please feel free to message me directly at [email protected].