Data from: Phylogenetic inference from atomised 3D morphometric data: a case study using kangaroos

Reconstructing phylogeny from morphological data remains mired in
investigator biases, including subjective inclusion and discretisation of
phenotypic variation. Geometric morphometrics and multivariate statistical
analyses provide an alternative array of tools for studying variation in
morphological traits. However, direct analysis of landmark data is often
unreliable for phylogeny reconstruction. Morphological variation is
typically highly correlated among nearby landmarks and may evolve
saltationally between adaptive peaks instead of gradually, thereby
violating the assumptions of typical continuous models. To address these
concerns, we developed an approach to more objectively discretise
morphometric data and applied it to 3D surface scans of mandibles and
postcranial elements of Macropodiformes (kangaroos, bettongs, and
rat-kangaroos). These scans were partitioned into sets of locally
co-varying landmarks which approximate functional units. These “atomised”
characters were then discretised using novel approaches to combine the
objectivity of continuous shape variation for delineating discrete states
with the model flexibility offered for multi-state characters. This allows
us to (1) potentially reduce the influence  of non-independence
among neighbouring landmarks, (2) accommodate multimodal variation from
saltational evolution, (3) accommodate missing data, such as from
fragmentary fossils, and (4) promote tree-search efficiency. We built
discrete morphological character matrices using three alternative
approaches: commonly used clustering algorithms (UPGMA, *k-*means,
*k-*medoids, Gaussian mixture modelling), a minimum evolution branch
length criterion, and a tree sampling procedure. Our phylogenetic analyses
with these novel matrices generally succeeded in recovering genera and
several deep-level macropodiform clades, but failed to accurately
reconstruct intergeneric relationships within the rapid diversification of
the macropodine sub-family; those relationships were also not recovered
with continuous morphological data or traditionally discretised characters
and are the most poorly resolved with DNA data. On balance, our atomised
characters, which derive from only mandibular and three postcranial
elements, show promise for improving objectivity, accuracy and
clocklikeness in morphological phylogenetics and provide pathways for
accommodating correlated homoplasy and for more accurately estimating
rates of morphological evolution, and thereby better integrating
phenotypic and genomic data for phylogenetic inference.