Data from: Estimating morphological diversity and tempo with discrete character-taxon matrices: implementation, challenges, progress, and future directions

Discrete character-taxon matrices are increasingly being used in an
attempt to understand the pattern and tempo of morphological evolution;
however, methodological sophistication and bespoke software
implementations have lagged behind. In the present study, an attempt is
made to provide a state-of-the-art description of methodologies and
introduce a new R package (Claddis) for performing foundational disparity
(morphologic diversity) and rate calculations. Simulations using its core
functions show that: (1) of the two most commonly used distance metrics
(Generalized Euclidean Distance and Gower's Coefficient), the latter
tends to carry forward more of the true signal; (2) a novel distance
metric may improve signal retention further; (3) this signal retention may
come at the cost of pruning incomplete taxa from the data set; and (4) the
utility of bivariate plots of ordination spaces are undermined by their
frequently extremely low variances. By contrast, challenges to estimating
morphologic tempo are presented qualitatively, such as how trees are
time-scaled and changes are counted. Both disparity and rates deserve
better time series approaches that could unlock new macroevolutionary
analyses. However, these challenges need not be fatal, and several
potential future solutions and directions are suggested.