Running head: INFERRING PHYLOGENIES FROM CONTINUOUS CHARACTERS

8 The recent surge in enthusiasm for simultaneously inferring relationships from extinct and 9 extant species has reinvigorated interest in statistical approaches for modelling morphological 10 evolution. Current statistical methods use the Mk model to describe substitutions between 11 discrete character states. Although representing a significant step forward, the Mk model presents 12 challenges in biological interpretation, and its adequacy in modelling morphological evolution 13 has not been well explored. Another major hurdle in morphological phylogenetics concerns the 14 process of character coding of discrete characters. The often subjective nature of discrete 15 character coding can generate discordant results that are rooted in individual researchers’ 16 subjective interpretations. Employing continuous measurements to infer phylogenies may 17 alleviate some of these issues. Although not widely used in the inference of topology, models 18 describing the evolution of continuous characters have been well examined, and their statistical 19 behaviour is well understood. Also, continuous measurements avoid the substantial ambiguity 20 often associated with the assignment of discrete characters to states. I present a set of simulations 21 to determine whether use of continuous characters is a feasible alternative or supplement to 22 discrete characters for inferring phylogeny. I compare relative reconstruction accuracy by 23 inferring phylogenies from simulated continuous and discrete characters. These tests demonstrate 24 significant promise for continuous traits by demonstrating their higher overall accuracy as 25 compared to reconstruction from discrete characters under Mk when simulated under unbounded 26 Brownian motion, and equal performance when simulated under an Ornstein-Uhlenbeck model. 27 Continuous characters also perform reasonably well in the presence of covariance between sites. I 28 argue that inferring phylogenies directly from continuous traits may be benefit efforts to maximise 29 phylogenetic information in morphological datasets by preserving larger variation in state space 30 2 . CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/121343 doi: bioRxiv preprint first posted online Mar. 28, 2017;