RESUMO
The evolutionary history of Mesozoic mammaliaformes is well studied. Although the backbone of their phylogeny is well resolved, the placement of ecologically specialized groups has remained uncertain. Functional and developmental covariation has long been identified as an important source of phylogenetic error, yet combining incongruent morphological characters altogether is currently a common practice when reconstructing phylogenetic relationships. Ignoring incongruence may inflate the confidence in reconstructing relationships, particularly for the placement of highly derived and ecologically specialized taxa, such as among australosphenidans (particularly, crown monotremes), haramiyidans, and multituberculates. The alternative placement of these highly derived clades can alter the taxonomic constituency and temporal origin of the mammalian crown group. Based on prior hypotheses and correlated homoplasy analyses, we identified cheek teeth and shoulder girdle character complexes as having a high potential to introduce phylogenetic error. We showed that incongruence among mandibulodental, cranial, and postcranial anatomical partitions for the placement of the australosphenidans, haramiyids, and multituberculates could largely be explained by apparently non-phylogenetic covariance from cheek teeth and shoulder girdle characters. Excluding these character complexes brought agreement between anatomical regions and improved the confidence in tree topology. These results emphasize the importance of considering and ameliorating major sources of bias in morphological data, and we anticipate that these will be valuable for confidently integrating morphological and molecular data in phylogenetic and dating analyses.
RESUMO
Geometric morphometrics is routinely used in ecology and evolution and morphometric datasets are increasingly shared among researchers, allowing for more comprehensive studies and higher statistical power (as a consequence of increased sample size). However, sharing of morphometric data opens up the question of how much nonbiologically relevant variation (i.e., measurement error) is introduced in the resulting datasets and how this variation affects analyses. We perform a set of analyses based on an empirical 3D geometric morphometric dataset. In particular, we quantify the amount of error associated with combining data from multiple devices and digitized by multiple operators and test for the presence of bias. We also extend these analyses to a dataset obtained with a recently developed automated method, which does not require human-digitized landmarks. Further, we analyze how measurement error affects estimates of phylogenetic signal and how its effect compares with the effect of phylogenetic uncertainty. We show that measurement error can be substantial when combining surface models produced by different devices and even more among landmarks digitized by different operators. We also document the presence of small, but significant, amounts of nonrandom error (i.e., bias). Measurement error is heavily reduced by excluding landmarks that are difficult to digitize. The automated method we tested had low levels of error, if used in combination with a procedure for dimensionality reduction. Estimates of phylogenetic signal can be more affected by measurement error than by phylogenetic uncertainty. Our results generally highlight the importance of landmark choice and the usefulness of estimating measurement error. Further, measurement error may limit comparisons of estimates of phylogenetic signal across studies if these have been performed using different devices or by different operators. Finally, we also show how widely held assumptions do not always hold true, particularly that measurement error affects inference more at a shallower phylogenetic scale and that automated methods perform worse than human digitization.
