Getting Its Feet on the Ground: Elucidating Paralouatta’s Semi-Terrestriality Using the Virtual Morpho-Functional Toolbox

Abstract

Currently, there are no living platyrrhine primates inhabiting the main Caribbean islands. Nevertheless, the fossil record of this area has provided outstanding findings of different New World monkeys that were part of a diverse radiation exhibiting remarkably unusual morphologies. Among these, the Cuban genus Paralouatta corresponds to one of the most enigmatic primates ever found in the Greater Antilles. Some researchers have argued that Paralouatta's post-cranium shows evidence of semi-terrestriality, a locomotor adaptation that is unusual, if not unique, in platyrrhine evolutionary history. Whether or not Paralouatta was truly semi-terrestrial remains uncertain, however, due to a lack of more sophisticated functional analyses on its morphology. Using novel virtual morpho-functional techniques on a comparative sample of 3D talar models belonging to diverse primate species representing three substrate preferences, this study aims to further evaluate whether Paralouatta was a semi-terrestrial genus or not. Geometric morphometrics and finite element analysis were used to empirically assess shape and biomechanical performance, respectively, and then several machine-learning (ML) classification algorithms were trained using both morphometric and biomechanical data to elucidate the substrate preference of the fossils. The ML algorithms categorized the Paralouatta specimens as either arboreal or as species commonly active on both ground and in trees. These mixed results are suggestive of some level of semi-terrestriality, thus representing the only known example of this locomotor behavior in platyrrhine evolutionary history.

Dental form and function in the early feeding diversification of dinosaurs

“…The diet of early dinosaurs was predicted by applying machine learning algorithms to the biomechanical and morphological data, following the workflow proposed in ( 28 , 29 ). The classification was conducted on the PC coordinates corresponding to the PCs that accounted for 90% of the variance (two PCs for biomechanical data and five PCs for morphological data) and the dietary information from living species, divided into three classes (carnivores, herbivores, and omnivores).…”

“…Decision boundary plots were created using the two variables with the highest importance in each model to establish class predictions in 2D morphospaces, following Püschel et al. ( 28 , 29 ).…”

“…Because low but significant phylogenetic signal is present in both biomechanical and morphological datasets, the classification models may be affected by the phylogenetic structure of the data. Decision boundary plots were created using the two variables with the highest importance in each model to establish class predictions in 2D morphospaces, following Püschel et al (28,29).…”

“…These are powerful tools to unravel the relationship between dental form and function and support dietary inferences in extinct taxa, especially when informed by ecological information from modern analogs ( 26 , 27 ). These morphofunctional and ecological data, combined with machine learning classification methods, can generate robust predictions of ecology in extinct species ( 28 , 29 ).…”

Characterizing the body morphology of the first metacarpal in the Homininae using 3D geometric morphometrics

“…The LDA was carried out using the lda() function of the ‘MASS’ 7.3-51.6 R package (Venables & Ripley, 2002). Performance was calculated using the confusion matrix from which the overall classification accuracy was computed, as well as the Cohen’s Kappa statistic (Püschel, Marcé-Nogué, Gladman, et al, 2020; Püschel, Marcé-Nogué, Gladman, Bobe, & Sellers, 2018). The complete dataset was resampled using a ‘leave-one-subject-out’ cross-validation, as a way to asses classification performance (Kuhn & Johnson, 2013).…”