A comparison of machine learning techniques for taxonomic classification of teeth from the Family Bovidae

Inferring the locomotor ecology of two of the oldest fossil squirrels: influence of operationalization, trait, body size and machine learning method

Correlations between morphology and lifestyle of extant taxa are useful for predicting lifestyles of extinct relatives. Here, we infer the locomotor behaviour of Palaeosciurus goti from the middle Oligocene and Palaeosciurus feignouxi from the lower Miocene of France using their femoral morphology and different machine learning methods. We used two ways to operationalize morphology, in the form of a geometric morphometric shape dataset and a multivariate dataset of 11 femoral traits. The predictive models were built and tested using more than half (180) of the extant species of squirrel relatives. Both traditional models such as linear discriminant analysis and more sophisticated models like neural networks had the greatest predictive power. However, the predictive power also depended on the operationalization and the femoral traits used to build the model. We also found that predictive power tended to improve with increasing body size. Contrary to previous suggestions, the older species, P. goti, was most likely arboreal, whereas P. feignouxi was more likely terrestrial. This provides further evidence that arboreality was already the most common locomotor ecology among the earliest squirrels, while a predominantly terrestrial locomotor behaviour evolved shortly afterwards, before the vast establishment of grasslands in Europe.

African bovid tribe classification using transfer learning and computer vision

Objective analytical identification methods are still a minority in the praxis of paleobiological sciences. Subjective interpretation of fossils and their modifications remains a nonreplicable expert endeavor. Identification of African bovids is a crucial element in the reconstruction of paleo-landscapes, ungulate paleoecology, and, eventually, hominin adaptation and ecosystemic reconstruction. Recent analytical efforts drawing on Fourier functional analysis and discrimination methods applied to occlusal surfaces of teeth have provided a highly accurate framework to correctly classify African bovid tribes and taxa. Artificial intelligence tools, like computer vision, have also shown their potential to be objectively more accurate in the identification of taphonomic agency than human experts. For this reason, here we implement some of the most successful computer vision methods, using transfer learning and ensemble analysis, to classify bidimensional images of African bovid teeth and show that 92% of the large testing set of images of African bovid tribes analyzed could be correctly classified. This brings an objective tool to paleoecological interpretation, where bovid identification and paleoecological interpretation can be more confidently carried out.

Comparative morphometric analyses of the deciduous molars of Homo naledi from the Dinaledi Chamber, South Africa

OBJECTIVES

The purpose of this study is to help elucidate the taxonomic relationship between Homo naledi and other hominins.

MATERIALS AND METHODS

Homo naledi deciduous maxillary and mandibular molars from the Dinaledi Chamber, South Africa were compared to those of Australopithecus africanus, Australopithecus afarensis, Paranthropus robustus, Paranthropus boisei, early Homo sp., Homo erectus, early Homo sapiens, Upper Paleolithic H. sapiens, recent southern African H. sapiens, and Neanderthals by means of morphometric analyses of crown outlines and relative cusp areas. The crown shapes were analyzed using elliptical Fourier analyses followed by principal component analyses (PCA). The absolute and relative cusp areas were obtained in ImageJ and compared using PCA and cluster analyses.

RESULTS

PCA suggests that the crown shapes and relative cusp areas of mandibular molars are more diagnostic than the maxillary molars. The H. naledi deciduous mandibular first and second molar (dm₁ and dm₂ ) do not have a strong affinity to any taxon in the comparative sample in all analyses. While the H. naledi dm₂ plots as an outlier in the relative cusp analysis, the H. naledi specimen fall closest to Australopithecus due to their relatively large metaconid, a primitive trait for the genus Homo. Although useful for differentiating Neanderthals from recent southern African H. sapiens and UP H. sapiens, the PCA of the relative cusp areas suggests that the deciduous maxillary second molars (dm² ) do not differentiate other groups. The three H. naledi dm² cuspal areas are variable and fall within the ranges of other Homo, as well as Australopithecus, and Paranthropus suggesting weak diagnostic utility.

DISCUSSION

This research provides another perspective on the morphology of, and variation within, H. naledi. The H. naledi deciduous molars do not consistently align with any genus or species in the comparative sample in either the crown shape or relative cusp analyses. This line of inquiry is consistent with other cranial and postcranial studies suggesting that H. naledi is unique.