Despite the accumulating evidence suggesting the importance of phenotypic plasticity in diversification and adaptation, little is known about plastic variation in primate skulls. The present study evaluated the plastic variation of the mandible in Japanese macaques by comparing wild and captive specimens. The results showed that captive individuals are square-jawed with relatively longer tooth rows than wild individuals. We also found that this shape change resembles the sexual dimorphism, indicating that the mandibles of captive individuals are to some extent masculinized. By contrast, the mandible morphology was not clearly explained by ecogeographical factors. These findings suggest the possibility that perturbations in the social environment in captivity and resulting changes of androgenic hormones may have influenced the development of mandible shape. As the high plasticity of social properties is well known in wild primates, social environment may cause the inter- and intra-population diversity of skull morphology, even in the wild. The captive–wild morphological difference detected in this study, however, can also be possibly formed by other untested sources of variation (e.g. inter-population genetic variation), and therefore this hypothesis should be validated further.

Macaques (genus Macaca) are known to have wide variation in tail length. Within each species group tail length varies, which could be associated with a phylogenetic trend seen in caudal vertebral morphology. We compared numbers and lengths of caudal vertebrae in species of the fascicularis group, M. assamensis (sinica group), M. nemestrina (silenus group), and those obtained from reports for an additional 11 species. Our results suggest different trends in number and lengths. The caudal vertebral length profiles revealed upward convex patterns for macaques with relative tail lengths of ≥15%, and flat to decreasing for those with relative tail lengths of ≤12%. They varied between species groups in terms of the lengths of proximal vertebrae, position and length of the longest vertebra, numbers and lengths of distal vertebrae, and total number of vertebrae. In silenus and sinica group, the vertebral length is the major skeletal determinant of tail length. On the other hand, the vertebral number is the skeletal determinant of tail length in the fascicularis group. Tail length variation among species groups are caused by different mechanisms which reflect the evolutionary history of macaques.

Aim: Understanding patterns and processes of geographic genetic variation within and among closely related species is the essence of phylogeography. Japanese macaques, also called snow monkeys, have been extensively studied, particularly in the fields of sociobiology, ecology and experimental biology; however, our knowledge of their evolutionary history is relatively limited. In this study we aimed to elucidate the geographic patterns of genetic variation in Japanese macaques and the processes that underlie them. Location: Japan.

The importance of hybridization in morphological diversification is a fundamental topic in evolutionary biology. However, despite accumulated knowledge concerning adult hybrid variations, how hybridization affects ontogenetic allometry is less well understood. Herein, we assessed the effects of hybridization on the postnatal ontogenetic allometry in skulls of a putative hybrid population of introduced Taiwanese macaques (Macaca cyclopis) and native Japanese macaques (M. fuscata). Genomic analyses indicated that the population consisted of individuals with various degrees of admixture, formed by male migration of Japanese to Taiwanese macaques. Hybridization parallelly shifted the ontogenetic trajectories of the overall skull shape in an almost additive manner. Transgressive variations in the overall skull shape were observed mainly in non-allometric components. Hybridization lifted the restriction found in Japanese macaques on the growth rate of the maxillary sinus (the hollow space in the face), producing hybrids with a mosaic pattern, i.e., the maxillary sinus is as large as that in Taiwanese macaques, although the overall skull shape is intermediate. Our findings suggest that the transgressive variations can be caused by prenatal shape modifications and the lifting of the genetic restriction on the regional growth rate, highlighting the complex genetic and ontogenetic factors underlying hybridization-induced morphological diversification.

Objectives: Morphometrics has played essential roles in the comprehension of biological variation and the evolution of morphological phenotypes. This approach usually imposes strict requirements on data, such as rigid alignment of subjects, and the collection and manual preprocessing of data meeting these requirements are often time consuming. Artificial intelligence (AI) technology is developing and it potentially reduces this load, but they usually presuppose the availability of "big data" for successful learning, beyond the empirically plausible amount in biological studies. Here, we propose a deep learning-based analysis of three-dimensional data. Materials and Methods:We built a deep learning-based analysis of three-dimensional morphological data that does not require strict alignment or an implausible sample size. We benchmarked the proposed method by case studying sex classification of macaques, referring to computed tomography scans of their mandible. Results:The model learned from just 139 mandible specimens of Japanese macaques and successfully generalized the learned classification to previously unseen specimens of the same species and even other species of macaques. Moreover, we visualized those characteristic regions in the data that the model used during sex classification and showed that they were consistent with the criteria used by human experts.Discussion: Our analysis does not require rigidly aligned data, so can effectively use data collected in previous studies with different focus/aims. This proposed AI method can potentially help researchers to discover new morphological features of different species and other biological groups. Implementation of this proposed AI system will be available to other researchers for further investigation.