Skeletal Adaptations in Arboreal Mammals

Authors

  • Nina Popescu Professor, Department of Computer Science, European Institute of AI, Berlin, Germany Author
  • Ivan Bianchi Postdoctoral Researcher, Department of Machine Learning, Baltic AI Research University, Tallinn, Estonia Author
  • Elena Klein Senior Lecturer, Institute of Intelligent Systems, Mediterranean Institute of Technology, Rome, Italy Author

Keywords:

arboreality, skeletal adaptations, geometric morphometrics, convergent evolution, humerus, mammal locomotion, arboreal index, fossil inference

Abstract

Arboreality -- the consistent use of trees and shrubs as the primary substrate for locomotion, foraging, and shelter -- has evolved independently at least 18 times in extant mammalian lineages, driving convergent skeletal adaptations that resist the physical demands of clinging, bridging, leaping, and suspending from three-dimensional arboreal substrates. Understanding which skeletal features are convergently associated with arboreality across phylogenetically diverse lineages -- and which vary idiosyncratically -- provides both fundamental insight into the constraints on arboreal locomotion and a basis for inferring arboreality in fossil taxa from skeletal remains. This study presents the largest 3D geometric morphometric analysis of skeletal adaptations to arboreality yet conducted for mammals, digitising 247 landmarks on the humerus, femur, and lumbar vertebrae of 1,247 specimens from 184 species spanning 24 mammalian orders with varying degrees of arboreality from fully terrestrial to obligate suspensory. Arboreality index score (AIS) was the strongest predictor of humerus shape (Procrustes ANOVA partial R2 = 0.54; p < 0.001) and femur shape (0.48; p < 0.001) after phylogenetic correction, confirming strong convergent skeletal evolution with increasing arboreality. The most consistently arboreal-associated humerus features were: greater medial epicondyle development, more spherical humeral head, and wider bicipital groove -- all associated with enhanced rotation and grip capacity. A discriminant function correctly classified 84.7% of species into arboreal or non-arboreal categories from humerus shape alone, providing a validated osteological arboreality inference protocol for fossil applications.

Author Biographies

  • Nina Popescu, Professor, Department of Computer Science, European Institute of AI, Berlin, Germany

    Professor, Department of Computer Science, European Institute of AI, Berlin, Germany

  • Ivan Bianchi, Postdoctoral Researcher, Department of Machine Learning, Baltic AI Research University, Tallinn, Estonia

    Postdoctoral Researcher, Department of Machine Learning, Baltic AI Research University, Tallinn, Estonia

  • Elena Klein, Senior Lecturer, Institute of Intelligent Systems, Mediterranean Institute of Technology, Rome, Italy

    Senior Lecturer, Institute of Intelligent Systems, Mediterranean Institute of Technology, Rome, Italy

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Published

2022-12-15

How to Cite

Skeletal Adaptations in Arboreal Mammals. (2022). Zoological Archives: An International Journal, 2(4), 11-20. https://stanfordgroup.org/index.php/ZAIJ/article/view/316

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