Meloro, C and Marques De Oliveira, A (2017) Elbow Joint Geometry in Bears (Ursidae, Carnivora): a Tool to Infer Paleobiology and Functional Adaptations of Quaternary Fossils. Journal of Mammalian Evolution. ISSN 1064-7554

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Abstract

Bears are currently represented by eight species among Carnivora. Being all particularly large and generally plantigrade limits to certain extent their functional morphology so that inferences about their past diversification are difficult to achieve. We analyzed variation in bears’ elbow joint size and shape to reconstruct paleobiology of Quaternary fossil species. By using 2D geometric morphometrics, we were able to discriminate with high degree of accuracy species, locomotor and habitat adaptations among extant bears. The giant panda and the spectacled bear are well characterized by an enlarged medial epicondyle, while large members of the genus Ursus can be distinguished by their relatively longer and wider trochlea. Elbow joint size varies consistently among ecological categories of extant bears and is generally selected by discriminant function models providing a high degree of classification accuracy (> 80%). American genera Arctotherium and Arctodus are predicted as non-climbing species potentially adapted to open and mixed environments in agreement with their potentially opportunistic feeding behavior. They retain a wide medial epicondyle probably in relation to a high degree of forelimb dexterity. Cave bears are equally predicted as non-climbers adapted to open habitats while the middle Pleistocene Ursus deningeri and fossil Ursus arctos are generally classified as scansorial species with a preference towards mixed habitats. Our study is the first to demonstrate that fragmentary distal epiphyses also can be useful for interpreting functional morphology and ecological adaptations within the family Ursidae.

Item Type:	Article
Uncontrolled Keywords:	0608 Zoology
Subjects:	Q Science > QL Zoology
Divisions:	Natural Sciences & Psychology (closed 31 Aug 19)
Publisher:	Springer Verlag
Date Deposited:	13 Nov 2017 09:47
Last Modified:	04 Sep 2021 03:37
DOI or ID number:	10.1007/s10914-017-9413-x
URI:	https://researchonline.ljmu.ac.uk/id/eprint/7536

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