Functional Limb Morphology of African Myosoricine Shrews (Mammalia, Soricidae)


Meeting Abstract

P3.130  Monday, Jan. 6 15:30  Functional Limb Morphology of African Myosoricine Shrews (Mammalia, Soricidae) STABILE, F. S.*; WOODMAN, N.; The College of New Jersey, Ewing; National Museum of Natural History, Smithsonian Institution, Washington, DC and Pauxtent Wildlife Research Center, United States Geological Survey, Laurel, MD stabilf1@tcnj.edu

Shrews in the African subfamily Myosoricinae exhibit considerable variation in skeletal morphology, which likely reflects variation in substrate use. To quantify this variation, we measured the postcranial skeletons of each of the three Myosoricinae genera (Surdisorex, Myosorex, and Congosorex). We then calculated 20 standard indices and used these to rank the potential burrowing ability of each species relative to Uropsilus soricipes, a terrestrial mole, and Neurotrichus gibbsii, a semifossorial mole. Indices related to the manus and the humerus provided the best indicators of fossoriality. Our ranking system yielded three groupings: Congosorex phillipsorum, Myosorex cafer, M. kihaulei, and M. geata are similar to Uropsilus and represent primarily terrestrial species. The remaining MyosorexM. zinki, M. blarina, M. varius—have an intermediate morphology between the two moles and show some adaptations for burrowing. The Surdisorex are most similar to Neurotrichus and are best equipped to burrow. In terrestrial species, the distal phalanges and claws are short, the metacarpals long and thin, and the humerus slender, with small epicondyles, a short teres tubercle, and a small deltopectoral crest. In semifossorial species, the distal phalanges and claws are elongate and the metacarpals short and thick. The humerus is robust with wide epicondyles, a long teres tubercle, and a large deltopectoral crest. Myosoricine shrews exhibit quantifiable morphological variation that reflects a potentially broad range of substrate use. Thus, the postcranial skeleton is useful not only for species identification, but also for predictions of digging behavior.

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