Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-05T04:11:23.608Z Has data issue: false hasContentIssue false

Covariation patterns in the postcranial skeleton of moas (Aves, Dinornithidae): A factor analytic study

Published online by Cambridge University Press:  08 February 2016

Joel Cracraft*
Affiliation:
Department of Anatomy, University of Illinois at the Medical Center; Chicago, Illinois 60680

Abstract

The covariation patterns of the postcranial skeleton in eight species of moas (Aves, Dinornithidae) from the Pleistocene of New Zealand are described using multiple factor analysis. Rotation schemes include an orthogonal Varimax and oblique (direct quartimin) simple structure solutions.

Four major patterns of covariation are resolved: a length factor, primarily that of leg length; a width factor, including pelvis width and long bone widths; a sternal breadth factor; and a sternal length-posterior pelvis length factor. The first two patterns represent a functional separation between body size and those aspects of the skeleton, scaling allometrically, adapted to support body weight. The sternal breadth factor may indicate that features contributing to trunk support are independent from those width measurements of the pelvis and hindlimb bones. The sternal length-posterior pelvis length factor reveals a pattern of covariation that is somewhat independent of other patterns (long bone lengths) determining variability in body size.

Type
Research Article
Copyright
Copyright © The Paleontological Society 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

Amadon, D. 1947. An estimated weight of the largest known bird. Condor. 49:159164.CrossRefGoogle Scholar
Andrews, H. E. 1974. Morphometrics and functional morphology of Turritella mortoni. J. Paleontol. 48:11261140.Google Scholar
Archey, G. 1941. The moa. A study of the Dinornithiformes. Bull. Auckl. Inst. Mus. 1:1145.Google Scholar
Atchley, W. R. 1971. A comparative study of the cause and significance of morphological variation in adults and pupae of Culicoides: a factor analysis and multiple regression study. Evolution. 25:563583.Google ScholarPubMed
Atchley, W. R. and Hensleigh, D. A. 1974. The congruence of morphometric shape in relation to genetic divergence in four races of morabine grasshoppers (Orthoptera: Eumastacidae). Evolution 28:416427.CrossRefGoogle ScholarPubMed
Cracraft, J. 1974. Phylogeny and evolution of the ratite birds. Ibis. 116:494521.CrossRefGoogle Scholar
Cracraft, J. in press a. The species of moas (Aves, Dinornithidae). Smithson. Contrib. Paleobiol.Google Scholar
Cracraft, J. in press b. The hindlimb elements of the Moas (Aves, Dinornithidae): a multivariate assessment of size and shape. J. Morph.Google Scholar
Dixon, W. J., ed. 1969. BMD biomedical computer programs. X-series supplement. Univ. California Publ. Autom. Comput. No. 3.Google Scholar
Fisher, D. R. 1973. A comparison of various techniques of multiple factor analysis applied to biosystematic data. Univ. Kans. Sci. Bull. 50:127162.Google Scholar
Fleming, C. A. 1962. The extinction of moas and other animals during the Holocene Period. Notornis. 10:113117.Google Scholar
Frazzetta, T. H. 1975. Complex Adaptations in Evolving Populations. 267 pp. Sinauer Assoc. Inc.; Sunderland, Mass.Google Scholar
Gould, S. J. 1967. Evolutionary patterns in pelycosaurian reptiles: a factor-analytic study. Evolution. 21:385401.CrossRefGoogle ScholarPubMed
Gould, S. J. 1974. The origin and function of “bizarre” structures: antler size and skull size in the “Irish Elk,” Megaloceros giganteus. Evolution. 28:191220.Google ScholarPubMed
Gould, S. J. and Garwood, R. A. 1969. Levels of integration in mammalian dentitions: an analysis of correlations in Nesophontes micrus (Insectivora) and Oryzomys couesi (Rodentia). Evolution. 23:276300.CrossRefGoogle ScholarPubMed
Gould, S. J. and Littlejohn, J.Factor analysis of caseid pelycosaurs. J. Paleontol. 47:886891.Google Scholar
Harman, H. H. 1967. Modern Factor Analysis. 474 pp. Univ. Chicago Press; Chicago, Ill.Google Scholar
Hutchinson, H. N. 1910. Extinct Monsters. 254 pp. D. Appleton and Co.; New York.Google Scholar
Imbrie, J. and Van Andel, T. H. 1964. Vector analysis of heavy-mineral data. Geol. Soc. Am. Bull. 75:11311156.CrossRefGoogle Scholar
Leamy, L. 1975. Component analysis of osteometric traits in randombred house mice. Syst. Zool. 24:176190.CrossRefGoogle Scholar
Lynts, G. W. and Paris, N. L. 1971. Fortran program for missing data factor-vector analysis (IBM 360–75): with test example. Southeast. Geol. 13:229263.Google Scholar
Manson, V. and Embrie, J. 1964. Fortran program for factor and vector analysis of geologic data using an IBM 7090 or 7094/1401 computer system. Kans. Geol. Surv. Comput. Contrib. 13:147.Google Scholar
Oliver, W. R. B. 1949. The moas of New Zealand and Australia. Dominion Mus. Bull. 15:1206.Google Scholar
Olson, E. C. and Miller, R. L. 1958. Morphological Integration. 317 pp. Univ. Chicago Press; Chicago, Ill.Google Scholar
Power, D. M. 1971. Statistical analysis of character correlations in Brewer's Blackbirds. Syst. Zool. 20:186203.CrossRefGoogle Scholar
Rohlf, F. J. and Sokal, R. R. 1972. Comparative morphometrics by factor analysis in two species of Diptera. Z. Morph. Tiere 72:3645.CrossRefGoogle Scholar
Rummel, R. J. 1970. Applied Factor Analysis. 617 pp. Northwestern Univ. Press; Evanston, Ill.Google Scholar