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Multivariate Allometry

  • Chapter
Advances in Morphometrics

Part of the book series: NATO ASI Series ((NSSA,volume 284))

Abstract

The subject of allometry is variation in morphometric variables or other features of organisms associated with variation in size. Such variation can be produced by several biological phenomena, and three different levels of allometry are therefore distinguished: static allometry reflects individual variation within a population and age class, ontogenetic allometry is due to growth processes, and evolutionary allometry is the result of phylogenetic variation among taxa. Most multivariate studies of allometry have used principal component analysis. I review the traditional technique, which can be interpreted as a least-squares fit of a straight line to the scatter of data points in a multidimensional space spanned by the morphometric variables. I also summarize some recent developments extending principal component analysis to multiple groups. “Size correction” for comparisons between groups of organisms is an important application of allometry in morphometrics. I recommend use of Burnaby’s technique for “size correction” and compare it with some similar approaches. The procedures described herein are applied to a data set on geographic variation in the waterstrider Gerris costae (Insecta: Heteroptera: Gerridae). In this example, I use the bootstrap technique to compute standard errors and perform statistical tests. Finally, I contrast this approach to the study of allometry with some alternatives, such as factor analytic and geometric approaches, and briefly analyze the different notions of allometry upon which these approaches are based.

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Authors and Affiliations

  1. Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada

    Christian Peter Klingenberg

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  1. Christian Peter Klingenberg
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Editor information

Editors and Affiliations

  1. Department of Biology, Mail: Dept. Invertebrates, Queens College of the City University of New York, Flushing, New York, USA

    Leslie F. Marcus

  2. American Museum of Natural History, CPW at 79th Street, 10024, New York, New York, USA

    Leslie F. Marcus

  3. Dipartimento di Biologia Animale e dell’Uomo, University of Rome “La Sapienza”, via Borelli 50, 00161, Rome, Italy

    Marco Corti

  4. University of Rome “La Sapienza”, Rome, Italy

    Anna Loy

  5. Department of Biology, Osborn Memorial Laboratory, Yale University, P.O. Box 208104, 06520-8104, New Haven, Connecticut, USA

    Gavin J. P. Naylor

  6. Department of Ecology and Evolution, State University of New York, 11794, Stony Brook, New York, USA

    Dennis E. Slice

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© 1996 Springer Science+Business Media New York

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Klingenberg, C.P. (1996). Multivariate Allometry. In: Marcus, L.F., Corti, M., Loy, A., Naylor, G.J.P., Slice, D.E. (eds) Advances in Morphometrics. NATO ASI Series, vol 284. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-9083-2_3

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  • DOI: https://doi.org/10.1007/978-1-4757-9083-2_3

  • Publisher Name: Springer, Boston, MA

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  • Online ISBN: 978-1-4757-9083-2

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