Overview of the New, or Geometric Morphometrics

  • Leslie F. Marcus
  • Marco Corti
Chapter
Part of the NATO ASI Series book series (NSSA, volume 284)

Abstract

The new morphometrics, or geometric morphometrics, is a rapidly evolving field. “Morphometrics” has been used to describe a number of fields that study measurements of organisms, and that is why the modifier “new” or “geometric” is necessary to set aside the special subject matter discussed here: the shape of biological organisms as it is studied using as data, point coordinates in two or three dimensions. This includes landmark and outline coordinates. Landmarks are specific points on an organism that correspond in a sensible way over the forms being studied, that is they are homologs; while outline points do not share this notion of homology. The data of morphometrics is now being extended to include tangent directions at coordinates as well (see Bookstein and Green, 1993; Little and Mardia, this volume). Shape is primarily concerned with properties of coordinates that are invariant to scale, location and orientation (see Appendix I, Glossary). The current status of morphometrics together with some future objectives are summarized in a review by Rohlf and Marcus (1993a).

Keywords

Covariance Corti Archie 

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References

  1. Becerra, J. M., E. Bello, and A. Garcia-Valdecasas 1993. Building your own machine image system: A user point of view. Pages 65–92 in L. F. Marcus, E. Bello, and A. Garcia-Valdecasas, (eds.), Contributions to morphometrics. Monografias del Museo Nacional de Ciencias Naturales 8, Madrid.Google Scholar
  2. Bookstein, F. L. 1989a. “Size and shape”: A comment on semantics. Systematic Zoology 38: 173–180.Google Scholar
  3. Bookstein, F. L. 1989b. Principal warps: thin-plate splines and the decomposition of deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence 11: 567–585.CrossRefGoogle Scholar
  4. Bookstein, F. L. 1991. Morphometric tools for landmark data: Geometry and biology. Cambridge University Press: CambridgeGoogle Scholar
  5. Bookstein, E. L. 1993. A brief history of the morphometric synthesis. Pages 15–40 in L. F. Marcus, E. Bello, and A. Garcia-Valdecasas, (eds.), Contributions to morphometrics. Monografias del Museo Nacional de Ciencias Naturales 8, Madrid.Google Scholar
  6. Bookstein, F. L. 1994. Can biometrical shape be a homologous character? Pages 197–227 in B. K. Hall, (ed.), Homology: The hierarchical basis of comparative biology. Academic Press: New York.Google Scholar
  7. Bookstein, F. L., B. Chernoff, R. L. Elder, J. M. Humphries, Jr., G. R. Smith, and R. E. Strauss. 1985. Morphometrics in evolutionary biology: The geometry of size and shape change, with examples from fishes. Academy of Natural Sciences of Philadelphia Special Publication 15. [Red book]Google Scholar
  8. Bookstein, E. L. and W. D. K. Green 1993. A feature space for edgels in images with landmarks. Journal of Mathematical Imaging and Vision 3: 231–261.CrossRefGoogle Scholar
  9. Corti, M. 1993. Geometric morphometrics: An extension to the revolution. Trends in Ecology and Evolution 8 (2): 302–303.PubMedCrossRefGoogle Scholar
  10. Fink, W. L. 1990. Data acquisition for morphometric analysis in systematic biology. Pages 9–19 in F. J. Rohlf and F. L. Bookstein, (eds.), Proceedings of the Michigan Morphometrics Workshop. University of Michigan Museum of Zoology Special Publication 2.Google Scholar
  11. Fink, W. L. and M. L. Zelditch. 1995. Phylogenetic analysis of ontogenetic shape transformations: A reassessment of the piranha genus Pygocentris ( Telostei ). Systematic Biology 44: 343–360.Google Scholar
  12. Goodall, C. R. 1991. Procrustes methods in the statistical analysis of shape (with discussion and rejoinder). Journal of the Royal Statistical Society, Series B, 53: 285–339.Google Scholar
  13. Green, W. D. K. 1995. Spline-based deformable models. Pages 290–301 in R. Metter, A. Wu., F. Bookstein, and W. D. K. Green, (eds.), Vision geometry IV. SPIE Proceedings.Google Scholar
  14. Isaev, M. 1995. EFAWin: Window shell for Elliptic Fourier. Genesys Labs, 1111 BayHill Dr, Suite 180, San Bruno, CA 94066.Google Scholar
  15. Laduke, T. C. 1991. Morphometric variability of the precaudal vertebrae of Thamnophis sirtalis sirtalis (Serpentes: Colubridae), and implications for interpretation of the fossil record. Ph. D. dissertation, City University of New York.Google Scholar
  16. Lele, S. 1993. Euclidean distance matrix analysis (EDMA): Estimation of mean form and mean form difference. Mathematical Geology 25: 573–602.Google Scholar
  17. Lele, S., and J. T. Richtsmeier. 1991. Euclidean distance matrix analysis: A coordinate free approach for comparing biological shapes using landmark data. American Journal of Physical Anthropology 86: 415–428.Google Scholar
  18. Lele, S. and J. T. Richtsmeier. 1992. On comparing biological shapes: Detection of influential landmarks. American Journal of Physical Anthropology 87: 49–65.Google Scholar
  19. Loy, A., M. Corti, and L. F. Marcus. 1993. Landmark data: Size and shape analysis in systematics. A case study on Old World Talpidae (Mammalia, Insectivora). Pages 215–240 in L. F. Marcus, E. Bello, and A. Garcia-Valdecasas, (eds.), Contributions to morphometrics, Monografias del Museo Nacional de Ciencias Naturales 8, Madrid.Google Scholar
  20. MacLeod, N. 1990. Digital images and automated image analysis systems. Pages 21–35 in F. J. Rohlf and F. L. Bookstein, (eds.), Proceedings of the Michigan morphometrics workshop. University of Michigan Museum of Zoology Special Publication 2.Google Scholar
  21. Marcus, L. F. 1988. Automated data acquisition in museums. Workshop on Computers in Museums, University of Mexico. Spectra.Google Scholar
  22. Marcus L. F., E. Bello and A. Garcia-Valdecasas. (eds.). 1993. Contributions to morphometrics. Monografias del Museo Nacional de Ciencias Naturales 8, Madrid. [Black book]Google Scholar
  23. Mardia, K. V., and C. A. Gill (eds.). 1995. Proceedings in current issues in statistical shape analysis. Leeds University Press: Leeds, United Kingdom.Google Scholar
  24. Reyment, R. A. 1991. Multidimensional palaeobiology. Pergamon Press: Oxford.Google Scholar
  25. Rohlf, F. J. 1986. Relationships among eigenshape analysis, Fourier analysis, and analysis of coordinates. Mathematical Geology 18: 845–854.Google Scholar
  26. Rohlf, F. J. 1990a. Rotational fit (Procrustes) methods. Pages 227–236 in F. J. Rohlf and F. L. Bookstein, (eds.), Proceedings of the Michigan morphometrics workshop. University of Michigan Museum of Zoology Special Publication 2.Google Scholar
  27. Rohlf, F. J. 1990b. An overview of image processing and analysis techniques for morphometrics. Pages 37–60 in F. J. Rohlf and F. L. Bookstein, (eds), Proceedings of the Michigan morphometrics workshop. University of Michigan Museum of Zoology Special Publication 2.Google Scholar
  28. Rohlf, F. J. 1990c. Fitting curves to outlines. Pages 167–177 in F. J. Rohlf and F. L. Bookstein, (eds.), Proceedings of the Michigan morphometrics workshop. University of Michigan Museum of Zoology Special Publication 2.Google Scholar
  29. Rohlf, F. J. 1990d. TPSPLINE: A program to compare two shapes using a thin-plate spline. Department of Ecology and Evolution, State University of New York, Stony Brook, New York 11794.Google Scholar
  30. Rohlf, F. J. 1993a. NTSYS-pc - Numerical taxonomy and multivariate analysis system, version 1. 80. Exeter Software: Setauket, New York.Google Scholar
  31. Rohlf, F. J. 19936. Feature extraction in systematic biology. Pages 375–392. in R. Fortuner, (ed), Advances in computer methods for systematic biology: Artificial intelligence, databases, computer vision. John Hopkins University Press: Baltimore.Google Scholar
  32. Rohlf, F. J. 1993c. TPSREGR: A program for regression of partial warp scores. Department of Ecology and Evolution, State University of New York, Stony Brook, New York 11794.Google Scholar
  33. Rohlf, F. J. 1993d. Relative warp analysis and an example of its application to mosquito wings. Pages 131–159 in L. F. Marcus, E. Bello and A. García-Valdecasas, (eds.), Contribution to morphometrics. Monografias del Museo Nacional de Ciencias Naturales 8, Madrid.Google Scholar
  34. Rohlf, F. J. 1993e. TPSRW-Thin-plate spline relative warp. Department of Ecology and Evolution, State University of New York, Stony Brook, New York 11794.Google Scholar
  35. Rohlf, F. J., and J. W. Archie. 1978. Least-squares mapping using interpoint distances. Ecology 59 (1): 126–132.CrossRefGoogle Scholar
  36. Rohlf, F. J. and J. W. Archie. 1984. A comparison of Fourier methods for the description of wing shape in mosquitoes ( Diptera: Culicidae). Systematic Zoology 33: 302–317.Google Scholar
  37. Rohlf, F. J and F. L. Bookstein (eds.). 1990. Proceedings of the Michigan morphometrics workshop. University of Michigan Museum of Zoology Special Publication 2. [Blue book]Google Scholar
  38. Rohlf, F. J., and L. F. Marcus. 1993a. A revolution in morphometrics. Trends in Ecology and Evolution 8 (4): 129–132.CrossRefGoogle Scholar
  39. Rohlf, F. J., and L. F. Marcus. 1993b. Geometric morphometrics: Reply to M. Corti. Trends in Ecology and Evolution 8 (9): 339.CrossRefGoogle Scholar
  40. Rohlf, F. J., and D. E. Slice. 1990a. Extensions of the Procrustes method for the optimal superimposition of landmarks. Systematic Zoology 39: 40–59.CrossRefGoogle Scholar
  41. Rohlf, F. J., and D. E. Slice. I990b. GRF: A program for generalized rotational fitting. Department of Ecology and Evolution, State University of New York, Stony Brook, New York 11794.Google Scholar
  42. Slice, D. E. 1993a. Extensions, comparisons, and applications of superimposition methods for morphometric analysis. Ph.D. dissertation: State University of New York at Stony Brook.Google Scholar
  43. Slice, D. E. 1993b. GRF-ND: generalized rotational fitting of N-dimensional data. Department of Ecology and Evolution, State University of New York, Stony Brook, New York 11794.Google Scholar
  44. Spencer, M. A. and G. S. Spencer. 1995. Video-based three-dimensional morphometrics. American Journal of Physical Anthropology 96: 443–453.PubMedCrossRefGoogle Scholar
  45. Swiderski, D. L. 1994. Morphological evolution of the scapula in tree squirrels, chipmunks and ground squirrels (Sciuridae): An analysis using thin-plate splines. Evolution 47: 1854–1873.Google Scholar
  46. Zelditch, M. L., W. L. Fink, and D. L. Swiderski. 1995. Morphometrics, homology and phylogenetics: Quantified characters as synapomorphies. Systematic Biology 44(2):179–189.Google Scholar

Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Leslie F. Marcus
  • Marco Corti

There are no affiliations available

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