Shape Changes during the Growth of the Sea Bass, Dicentrarchus labrax (Teleostea: Perciformes), in Relation to Different Rearing Conditions

An Application of Thin-Plate Spline Regression Analysis
  • Angelo Loy
  • Stefano Cataudella
  • Marco Corti
Part of the NATO ASI Series book series (NSSA, volume 284)


Thin-plate spline regression analysis is applied to sample of sea bass Dicentrarchus labrax, reared at two different salinities, i.e., marine and freshwater, in order to show shape changes and to test statistically morphological differences. All specimens were derived from the same breeding stock and were sampled at five different ages. Centroid size is used as the independent variable in the thin-plate spline regression analysis, and splines at extreme values of centroid size are computed and plotted. Differences in centroid size, for Bookstein’s uniform components (UI and U2) as well as for the pure nonuniform components of shape change are tested for significance. These analyses allow a visualization of allometry and description and testing of significance of the morphological plasticity of the sea bass. In this sense they can be valuable tools in the study of shape change during ontogeny.


Shape Change Generalize Little Square Dicentrarchus Labrax Centroid Size Breeding Stock 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Barlow, G. W. 1961. Causes and significance of morphological variation in fishes. Systematic Zoology 10:105–117Google Scholar
  2. Barnab, G. 1980. Expose synoptique des donnees biologiques sur le loup ou bar Dicentrarcus labrax (Linne, 1758). FAO Fisheries. Synopsis. 126.Google Scholar
  3. Bookstein, F. L., 1989. Principal warps: Thin-plate splines and the decomposition of deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence 11: 567–585.Google Scholar
  4. Bookstein, F. L. 1991. Morphometric tools for landmark data: Geometry and biology. Cambridge University Press: Cambridge.Google Scholar
  5. Chervinsky, J. 1974. Sea bass (Dicentrarchus labrax L., Pisces, Serranidae) a “police fish” in freshwater ponds and its adaptability to various saline conditions. Bamigdeh 26: 110–113.Google Scholar
  6. Chervinsky, J. 1979. Preliminary experiments on the adaptability of juvenile European sea bass (Dicentrarchus labrax) and gilthead sea bream (Sparus aurata) to brackish water. Bamigdeh 31: 14–17.Google Scholar
  7. Corti, M. 1992. Data analysis in systematics: A workshop and a manual to introduce geometric morphometrics. ICOLATER., Caracas, Venezuela (Document accessible through anonymous FTP from—see Appendix 3 for instructions)Google Scholar
  8. Corti, M. A. Loy, and S. Cataudella. 1996. Ecophenotypism in the sea bass, Dicentrarchus labrax ( Moronidae: Teleostea), after acclimation to freshwater. A geometric morphometric analysis using Shape Coordinates. Envir. Biol. Fish.Google Scholar
  9. Holliday, F. G. T. 1988. The effects of salinity on the eggs and larvae of teleosts. in W. S. Hoar and D. J. Randall (eds.), The physiology of developing fish. Volume I. Academic Press: New York.Google Scholar
  10. Mayr, E. 1963. Animal species and evolution. Bellknap Press of Harvard University Press: Cambridge, Massachusetts.Google Scholar
  11. Reyment, R. A. 1991. Multidimensional paleobiology. Pergamon Press: Oxford.Google Scholar
  12. Rohlf, F. J. 1993a. TPSRW—Thin-plate spline relative warp. Department of Ecology and Evolution, State University of New York, Stony Brook, New York 11794Google Scholar
  13. Rohlf, F. J. 1993b. Relative warp analysis and an example of its application to mosquito wings. Pages 131–159 in L. F. Marcus, E. Bello and A. Garcia-Valdecasas, (eds.), Contribution to morphometrics., Monografias del Museo Nacional de Ciencias Naturales 8, Madrid.Google Scholar
  14. 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
  15. Rohlf, F. J. and L. F. Marcus. 1993. A revolution in morphometrics. Trends in Ecology and Evolution 8: 129–132.CrossRefGoogle Scholar
  16. Rohlf, F. J. and D. Slice, 1990. Extension of the Procrustes method for the optimal superimposition of landmarks. Systematic Zoology 39: 40–59.CrossRefGoogle Scholar
  17. Slice, D. 1991. DS-DIGIT: Basic digitizing software. Department of Ecology and Evolution, State University of New York, Stony Brook, New York 11794.Google Scholar
  18. Slice D. 1993. GRF-ND. Generalized rotational fitting on n-dimensional landmark data. Department of Ecology and Evolution, State University of New York, Stony Brook, New York 11794.Google Scholar
  19. Sokal, R. R., and F. J. Rohlf, 1981. Biometry: The principles and practice of statistics in biological research. 2nd edition. W. H. Freeman: San Francisco.Google Scholar
  20. Yashuov, A. 1969. Preliminary report on induced spawning of M. cephalus L. reared in captivity in fresh water ponds. Bamigdeh 21: 19–24.Google Scholar

Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Angelo Loy
    • 1
  • Stefano Cataudella
    • 1
  • Marco Corti
    • 2
  1. 1.Stazione di Acquacoltura ed Ecologia SperimentaleII Università di Roma ‘Tor Vergata’RomeItaly
  2. 2.Dipartimento di Biologia Animale e dell’UomoUniversità di Roma ‘La Sapienza’RomeItaly

Personalised recommendations