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Application of size-free canonical discriminant analysis to studies of geographic differentiation

 

 

Sérgio F. dos ReisI; Leila M. PessôaII; Richard E. StrausIII

IDepartamento de Parasitologia, Instituto de Biologia, Universidade Estadual de Campinas, Caixa Postal 6109, 13081 Campinas, SP, Brasil. Send correspondence to S.F.R.
IIDepartamento de Zoologia, Centro de Ciências da Saúde, Universidade Federal do Rio de Janeiro, 21941 Rio de Janeiro, RJ, Brasil
IIIDepartament of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, USA

 

 


ABSTRACT

Canonical discriminant analysis (CDA) is a multivariate procedure employed in the study of geographic variation, species differentiation, and macroevolution. However, the application of CDA to study organisms where character size-frequency distribution varies within samples due to sampling bias, may result in artifactual discrimination due to shifts in mean character values. In such cases it would be desirable to discriminate among samples that have been corrected for within-group size differences. In this note we illustrate the application of size-free canonical discriminant analysis. In this procedure the effect of size variation within groups is removed by regressing each character separately on the first pooled within-group principal component, which is an estimate of general size. The application of this procedure is illustrated by a study of geographic differentiation in the echimyid rodent Proechimys dimidiatus. A command file of SAS-PC procedures necessary for the implementation of size-free CDA is also provided.

Keywords: Size-free canonical discriminant; Geographic differentiation.


 

 

REFERENCES

Baker, A.J. (1980). Morphometric differentiation in New Zealand populations of the house sparrow (Passer domesticus). Evolution 34: 638-653.

Bookstein, F.L. (1982). Foundations of morphometrics. Ann. Rev. Ecol. Syst. 13: 451-470.

Bookstein, F.L., Chernoff, B., Elder, R., Humphries, J., Smith, G. and Strauss, RE. (1985). Morphometrics in Evolutionary Biology. Special Publication 15. The Academy of Natural Sciences of Philadelphia,Penn.

Bulmer, M.G. (1980). The Mathematical Theory of Quantitative Genetics. Clarendon Press, London.

Campbell, N.A. and Atchley, W.R. (1981). The geometry of canonical variate analysis. Syst. Zool. 30: 268280.

Chatfield, C. and Collins, AJ. (1980). Introduction to Multivariate Analysis. Chapman and Hall, London. Chesser, R.K. (1983). Cranial variation among populations of the black-tailed prairie dog in New Mexico. Occas. Papers Mus., Texas Tech Univ. 49: 1-25.

Falconer, D.S. (1989). Introduction to Quantitative Genetics. 3rd. ed. Oliver and Boyd, Edinburgh.

Humphries, J., Bookstein, F.L., Chernoff, B., Smith, G., Elder, R. and Poss, S. (1981). Multivariate discrimination by shape in relation to size. Syst. Zool. 30: 291-308.

Lessa, H.P. and Patton, J.L. (1989). Structural constraints, recurrent shapes, and allometry in pocket gophers (genus Thomomys). Biol. J. Linnean Soc. 36: 349-363.

Lindgren, B.W. (1976). Statistical Theory. 3rd. ed. MacMillan, N.Y.

Moojen, J. (1948). Speciation in the Brazilian spiny rats (Genus Proechimys, Family Echimyidae). Univ. Kans. Publ., Mus. Nat. Hist. 1: 301-406.

Moojen, J. (1952). Roedores do Brasil. Instituto Nacional do Livro, Rio de Janeiro.

Morrison, D.F. (1976). Multivariate Statistical Methods. McGraw Hill, New York.

Neff, N.A. and Marcus, L.F. (1980). A Survey of Multivariate Methods for Systematics. Privately Published, New York.

Patton, J.L. (1985). Population structure and the genetics of speciation in pocket gophers, genus Thomomys. Acta Zool. Fenn. 170: 109-114.

Patton, J.L. and Rogers, M.A. (1983). Systematic implications of non-geographic variation in the spiny rats genus proechimys (Echimyidae). Z. Saeugetierkunde 48: 363-370.

Patton, J.L. and Smith, M.F. (1989). Population structure and the genetic and morphologic divergence among pocket gopher species (genus Thomomys). In: Speciation and its Consequences (Otte, D. and Endler, J.A., eds.). Sinauer, Sunderland, pp. 215-235.

Pimentel, R.A. (1979). Morphometrics. Kendall/Hunt, Dubuque.

Rohlf, F.J. and Bookstein, F.L. (1987). A comment on shearing as a method of "size correction". Syst. Zool. 36: 356-367.

SAS Institute Inc. (1988). SAS/STAT User's Guide, Release 6.03 Edition. Cary, NC.

Searle, S.R. (1971). Linear Models. Wiley, N.Y.

Schmidly, D.J., Bradley, R.D. and Cato, P.S. (1988). Morphometric differentiation and taxonomy of three chromosomally characterized groups of Peromyscus boylii from East-Central Mexico. J. Mar-rim. 69: 462-480.

Smith, M.F. and Patton, J.L. (1988). Subspecies of pocket gophers: Causal basis for geographic differentiation in Thomomys bottae. Syst. Zool. 37: 163-178.

Sokal, R.R. e Rohlf, F.J. (1981). Biometry. 2nd. ed. Freeman, San Francisco.

Straney, D.O. (1978). Variance partitioning and nongeographic variation. J. Mamm. 59: 1-11.

Strauss, R.E. (1985). Static allometry and variation in body form in the South American catfish genus Corydoras (Callichthyidae). Syst. Zool. 34: 381-396.

Thorpe, R.S. (1983). A review of the numerical methods for recognizing and analysing racial differentiation. In: Numerical Taxonomy (Felsenstein, J., ed.). Springer Verlag, Berlin, pp. 404-423.

Thorpe, R.S. (1987). Geographic variation: a synthesis of cause, data, pattern and congruence in relation to subspecies, multivariate analysis and phylogenesis. Boll. Zool. 54: 3-11.

Van Vleck, L.D. and Searle, S.R. (1979). Variance Components and Animal Breeding. Cornell University, N.Y.

Winer, B.J. (1971). Principles in Experimental Design. 2nd. ed. McGraw-Hill, N.Y.

Wright, S. (1954). The interpretation of multivariate systems. In: Statistics and Mathematics in Biology (Kempthorne, O., Bancroft, T.A., Gowen, J.W. and Lush, J.L., eds.). Iowa State College Press, Ames, pp. 11-33.