Congruence Between Morphological and Allozyme Data in Evolutionary Inference and Character Evolution

Mickevich, M. F., and M. S. Johnson (Centre de Recherches Mathematiques, Universite de Montreal, Montreal, P.Q., Canada and Department of Ecology and Evolution, State University of New York, Stony Brook, N. Y. 11794) 1976. Congruence between morphological and allozyme data in evolutionary inference and character evolution. Syst. Zool. 25:260–270.—In view of the growing concern that evolutionary information obtained from morphological data may differ in content from evolutionary information from molecular data, we have asked whether morphological data yield phyletic interpretations consistent with those inferred from allozymes. Minimum length Wagner trees were calculated from sets of morphometric and allozyme data on sixteen populations representing five nominal species of Menidia (Teleostei, Atherinidae). The two sets of characters yield nearly perfectly congruent evolutionary trees, despite the fact that phenetic analyses reveal very great disparity between the similarity structures of the morphometrics and the allozymes. A quantitative method for estimating convergence and parallelism was developed and revealed no significant differences in the proportions of these types of homoplasy for the two data sets. This cladistical method for estimating convergence is contrasted with partially phenetic methods used in the past; the later are shown to be incorrect. Mosaic evolution between morphometrics and allozymes is demonstrated statistically, and shown to result from heterogeneous rates of apomorphy, rather than from a preponderance of plesiomorphy in one data set. This mosaicism is the probable source of the large phenetic disparity. We conclude that 1) cladistical, rather than phenetic, methods are required for the analysis of character evolution, and 2) that the ease of obtaining sufficient information, rather than presumed inherent differences between characters, should determine which characters are used for evolutionary taxonomic inference.