Hennig's Parasitological Method: A Proposed SolutionBrooks, Daniel R.
doi: 10.1093/sysbio/30.3.229pmid: N/A
AbstractHennig's parasitological method: a proposed solution. Syst. Zool., 30:229–249.—A quantitative solution for Hennig's parasitological method is presented. Cladograms summarizing natural relationships among parasite taxa are converted into host-group characters by means of additive binary coding. Unrooted Wagner analysis followed by most parsimonious rooting produces a maximum information-content representation of natural host-parasite relationships. Because host-parasite relationships result either from random colonization or from co-speciation, host relationships well corroborated by a multi-parasite analysis correspond to host phylogeny. Poorly corroborated host relationships indicate an ambiguous parasite message alerting a worker to possible host transfers. Thus, such analyses point out co-speciation and random colonization components of host-parasite systems. Single or multiple parasite taxa may be used. A host phylogeny based on non-parasite characters is neither necessary nor sufficient for studying phylogenetic aspects of coevolution, although such may be helpful in testing ambiguous aspects. Once a host-group cladogram based on parasites has been established, phylogenetic interpretations for each observed host-parasite relationship may be made according to a listed set of necessary and sufficient criteria. Finally, evaluation of two models of coevolution, a “vicariance” model and the “resource-tracking” model, indicates that the latter cannot be extrapolated successfully to explain congruent phylogenetic differentiation of hosts and parasites and that the former model represents the general pattern of natural relationships among hosts and parasites.
A Comparative Study of Data and Ordination Techniques Based on a Hybrid Swarm of Sand Verbenas (Abronia Juss.)Pimentel, Richard A.
doi: 10.1093/sysbio/30.3.250pmid: N/A
AbstractA comparative study of data and ordination techniques based on a hybrid swarm of sand verbenas (Abronia Juss.). Syst. Zool., 30:250–267.—The influence of kinds of variables, data errors, standardizations similarity coefficients, and ordination techniques are judged in reference to a model involving hybridization and introgression in three species of sand verbenas, Abronia (Juss.). Various criteria indicate that principal component analysis performs best, but inaccurately, with variable standardization and the correlation matrix, and that nonlinear mapping consistently performs poorly. Excellent results were obtained from principal coordinate analysis with Gower's general similarity coefficient based upon quantitative and multistate variables; a ‘diagnostic’ character measured with known error; and detailed color evaluation. This and other principal coordinate analysis results were further improved by nonmetric multidimensional scaling. Performance of methods is consistent with the nonlinearity of Abronia data. It is assumed that nonlinearity is common in taxonomic data.
The Geometry of Canonical Variate AnalysisCampbell, N. A.; Atchley, William R.
doi: 10.1093/sysbio/30.3.268pmid: N/A
AbstractThe geometry of canonical variate analysis. Syst. Zool., 30:268–280.—The geometry of canonical variate analysis is described as a two-stage orthogonal rotation. The first stage involves a principal component analysis of the original variables. The second stage involves a principal component analysis of the group means for the orthononnal variables from the first-stage eigenanalysis. The geometry of principal component analysis is also outlined. Algebraic aspects of canonical variate analysis are discussed and these are related to the geometrical description. Some practical implications of the geometrical approach for stability of the canonical vectors and variable selection are presented.
Congruence among Character Sets in Phylogenetic Studies of the Frog Genus LeptodactylusMiyamoto, Michael M.
doi: 10.1093/sysbio/30.3.281pmid: N/A
AbstractCongruence among character sets in phylogenetic studies of the frog genus Leptodactylus. Syst. Zool., 30:281–290.—Four species groups of the neotropical frog genus Leptodactylus are currently recognized on the bases of morphological and life history characteristics. The fuscus and pentadactylus groups are related as a monophyletic cluster, whereas the phylogenetic relationships of the melanonotus and ocellatus groups remain unknown. Five species representing all four species groups occur in Costa Rica. This study examined protein variability among four Costa Rican species as ascertained by electrophoretic and histochemical techniques. The presumptive genetic data were analyzed cladistically with the Wagner method. This procedure constructed a cladogram for the Costa Rican species which was congruent with the phylogenetic relationships proposed for their species groups from morphological and life history characteristics. This congruence among phylogenetic inferences based on different character sets argues for the continued recognition of species group relationships as currently viewed within the genus.
Multivariate Discrimination by Shape in Relation to SizeHumphries, J. M.; Bookstein, F. L.; Chernoff, B.; Smith, G. R.; Elder, R. L.; Poss, S. G.
doi: 10.1093/sysbio/30.3.291pmid: N/A
AbstractMultivariate discrimination by shape in relation to size. Syst. Zool., 30:291–308.—The diverse methods for analyzing size-free shape differences tend to be guided by computational expediency rather than geometric principles. We question the use of ratios and ad hoc combinations of spatially unrelated measures. Neither are linear discriminant functions or series of independent regressions helpful to the visualization of shape differences. A bridge is needed between traditional quantitative methods and thegeometrical analysis of shape.In principle any measured transects between landmarks of a form can serve as characters in a morphometric analysis. Systematic studies use a highly non-random sample of these, particularly biased regarding geometrical information. We suggest defining size and shape in terms of factors—estimates of information common to a universe of measured distances.The model presented here calculates a linear combination of variables that quantifies shape differences among populations, independent of size. In analyses in which the first two principal components confound size and shape, size is removed from one axis with shear coefficients derived from regression of general size on principal components centered by group. The general size factor is estimated by the principal axis of the within-group covariancematrix of the log-transformed data. Residuals from the regression of general size onthe transformed axes approximate a shape-discriminating factor that is uncorrelated with size within group and displays the interpopulation shape differences borne by the first two principal components. The results bear a direct and interpretable correspondence to biorthogonal analysis of shape difference.