Numerical taxonomy, cluster analysis, common principal component model, Mahalanobis distance. Gölz and Reinhard distance, Orchidaceae
Abstract :
[en] Four distance coefficients are compared on four data sets composed of samples coming from western European populations of the genera Dactylorhiza, Orchis and Epipactis (Orchidaceae). The performance of the distance coefficients is evaluated through: (a) the quality of clusters obtained by five classical methods (as compared to a priori classification), (b) the Mantel statistic with respect to an a priori distance matrix resulting from previous knowledge, (c) the result obtained with the k-means method, and (d) principal coordinate diagrams. It appears that: (a) the Mahalanobis distance based on the pooled dispersion matrix performs best on the whole; (b) a distance based on the recently developed Common Principal Component model, used with a log transformation, also provides useful information and performs best on the largest data set; (c) the Gölz and Reinhard taxonomic distance, widely used among orchidologists, is attractive for its simplicity, yet good performance and the valuable information it provides, despite its theoretical shortcomings. A brief taxonomic discussion is made on the results obtained for the Dactylorhiza samples, especially about samples whose identification was in doubt.
Disciplines :
Environmental sciences & ecology
Author, co-author :
Tyteca, D.; Institut d'Administration et de Gestion, Université Catholique de Louvain, Unité d'Écologie et de Biogégraphie, Place des Doyens 1, Place Croix Sud 4 -5, B-1348 Louvain-la-Neuve, Belgium
Dufrêne, Marc ; Université de Liège - ULiège > Forêts, Nature et Paysage > Biodiversité et Paysage
Language :
English
Title :
On the Use of Distance in the Taxonomic Study of Critical Plant Groups-Case Studies of Western European Orchidaceae
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