Faculty of Agronomic sciences, University of Abomey-Calavi, 01 BP 526, Cotonou, Benin; Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Salako, V.K., Faculty of Agronomic sciences, University of Abomey-Calavi, 01 BP 526, Cotonou, Benin; Adebanji, A., Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana; Glèlè Kakaï, R., Faculty of Agronomic sciences, University of Abomey-Calavi, 01 BP 526, Cotonou, Benin
Non-metric multidimensional scaling (NMDS) is widely used as a routine method for ordination in vegetation studies. Its use in statistical softwares often requires the choice of several options on which the accuracy of results will depend. This study focuses on the combined effect of sample size, similarity/dissimilarity indexes, data standardization and structure of data matrix (abundance and binary) on NMDS efficiency based on real data from the Lama Forest Reserve in Southern-Bénin. The Spearman's Rank Correlation coefficient and the s-stress were used as an assessment criterion. All the four factors were found to influence the efficiency of the NMDS and the samples (plots) standardization to equal totals gave the best results among standardization procedures considered. The Jaccard and Sorensen similarity/dissimilarity indexes performed equally whatever the nature of the matrix. However, with binary matrices, Sokal and Michener similarity index performed better. A quadratic relationship was noted between s-stress and sample size. A lower optimal sample size (75 plots) was observed for the binary matrices than for the abundance ones (90 plots). © 2013 by CESER Publications.
Assessment criteria; Binary matrix; Combined effect; Data matrices; Data standardization; Empirical performance; Forest reserves; Non-metric multidimensional scaling; Optimal samples; Routine method; Sample sizes; Similarity indices; Spearman's rank correlation coefficients; Statistical software; Efficiency; Nickel compounds; Standardization; Vegetation
