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[ Article ] On The Empirical Performance Of Non- Metric Multidimensional Scaling In Vegetation Studies.

Date de soumission: 23-09-2016
Année de Publication: 2013
Entité/Laboratoire Laboratoire de Biomathématiques et d'Estimations Forestières (LABEF)
Document type : Article
Discipline(s) : Sciences Environnement &Ecologie
Titre On The Empirical Performance Of Non- Metric Multidimensional Scaling In Vegetation Studies.
Auteurs
Journal: International journal of applied mathematics and statistics
Catégorie Journal: Internationale
Impact factor: 0
Volume Journal: 36
DOI:
Resume 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).
Mots clés Non-metric multidimensional scaling, efficiency, vegetation studies.
Pages 54 - 67
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