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Community Ecology

, Volume 18, Issue 3, pp 260–279 | Cite as

Recoding and multidimensional analyses of vegetation data: a comparison

  • S. CamizEmail author
  • P. Torres
  • V. D. Pillar
Article

Abstract

Two simulated coenoclines and a real data set were differently recoded with respect to the Braun-Blanquet coding (including presence/absence) and analysed through the most common multidimensional scaling methods. This way, we aim at contributing to the debate concerning the nature of the Braun-Blanquet coding and the consequent multidimensional scaling methods to be used. Procrustes, Pearson, and Spearman correlation matrices were computed to compare the resulting sets of coordinates and synthesized through their Principal Component Analyses (PCA). In general, both Procrustes and Pearson correlations showed high coherence of the obtained results, whereas Spearman correlation values were much lower. This proves that the main sources of variation are similarly identified by most of used methods/transformations, whereas less agreement results on the continuous variations along the detected gradients. The conclusion is that Correspondence Analysis on presence/absence data seems the most appropriate method to use. Indeed, presence/absence data are not affected by species cover estimation error and Simple Correspondence Analysis performs really well with this coding. As alternative, Multiple Correlation Analysis provides interesting information on the species distribution while showing a pattern of relevés very similar to that issued by PCA.

Keywords

Braun-Blanquet coding Comparisons Correspondence Analysis Non-metric Multidimensional Scaling Principal Component Analysis Recoding 

Abbreviations

BBc

Braun-Blanquet coding

CA

Correspondence Analysis

DCA

Detrended Correspondence Analysis

GPA

Generalized Procrustes Analysis

MCA

Multiple Correlation Analysis

MDS

nonmetric MultiDimensional Scaling

PCA

Principal Component Analysis

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Notes

Acknowledgements

For this work, Camiz and Pillar were supported by the Sapienza Università di Roma and Universidade Federal do Rio Grande do Sul grants for bilateral relations. Camiz was also granted by Sapienza’s agreement with Argentina and by the Special Visiting Researcher Fellowship of Brazilian CNPq, under the Brazilian Scientific Mobility Program “Ciências sem Fronteiras”, Process #: 314443/2014-2.

Supplementary material

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Recoding and multidimensional analyses of vegetation data: a comparison

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© Akadémiai Kiadó, Budapest 2017

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Dipartimento di MatematicaSapienza Università di RomaRomaItaly
  2. 2.Facultad de Ciencias AgrariasUniversidad de RosarioRosarioArgentina
  3. 3.Departamento de EcologiaUniversidade Nacional do Rio Grande do SulPorto AlegreBrazil

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