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11 - Visualising multivariate data

Published online by Cambridge University Press:  05 May 2014

Petr Šmilauer
Affiliation:
University of South Bohemia, Czech Republic
Jan Lepš
Affiliation:
University of South Bohemia, Czech Republic
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Summary

The primary device for presenting the results of an ordination model is the ordination diagram. The contents of an ordination diagram can be used to approximate the response data table, the matrix of distances between individual cases, or the matrix of correlations or dissimilarities between individual response variables. In ordination including predictor variables (either explanatory or supplementary variables), we can use the ordination diagram to approximate, among others, the relationship between the response and the predictor variables. The first two sections in this chapter summarise what we can deduce from ordination diagrams that result from linear and unimodal ordination methods.

Before we discuss the rules for interpreting ordination diagrams, we must stress that the absolute values of scores (i.e. coordinates of objects, such as cases, response and predictor variables) in ordination space do not have, in general, any meaning. When interpreting ordination diagrams, we use relative distances of symbols, relative directions of arrows, or relative ordering of projection points. A detailed description of an ordination diagram created in Canoco 5 can be obtained by the Graph | Describe contents menu command or using the ‘lifebuoy’ button in the toolbar.

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Publisher: Cambridge University Press
Print publication year: 2014

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  • Visualising multivariate data
  • Petr Šmilauer, University of South Bohemia, Czech Republic, Jan Lepš, University of South Bohemia, Czech Republic
  • Book: Multivariate Analysis of Ecological Data using CANOCO 5
  • Online publication: 05 May 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9781139627061.012
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  • Visualising multivariate data
  • Petr Šmilauer, University of South Bohemia, Czech Republic, Jan Lepš, University of South Bohemia, Czech Republic
  • Book: Multivariate Analysis of Ecological Data using CANOCO 5
  • Online publication: 05 May 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9781139627061.012
Available formats
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Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Visualising multivariate data
  • Petr Šmilauer, University of South Bohemia, Czech Republic, Jan Lepš, University of South Bohemia, Czech Republic
  • Book: Multivariate Analysis of Ecological Data using CANOCO 5
  • Online publication: 05 May 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9781139627061.012
Available formats
×