ZELENÝ, David and Lubomír TICHÝ. Linking JUICE and R: New developments in visualization of unconstrained ordination analysis. In 18th Workshop of European Vegetation Survey in Rome. Roma: La Sapienza Univerzita, 2009, p. 123-123.
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Basic information
Original name Linking JUICE and R: New developments in visualization of unconstrained ordination analysis
Name in Czech Propojení JUICE a R: pokrok ve vývoji nových vizualizačních metod pro nepřímou ordinační analýzu
Authors ZELENÝ, David and Lubomír TICHÝ.
Edition Roma, 18th Workshop of European Vegetation Survey in Rome, p. 123-123, 1 pp. 2009.
Publisher La Sapienza Univerzita
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10600 1.6 Biological sciences
Country of publisher Italy
Confidentiality degree is not subject to a state or trade secret
Organization unit Faculty of Science
Keywords in English R; JUICE; unconstrained analysis
Tags JUICE, R, unconstrained analysis
Tags International impact
Changed by Changed by: Mgr. David Zelený, Ph.D., učo 195404. Changed: 13/7/2009 13:51.
Abstract
JUICE program offers user friendly environment for editing, classification and analysis of vegetation data. R-project has almost unlimited possibilities of analysis and visualization of any type of data, yet its interface is not designed for user without an advanced experience. Therefore, we decided to use the benefits of these programs, using JUICE interface and R-project engine, for advanced visualization of results of unconstrained ordination analysis, such as Detrended Correspondence Analysis (DCA), Principal Components Analysis (PCA) and Non-metric Multidimensional Scaling (NMDS). In R-project, wide selection of analytical and visualization tools for multivariate ordination analysis is available in the package vegan, developed by Jari Oksanen and his colleagues. We used this package, extended its functionality for several new visualization methods and connected it with JUICE program. Beside traditional two dimensional ordination diagrams with projected environmental variables and vegetation groups, the combination of JUICE and R program offers more advanced methods such as three dimensional interactive ordination diagrams with convex hulls or spiderplots. The function such as manual update, online discussion forum, online manual and export of ordination results are also provided. We believe that this method, particularly the three dimensional visualization of ordination results, may bring new possibilities for interpretation of ordination results and their quick and effective visualization.
Abstract (in Czech)
JUICE program offers user friendly environment for editing, classification and analysis of vegetation data. R-project has almost unlimited possibilities of analysis and visualization of any type of data, yet its interface is not designed for user without an advanced experience. Therefore, we decided to use the benefits of these programs, using JUICE interface and R-project engine, for advanced visualization of results of unconstrained ordination analysis, such as Detrended Correspondence Analysis (DCA), Principal Components Analysis (PCA) and Non-metric Multidimensional Scaling (NMDS). In R-project, wide selection of analytical and visualization tools for multivariate ordination analysis is available in the package vegan, developed by Jari Oksanen and his colleagues. We used this package, extended its functionality for several new visualization methods and connected it with JUICE program. Beside traditional two dimensional ordination diagrams with projected environmental variables and vegetation groups, the combination of JUICE and R program offers more advanced methods such as three dimensional interactive ordination diagrams with convex hulls or spiderplots. The function such as manual update, online discussion forum, online manual and export of ordination results are also provided. We believe that this method, particularly the three dimensional visualization of ordination results, may bring new possibilities for interpretation of ordination results and their quick and effective visualization.
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