# Analysis of community ecology data in R

David Zelený

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en:tbpca_examples

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 en:tbpca_examples [2018/03/28 23:21]David Zelený en:tbpca_examples [2018/03/30 23:04] Line 1: Line 1: - ====== Unconstrained ordination ====== - ===== Transformation-based principal component analysis (tb-PCA) ===== - - [[{|width: 7em; background-color: white; color: navy}tbpca|Theory]] - [[{|width: 7em; background-color: white; color: navy}tbpca_R|R functions]] - [[{|width: 7em; background-color: light; color: firebrick}tbpca_examples|**Examples**]] - [[{|width: 7em; background-color: white; color: navy}tbpca_exercise|Exercise {{::lock-icon.png?nolink|}}]] - - - ==== Example 1: PCA on species data transformed using Hellinger transformation ==== - In this example we will use vegetation data from [[en:data:vltava|Vltava river valley dataset]], and we will analyse them by PCA after pre-transformation by Hellinger transformation. - - - vltava.spe <- read.delim ('http://www.davidzeleny.net/anadat-r/data-download/vltava-spe.txt', row.names = 1) - vltava.spe.hel <- decostand (log1p (vltava.spe), 'hellinger') # the species data (percentage scale) are first log transformed, and then transformed using Hellinger transformation - - PCA <- rda (vltava.spe.hel) - - source ('http://www.davidzeleny.net/anadat-r/doku.php/en:numecolr:cleanplot.pca?do=export_code&codeblock=0') # define the cleanplot.pca function - cleanplot.pca (PCA) - - - {{:obrazky:ordination_unc18.png?900&direct|}} - - These ordination diagrams do not look too helpful (you need to click to enlarge them to see more details) - but we will see [[en:indirect_ordination_viz|later]] how to visualize the results of ordination more effectively. -