Hi Bjorn,

A common practice in simplifying ordinatin plots is to keep species that show the best fit into the ordination space. The position of such species in the ordination diagram really (may) tell something. In linear methods like PCA a linear fit is suitable. This can be computed using vegan::envfit function.

For this I have a very simple function reduce.pca, which you can source using this line of code:

The code and example may be viewed here (skip the Czech introduction):

Your criterion on species selection is more complicated. You can change the function accordingly. I am not completely sure but a solution might be multiplying species fit by species variance, then ordering species acoording to this fit*variance and add species until the desired variance is achieved.
I might be wrong, anybody feel free to correct me, please.


Dne 2016-10-12 12:44, Bjorn napsal:
Hi all,

there might be a simple solution to do this, but I don't seem to
manage to find it. I have done a PCA using vegan. I now want to create
a biplot with only those species that explain a certain (cumulative)
amount of the variation along the first 2 PC axes (in order to keep
things clear). How could this be done?

Thanks in advance!

Kind regards,


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