[R-sig-eco] clustering communities by an environmental variable

[Pierre Thiriet]

Hi
You might have a look to multivariate regression tree, formerly mvpart packagé
Cheers

Le 24 avr. 2020 à 18:30, à 18:30, Salvador SANCHEZ COLON <salvadorsanchezcolon using prodigy.net.mx> a écrit:
>Hi Irene,
>
>
>The approach that you are using -i.e., calculating the between-sample
>dissimilarity with the Bray-Curtis distance, followed by the UPGMA
>clustering technique- will group your samples based on the values of
>all the variables contained in your data matrix (which, in ecological
>studies, usually are species abundance or presence/absence data). 
>
>
>I hope this helps but feel free to ask further details. 
>
>
>Salvador SÁNCHEZ-COLÓN
>Independent consultant
>
>
>En Vie, 24 Abril, 2020 en 10:49, Irene Adamo <i.adamo90 using gmail.com>
>escribió:
> 
>
>Para: r-sig-ecology using r-project.org
>Dear all,
>I am trying to do a dendrogram by trying to see if my communities by
>altitude but I am not sure on how to do it.
>lets say I have this example
>
># calculate Bray-Curtis distance among samples comm.bc.dist <-
>vegdist(comm,
>method = "bray") # cluster communities using average-linkage algorithm
>comm.bc.clust <- hclust(comm.bc.dist, method = "average") # plot
>cluster
>diagram plot(comm.bc.clust, ylab = "Bray-Curtis dissimilarity")
>
>Now, I would like to cluster my communities by Altitude always using
>the
>distance matrix and the dendrogram.
>Is it possible?
>
>Thanks a lot for any help!
>
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>
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