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

[Salvador SANCHEZ COLON]

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!

[[alternative HTML version deleted]]

_______________________________________________
R-sig-ecology mailing list
R-sig-ecology using r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
.
 
	[[alternative HTML version deleted]]