Tim, I've used mvpart to cluster, and then rpart.pca the resulting regression clustering.
mvpart requires a corresponding environmental data set.
The pca plot has what you require, polygons like ordihull based on and showing plots (rows in your data), and vectors to named species. I have assumed that the distance from the centroid to each species corresponds to its importance in configuring the output, but I'm a novice andwould like more information on that.
Mike Marsh

On 9/26/2015 3:00 AM, r-sig-ecology-requ...@r-project.org wrote:
  get species within sites ordihull polys

Date: Fri, 25 Sep 2015 18:58:19 +0000
From: "Howard, Tim G (DEC)"<tim.how...@dec.ny.gov>
To:"r-sig-ecology@r-project.org"  <r-sig-ecology@r-project.org>
Subject: [R-sig-eco] get species within sites ordihull polys
Message-ID:
        
<cy1pr09mb0266dbf8a724047334e58d6ca8...@cy1pr09mb0266.namprd09.prod.outlook.com>
        
Content-Type: text/plain; charset="us-ascii"

All -
Consider clusters of points in an NMDS with those clusters determined in some 
way (I'll use hclust below).

Then consider plotting the species on that ordination.  I'd like to 
automatically find which species are 'most associated' with each cluster. 
Perhaps that translates to finding those species that fall within an ordihull 
of each group.  Before I stumble down into the world of the sp package and 
spatial overlaps perhaps this is already a part of vegan or another package.

###Example:

library(vegan)
data(dune)
ord <- metaMDS(dune)
# get some groups based on hclust
dis <- vegdist(dune)
clus <- hclust(dis, "average")
plot(clus)
rect.hclust(clus, 3)
grp <- cutree(clus, 3)
#plot the mds with the groups
mdsPlot <- plot(ord, type="n", display = "sites")
points(ord, display = "sites", col="red", pch=19)
ordihull(ord, grp)
#plot the species
points(ord, display = "species", col = "blue", pch=19)

###End example

This isn't the best example because species points don't fall in more than one 
of the black polygons. But, my question: Can I easily identify which blue 
points (species) fall within the polygon?   Or can I easily identify which 
species are 'most important' (most abundant?) for defining each of the three 
groups?

Thanks for any pointers

Tim Howard

_______________________________________________
R-sig-ecology mailing list
R-sig-ecology@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-ecology

Reply via email to