betadisper() and variation in community change
betadisper() will give you a test of homogeneity of variance between groups; in other words it tests the null that the variance of the groups of sites does not change. adonis() is a test of location, which will test the null of no compositional change between groups of sites. Here I assume by groups of sites, "groups" is defined by the time points of sampling? It is somewhat unclear what you mean by "variation in plant community change over time among sites". Do you want to know if on average the composition of your groups of sites is changing through time? Or do you want to know something about change over time in that compositional change. The former could be done by adonis() the latter could be seen as an analysis of the first derivative of the change given by adonis() and I don't think we have anything for that easily to hand in vegan or R. Perhaps you could describe more clearly what it is that you hope to show/demonstrate? I have some rough code implementing an idea of Jari's (and a colleague of his) for a better way of quantifying rates of composition change and total amount of composition change: Rate of compositional turnover along gradients and total gradient length. Journal of Vegetation Science 6, 815-824. JO & Tonteri, T. But you would have to do that for each site individually and then perform some other test if you want to group data. The code is far from production - it was a proof of concept using smooth.spline() which doesn't really model the mean-variance relationship of abundance or compositional data properly, but it had analytical derivatives via the predict() method so it got used out of convenience rather than fitting via mgcv:::gam() and having to derive derivatives via finite differences (which is easy but tedious). HTH G
On Wed, 2012-10-17 at 15:48 +0200, Gustaf Granath wrote:
Dear all,
I want to compare variation in plant community change over time among
sites. The focus is quantify the species community change over time and
not so much to test if the community has changed significantly. The
sites do not share many species but I hope to investigate their
variation over time.
I am a bit unsure if my approach using betadisper() is correct and maybe
there are better ways to do this. Any input is appreciated.
For simplicity, say that we have 2 site with 4 and 2 subplots,
respectively. These plots were measured with e.g. 5 years intervals.
The aim is to compare variation of plant community change over time
between the two sites. Note that this is at the site level, not at the
sub plot level.
library(vegan)
## Lets use the grazed/ungrazed example but here I treat it as
## 4 subplots (grazed) and 2 subplots (ungrazed). These
## subplots were sampled 4 times.
data(varespec)
dis <- vegdist(varespec)
sites <- factor(c(rep(1,16), rep(2,8)), labels = c("grazed","ungrazed"))
time<-c(rep(1:4,each=4),rep(1:4,each=2))
sites_time<-factor(paste(sites,time,sep="_"))
## Calculate multivariate dispersions for each
## site:time combination
mod1 <- betadisper(dis, sites_time)
#extract centroid positions for each site:time combination
cen.si<-scores(mod1, display = c("centroid"), choices = c(1,2))
# Calculate distance matrix
time.dist<-vegdist(cen.si,method="euclidean")
sites_main <- factor(c(rep(1,4), rep(2,4)), labels = c("grazed","ungrazed"))
# Run betadisper() on the site:time positions
mod2 <- betadisper(time.dist,sites_main)
#compare the two sites
boxplot(mod2)
#use 3 PCoA axis to get the 3D movement of the plant community
cen.si<-scores(mod1, display = c("centroid"), choices = c(1,2,3))
time.dist<-vegdist(cen.si,method="euclidean")
sites_main <- factor(c(rep(1,4), rep(2,4)), labels = c("grazed","ungrazed"))
mod3 <- betadisper(time.dist,sites_main)
boxplot(mod3)
Cheers,
Gustaf
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