Hello everybody!
I didn't imagine that my questions will lead to such a debate among researchers
:) . It helps me to get ready for future reviewers' comments. ;)
Just a question still opened about NMDS (Gavin?):
Is it important to reach a convergent solution? since the best solution
ordinate
Hi everbody
I'm working on my bachelor thesis on clearance rate for mussel and need some
help R. First have a look at the DF
TimeCRobs
150 4.6589
300 3.9685
450 4.0124
.. ...
216000 1.0281
These
How about something like this?
jonas - data.frame(time = seq(100, 216000, by = 150), crobs = rnorm(1440))
head(jonas)
jonas$halfhour - cut(jonas$time, breaks = seq(from = 0, to = 216000, by =
1800))
head(jonas)
tapply(jonas$crobs, INDEX = list(jonas$halfhour), FUN = mean)
# or
aggregate(crobs ~
I would say that it *is* important, in general. However, you don't say
if you retried running `monoMDS` on the Hellinger transformed data
(without the Bray-Curtis metric - you should use Euclidean with
Hellinger transformation)? If you didn't try rerunning with out
Bray-Curtis and see if it
Hi Mitchell;
If I understood what you want, it should work:
beta - betadisper(vegdist(matrix), type=centroid)
beta$distances
This will give you the raw values and then you can move with your analyses.
But check the new paper by Baselga 2013 Ecography before using
dissimilarity. He has
The distance to centroid for a site isn't a measure of that site's alpha
diversity. It is a reflection (an approximation) of the compositional
similarity of the sample to the other samples; distances between sites
reflect compositional dissimilarity.
The value you want are in the `$distances`
Excellent, thank you. I'm working with soil bacterial communities which have
incredibly high diversity so insufficient sampling is often behind what
initially looks like an interesting pattern. If the increased dispersion in
certain groups is related to some underlying ecology (such as
I also suggest (like I have suggested before) that you run metaMDS with
argument plot = TRUE. The convergence criteria in metaMDS are pretty stringent,
but with plot argument you can see how different the solutions are. Two most
typical non-convergence cases are that
(1) most points are
