interpreting adonis results

Thanks all for your help on adonis???^_^
Thanks Kay too...;-)


So,I have moved on and currently working on betadisper and faced some 
problems.

1.In vegatutor.pdf, betadisper (pg 33), "The function can only use one 
factor as an independent variable, and it does not know the formula 
interface,..."

mod <- with(dune.env, betadisper(betad, Management))

Let's say I need to investigate the interaction of factors: Management and 
USE. My question is: Can i create a new factor from the interaction of 
factor Management and USE then use it in betadisper()? E.g.

groupA<-interaction(dune.env$Management,dune.env$Use)
mod <- with(dune.env, betadisper(betad, groupA))
mod

Error in optim(apply(X, 2, median, na.rm = TRUE), fn = medfun, gr = 
dmedfun, :
 non-finite value supplied by optim

For the dune dataset, the above error occured. But for my data, the 
interaction works. I wonder if i continue to use the new factor generated 
from the factor-interaction for the betadisper, will it affects the 
results? If this is wrong, what would be the recommended function to use?

Sincerely Yours,
J

On Nov 17 2011, Kay Cecil Cichini wrote:

..to be save I would consider to exclude an effect due to different  
multivariate spread. See chapter 5.2, Homogeneity of groups and beta  
diversity, in the vegan tutorial at  
http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf.

best,
kay


Zitat von Gavin Simpson <gavin.simpson at ucl.ac.uk>:

On Wed, 2011-11-16 at 03:43 +0100, Gian Maria Niccol? Benucci wrote:

Hi all,

I had 84 samples collected in 7 different sites. In each sample were 
individuated the different fungal species and recorded. I would test 
if exist a real difference between the sites and if exist a sort of 
site effect that structure the fungal communities... Then, I did 
adonis test

adonis(community.sq ~ location, data=env.table, permutations=999)

Call: adonis(formula = community.sq ~ location, data = env.table, 
permutations = 999)

          Df SumsOfSqs MeanSqs F.Model      R2 Pr(>F)
location   6    12.593 2.09886  6.8867 0.34922  0.001 ***
Residuals 77    23.467 0.30477         0.65078
Total     83    36.060                 1.00000
---
Signif. codes:  0 *** 0.001 ** 0.01 * 0.05 . 0.1   1



The significance is R2=0.349 at P=0.001 Can I assure that exist a 
strong site effect in structuring the communities in each site?

Depends. The test is one of no effect of `location`. You have found
evidence against this hypothesis and thus could reject this hypothesis,
instead accepting the alternative hypothesis that there is an effect of
`location`. As to the strength of this effect? ~35% of the sums of
squares can be explained by `location`. Substantially more of the
variance remains unexplained. As I know nothing about your subject area,
I am unable to comment further on the strength of the relationship.

Seeing as many ecologists whose work I read would say an effect is
significant if the p-value was >= 0.05. Not that I subscribe to this way
or working, but by that criterion, you have identified a significant
`location` effect.

HTH

G

Thanks for helping,

G.

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