interpreting adonis results

Gavin,

May I ask you if you have tutorial for the betadisper() function?

Maybe I did a mistake during the identification of the groups of samples...

The I tried to use the betadisper( ) function R gave me an error...
*******************************************************

groups <- factor(c(rep(1,12),rep(13,24),

rep(25,36),rep(37,48),rep(49,60),rep(61,72),rep(73,84),+
labels=c("SIG","BA","SIMa","SIMb","SZV","BM","BRE")))

betadiv <- betadisper(dist1, groups)

Error: (subscript) logical subscript too long

*******************************************************
I can't understand what is wrong...
Thank you help and patience,

tail(groups)

nlevels(groups)

levels(groups)

Gian







2011/11/17 Gavin Simpson <gavin.simpson at ucl.ac.uk>

On Thu, 2011-11-17 at 10:01 +0100, gabriel singer wrote:

... dangerous wording, there could in fact be a location effect of
'location' and/or a dispersion effect of 'location'.

Well of course, but I was assuming that the assumptions of the test were
met! ;-)

Gian, I suggest you add a test of a dispersion effect using the function
betadisper(), then you know a bit more about the type of effect.

Indeed, and as the author of that function I too would suggest that the
homogeneity assumption be tested.

G

gabriel

On 11/16/11 11:02 PM, Gavin Simpson wrote:

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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