Hello Cichini,

I cannot help with your code but seems like you have a silly hypothesis.
Think about it: Probability of two communities to be identical?
You need to restate it in some more useful way. We already know most things
are different but with what magnitude? Which factors are causing these
changes? How these changes matter from the environment and us?

2012/4/25 Chris Howden <chris@trickysolutions.com.au>

> Why not try some type of ANOVA style glm?
>
> Chris Howden
> Founding Partner
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> On 26/04/2012, at 7:19, Kay Cichini <kay.cichini@gmail.com> wrote:
>
> > Hello all,
> >
> > I'd like to test if total diversity differs between two communities. For
> > each community several samples were taken and abundances collapsed over
> > groups to compute total diversity for each group. I tried to use
> > vegan::oecosimu to test non-randomness of my statisitc (difference in
> > Simpson-Diversity indices of collapsed abundances) - however, I am not
> > quite sure if I oversee posssible pitfalls:
> >
> > library(vegan)
> > data(dune)
> >
> > # a grouping variable:
> > gr <- gl(2, nrow(dune)/2)
> >
> > divdiff <- function(x) abs(diversity(colSums(x[gr == "1", ]), "simp") -
> >                           diversity(colSums(x[gr == "2", ]), "simp"))
> > # testing function:
> > divdiff(dune)
> >
> > oecosimu(dune, divdiff, "r2dtable", nsimul = 1999)
> > # oecosimu with 1999 simulations
> > # simulation method r2dtable
> > # alternative hypothesis: true mean is not equal to the statistic
> > #           statistic        z     2.5%      50% 97.5% Pr(sim.)
> > # statistic   0.00275 -0.20996  0.00013  0.00280  0.01     0.98
> >
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