Dear colleagues,
I and a graduate student (Fabiana Schneck) are using the adonis() function in vegan to test for the effect of two treatments (homogenous and heterogenous substrate) on diatom species composition. Data resulted from a experiment carried out in 11 stream reaches. Data were obtained in six visits after colonization ceased and we opted to use the 66 combination of reaches and time as block (strata in the argument list of the function). We were able to run the function using the default 'bray' method. However, we get negative F-values when using a dissimilarity matrix obtained from simpson formulae. This is our code and result:
bio.quali<-ifelse(bio>0, 1, 0)bio.quali.simp<-betadiver(bio.quali, "sim")adonis(bio.quali.simp~trat, strata=bloco, permutations = 9999)

Call:
adonis(formula
= bio.quali.simp ~ trat, permutations = 9999,      strata = bloco) 

                               Df       SumsOfSqs    MeanSqs   F.Model   R2     Pr(>F)
trat         1.000000  -0.587663  -0.587663  -8.821903 -0.0728      1
Residuals  130.000000  8.659838  0.066614  1.0728       

Total      131.000000  8.072174  1.0000     




The reasoning to use the simpson dissimilarity was to assess whether differences among treatments observed with Sorensen (Bray-Curtis for p/a data) was due to differences in species richness (the simpson index is supposed to measure turnover and be robust to differences in species richness: Lennon et al. 2001: J.An.ECol 70:966-79).
It is hard to imagine a negative F-value in a traditional univariate analysis, but I am not sure whether this is possible in adonis(). 
Adriano Sanches Melo

Departamento de Ecologia - ICB

Universidade Federal de GoiásBrazil


      
	[[alternative HTML version deleted]]

