[R-sig-eco] troubles with global test of rda from vegan

[claire della vedova]

Hi everybody,

I’m in troubles with results I obtained using rda function of vegan package
and I would greatly appreciate some help.
I did a rda to assess if my  matrix of species abundances (18 sites and 34
species)  can be explained by my  environmental matrix (18 sites and 5
variables). Abundances were transformed according hellinger equation
First I did a rda with all my environmental variables, and then did the
overall test. It was no significant.

myrda1<-rda(decostand(abund, "hellinger")~.,VarEnv)
anova(myrda1)
Permutation test for rda under reduced model

Model: rda(formula = decostand(abund, "hellinger") ~ VAR1 + VAR2 + Var3 +
Var4 + VAR5, data = VarEnv)
         Df      Var     F N.Perm Pr(>F)
Model     5 0.062863 1.025     99   0.43
Residual 12 0.147195         

 I also did the test by margin (all pvalues were no significant), and by
axis (first axis significant)
anova(myrda1, by="axis")

Model: rda(formula = decostand(abund, "hellinger") ~ VAR1 + VAR2 + Var3 +     
Var4 + VAR5, data = VarEnv)
         Df      Var      F N.Perm Pr(>F)   
RDA1      1 0.030016 2.4470    199   0.01 **
RDA2      1 0.013816 1.1263     99   0.29   
RDA3      1 0.009770 0.7965     99   0.68   
RDA4      1 0.006273 0.5114     99   0.84   
RDA5      1 0.002989 0.2437     99   1.00   
Residual 12 0.147195                        

On the plot, first axis is explained by Var1 and Var4


Since I was surprised by the results of the global test I tried a forward
selection. Only the Var4 was kept is the final model, and the test was now
significant. I also did backward selection ;  it was the Var1 which was kept
is the final model, and the test was significant too.

So my question is, why the global test of the rda with all the environmental
variables is not significant while the test by “axis” is significant for the
first one (explain by variables Var1 and Var4) and while model selection
lead to significant test for Var1 or Var4 ?

I analyzed the VIF of the full model, and all were lower than 3
vif.cca(myrda1)
     VAR1       VAR2     Var3       Var4      VAR5 
2.573506 2.949139 2.209569 2.023914 1.854133

Thanks in advance for your help.

All the best.
Claire Della Vedova




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