troubles with global test of rda from vegan
claire della vedova p??e v So 22. 03. 2014 v 00:30 -0700:
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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Hi, it is not so easy to answer without the knowledge of data sampling, whole data itself or complete results, but I will try anyway.(My apologies if I would not use some terms correctly - I would be happy to see more proper explanation). I guess that the data do not come from the experiment that manipulated (somehow) these 5 env. var. you mention. First of all, you would be quite lucky if you got overall significant test with five variables and 18 samples in non-experimental dataset. Moreover, only 1 axis and 2 env. var seem to describe some species-environment pattern, but they are definitely not great at it. As I understand your results, it could be read as: 1st canonical axis describes something non-random. It seems that it is related to Var1 and Var4, but not so tightly, as there is no significant marginal term. Both of the variables seem to be somehow correlated with the data, but not necessarily with each other. Everything else is just a mess that can be used to correlate with anything else - therefore the overall significance of the model is low. It is like having single (small) gem in the whole mountain: The gem would not increase the price of the whole mountain too much even if you know it is there, and an average cubic foot of the mountain is almost priceless. What to do: plot var1 and var4 against each other (and against data) and try to think what links them together. If you have enough resources, go to the field and try to get info about that common link. If not, present it like this: I have tried to relate my data to these 5 env vars. (Plot envfit). Using my variables, I was able link 0.06/(0.06 +0.14)*100 percent of overall variability in the data to the environment, which was not a significant portion. None of the env. variables described significant portion of variability alone, but (...number)% of variability in the data could be ascribed to linear combination of Var1 and Var4 (plot: RDA species~Var1+Var4. Besides: Is not there some interaction here?). Do not forget to discuss link data-var1-var4. (Maybe this could be still seen as fishing, so be prepared.) I both hope this helps and that someone who understands this topic better will correct me. Best, Martin
------------------------------ Pokud je tento e-mail sou??st? obchodn?ho jedn?n?, P??rodov?deck? fakulta Univerzity Karlovy v Praze: a) si vyhrazuje pr?vo jedn?n? kdykoliv ukon?it a to i bez uveden? d?vodu, b) stanovuje, ?e smlouva mus? m?t p?semnou formu, c) vylu?uje p?ijet? nab?dky s dodatkem ?i odchylkou, d) stanovuje, ?e smlouva je uzav?ena teprve v?slovn?m dosa?en?m shody na v?ech n?le?itostech smlouvy.