Jari, Gavin, Chris, Gabriel and Carsten...
Many thank you all for your support and kindness... and for your competence
and experience that could not be ever comparized to mine at least in that
stuffs...
Gabriel said: .*..I found this mailing list very helpful many times for my
own questions, but also very informative when just following the threads on
other questions...
*
I complitely agree about that, so here I am to go deeper inside my
statistical problems...
As Gavin argued the plot:
NMS.2$stress
[1] 24.53723
NMS.3$stress
[1] 16.29226
NMS.4$stress
[1] 11.79951
plot(2:4, c(24.53723, 16.29226, 11.79951), type = "b")
didn't show significally differences...
...so as him suggested I did the stressplot() and got shepard graphs...
(just to specify, sqrtABCD is the square roots transforming of the species
matrix)
stressplot(NMS.2)
Using step-across dissimilarities:
Too long or NA distances: 230 out of 780 (29.5%)
Stepping across 780 dissimilarities...
Non-metric fit, R2=0.94
Linear fit, R2=0.719
stressplot(NMS.3)
Using step-across dissimilarities:
Too long or NA distances: 230 out of 780 (29.5%)
Stepping across 780 dissimilarities...
Non-metric fit, R2=0.973
Linear fit, R2=0.815
stressplot(NMS.4)
Using step-across dissimilarities:
Too long or NA distances: 230 out of 780 (29.5%)
Stepping across 780 dissimilarities...
Non-metric fit, R2=0.986
Linear fit, R2=0.875
>From this data is clear that the fit is better for the NMS.4 (k=4) also the
blue points into the graph are more near to red line, less spare around the
graph space...
But maybe the R2 values of the NMS.2 aren't so bad in correlation terms, are
they?
In reason of what Gabriel said: *...I personally like a combination of NMDS
with the permutational MANOVA approach (by Marti Anderson) implemented in
the function adonis() in vegan. You can use the same dissimilarity measure
(Bray-Curtis) used for the NMDS and can test the "Area" vs. the "Host"
effect on parasite (was it?) composition. I think that could be a very
useful complement to an NMDS-derived ordination plot and then you may also
regard high-stress "representations" (and that´s what all the
low-dimensional ordination plots really ARE!) in a different light.*..
adonis(sqrtABCD ~ Host*Community, method="bray", data=env.table,
permutations=99)
Call:
adonis(formula = sqrtABCD ~ Host * Community, data = env.table,
permutations = 99, method = "bray")
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Host 1.00000 1.64429 1.64429 5.47874 0.1242 0.01 **
Community 2.00000 0.78834 0.39417 1.31337 0.0596 0.23
Residuals 36.00000 10.80441 0.30012 0.8162
Total 39.00000 13.23705 1.0000
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
...So, I would explain a little about my datasets:
- the species matrix is done by roots samples in which were counted the
ectomycorrhizal fungal species present (cells entities are different tips
individuals);
- sample where taken into four "Area" (A,B,C,D). The ares are about 30
meters far away one to each other;
- areas A and B are both form Corylus roots while areas C and D are both
from Ostrya roots.
To be more clear that is the enviromental matix used:
env.table
Community Host
A1 A Corylus
A2 A Corylus
A3 A Corylus
A4 A Corylus
A5 A Corylus
A6 A Corylus
A7 A Corylus
A8 A Corylus
A9 A Corylus
A10 A Corylus
B1 B Corylus
B2 B Corylus
B3 B Corylus
B4 B Corylus
B5 B Corylus
B6 B Corylus
B7 B Corylus
B8 B Corylus
B9 B Corylus
B10 B Corylus
C1 C Ostrya
C2 C Ostrya
C3 C Ostrya
C4 C Ostrya
C5 C Ostrya
C6 C Ostrya
C7 C Ostrya
C8 C Ostrya
C9 C Ostrya
C10 C Ostrya
D1 D Ostrya
D2 D Ostrya
D3 D Ostrya
D4 D Ostrya
D5 D Ostrya
D6 D Ostrya
D7 D Ostrya
D8 D Ostrya
D9 D Ostrya
D10 D Ostrya
...maybe could be helpfull to say that I calculated diversity indices
(richness, shannon, simpson and evenness) for my 4 areas and I use ANOVA to
see if them are diffent one from each other.
The results show me that area A and B are always different form areas C and
D but no differences are between them, so clearly Corylus fungal community
is alwasy different from Ostrya one.
...So, I think that "Host" effect is clear while the effect of "Community"
couldn't be the same in reason to that areas are similar 2 by 2, ...is it
right?
When I plot the MNS.2 and I watch to the Graph I clearly see that sample
points of A,B areas or Corylus are positioned on the left side while areas C
and D of Ostrya are more sparse and are positioned into the low right
side...
So, what else to say... I'll leave you space for any comments :))))
Tank you all,
Gian
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