Maria,


*...Nevertheless you still do not know if your communities are significantly
different between each other, within each host. Now it depends on the
hypothesis you intend to test.*..


I think no sense for "Community" inside "Host"... Couse A and B are from the
same host "Corylus", and C and D are from host "Ostrya".
So the effect between two host tree species is real, but difference between
two community inside the same host (A vs B i.g.) could not be.
That is also confirmed by my diversity indices data I got (see my lastest
post), they show that A and B are alwasy different from C and D, but between
A and B (and for sure also between C and D ) there are no statistical
differences (ANOVA).

I think both "host" and "community" effect and if use them separately I got
:

> adonis(sqrtABCD ~ Host, method="bray", data=env.table, permutations=99)

Call: adonis(formula = sqrtABCD ~ Host, data = env.table, permutations =
99,      method = "bray")

                Df SumsOfSqs  MeanSqs  F.Model     R2 Pr(>F)
Host       1.00000   1.64429  1.64429  5.38984 0.1242   0.01 **

Residuals 38.00000  11.59276  0.30507          0.8758
Total     39.00000  13.23705                   1.0000
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


> adonis(sqrtABCD ~ Community, method="bray", data=env.table,
permutations=99)

Call: adonis(formula = sqrtABCD ~ Community, data = env.table, permutations
= 99,      method = "bray")

                Df SumsOfSqs  MeanSqs  F.Model     R2 Pr(>F)
Community  3.00000   2.43264  0.81088  2.70182 0.1838   0.01 **

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
>


Thank you so much to all want to write any comments on that...

Cheers,


Gian




-- 
Dr. Gian Maria Niccolò Benucci
Department of Applied Biology - University of Perugia
Borgo XX Giugno, 74
I-06121 - Perugia, ITALY
Email: gian.benucci@gmail.com
Tel: +39.075.5856433






2009/12/10 Maria Dulce Subida <mdsubida@icman.csic.es>

 Dear Gian,
>
> I'm still not quite sure about the functioning of adonis(). I made some
> proofs and I don't understand how does it calculate the degrees of freedom
> of a nested factor. But this is most probably due to my lack of experience
> with this function (as I told you I usually work with the PERMANOVA add-in
> for PRIMER developed by Marti Jane Anderson and others).
> Anyway, in your table of results *I think* you miss the effect of the term
> Community(Host) [which means: the factor community nested in the factor
> host]. In the table you send me you can only see that there is a significant
> effect of the term Host (which I think it means that the communities are
> significantly different between hosts). Nevertheless you still do not know
> if your communities are significantly different between each other, within
> each host. Now it depends on the hypothesis you intend to test. It probably
> does not make any sense to ask if communities differ within each host, but
> *I think* you still have to include the term Community(Host) in your
> table. Though, I would wait for the opinion of a more experienced user of
> adonis() and ANOVA testing in general.
>
> HTH
>
>
> Cheers,
>
> Dulce
>
>
>  Maria Dulce Subida
>
>
>
> ~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*
>
>
>
> Instituto de Ciencias Marinas de Andalucía (ICMAN)
>
> Consejo Superior de Investigaciones Científicas (CSIC)
>
> Campus Universitário Río San Pedro
>
> 11510 Puerto Real - Cádiz. España.
>
>
>
> www.icman.csic.es               0034 956832612 ext. 316
>
>
>
> ~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*
>
>
>
>
> Gian Maria Niccolò Benucci escribió:
>
> Hi Maria,
>
> Yes, I think it's right, maybe now I did the correct function, It seems that
> the "area" effect is also visible...
>
>
>
>  adonis(ABCDsqrt ~ Host, method="bray", data=env.table, permutations=99,
>
>
>  strata=env.table$Community)
>
> Call: adonis(formula = ABCDsqrt ~ Host, data = env.table, permutations = 99,
> method="bray", strata = env.table$Community)
>
>                 Df SumsOfSqs  MeanSqs  F.Model     R2 Pr(>F)
> Host       1.00000   1.64429  1.64429  5.38984 0.1242   0.01 **
> Residuals 38.00000  11.59276  0.30507          0.8758
> Total     39.00000  13.23705                   1.0000
> ---
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
>
> don't you think?
>
>
> Gian
>
>
>
>
> 2009/12/9 Maria Dulce Subida <mdsubida@icman.csic.es> <mdsubida@icman.csic.es>
>
>     Hi Gian,
>
>
> I've never used adonis() [I'm a R beginner] but I've been doing
> multivariate analysis for some time: I usually use PRIMER with the PERMANOVA
> add-in. nMDS followed by PERMANOVA works quite well for me in experimental
> designs similar to yours. But it seems to me that you have nestedness in
> your design and this should be considered when you do adonis(). After a
> quick look to the ?adonis? documentation, *I think* you should state
> strata = env.table$Community in your adonis() function, since your
> "community" factor is nested within the "host" factor. Otherwise you're
> getting wrong pseudo-F values as well as wrong p-values.
> Good luck!
>
> Cheers,
>
> Dulce
>
>
>  Maria Dulce Subida
>
>
>
> ~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*
>
>
>
> Instituto de Ciencias Marinas de Andalucía (ICMAN)
>
> Consejo Superior de Investigaciones Científicas (CSIC)
>
> Campus Universitário Río San Pedro
>
> 11510 Puerto Real - Cádiz. España.
>
>
> www.icman.csic.es               0034 956832612 ext. 316
>
>
>
> ~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*
>
>
>
>
> Gian Maria Niccolò Benucci escribió:
>
> Jari, Gavin, Chris, Gabriel and Carsten...
>
> Many thank you all for your support and kindness... and for your competence
> and experience that could not be ever comparized to mine at least in that
> stuffs...
>
> Gabriel said: .*..I found this mailing list very helpful many times for my
> own questions, but also very informative when just following the threads on
> other questions...
> *
> I complitely agree about that, so here I am to go deeper inside my
> statistical problems...
>
> As Gavin argued the plot:
>
>
>
>  NMS.2$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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>
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>
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>






-- 
Dr. Gian Maria Niccolò Benucci
Department of Applied Biology - University of Perugia
Borgo XX Giugno, 74
I-06121 - Perugia, ITALY
Email: gian.benucci@gmail.com
Tel: +39.075.5856433

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