[R-sig-eco] Vegan CCA - Problem in constraining variables

[Gavin Simpson]

On Thu, 2013-01-17 at 17:50 -0200, Pedro Meirelles wrote:
> Hello everyone,
> 
> This is my first post in this list and I am a new r user and I am not very
> experienced in multivariate analysis, sorry if my question is silly.
> 
> I am trying to run a cca (vegan package) but I am encountering a problem: I
> want to constrain the analysis by all environment variables, but it do not
> happens. The program "choose" some of it. When I try to plot the results
> only these "automatic chosen" variables are ploted. I tried to run cca with
> vegan data (varespec and varechem) and it worked fine.
> 
> There is something strange on the "Biplot scores for constraining
> variables" results. The CA's have only 0 values (bellow in yellow). I
> am writing the complet "Biplot scores for constraining variables" section.
> 
> My data is like this:
> 
> I have 9 samples (I will not show all data to reduce the email size).
> 
> I have 9 environmental variables (nutrients).
> > env
>       Depth   Sal Nitrite Nitrate Amonia T_Org_N Silicate Total_I_P OrthoP
> Vit1     63 37.07    0.03    1.24  0.031   5.849     0.85      0.14   0.08
> Vit2     63 37.07    0.03    1.24  0.031   5.849     0.85      0.14   0.08
> Dav1     40 37.35    0.05    1.43  0.031   8.849     0.76      0.11   0.14
> Dav2     40 37.35    0.05    1.43  0.002   8.878     0.76      0.11   0.14

By the looks of those data, some of your env samples are repeated to
make the nine total samples. That won't help matters.

You can also run `alias(spp.cca)` to see which if any terms are linearly
dependent upon one another as that can also reduce the effective number
of contraints.

Bottom line, vegan used what it could of your data and you need to look
at your data to see what is wrong as you have it and we don't.

HTH

G

> .
> .
> 
> I have 32 "species" (actually this is bacterial and archeal phyla). I will
> not show all columns to reduce the email size.
> 
> > spe
>       Acidobacteria Actinobacteria Aquificae ...
> Vit1              9            129         5      ...
> Vit2             14            154         8      ...
> Dav1              8            122         4      ...
> 
> 
> I am running the cca with the follow script:
> 
> >library(vegan)
> >spe <- read.csv("cvt_org_test.csv", row.names=1)
> >env <- read.csv("test_chem2.csv", row.names=1)
> > spe.hel <- decostand(spe, "hellinger")
> > spe.cca <- cca(spe.hel,env)
> > summary(spe.cca) # Scaling 2 (default)
> Call:
> cca(X = spe.hel, Y = env)
> 
> Partitioning of mean squared contingency coefficient:
>               Inertia Proportion
> Total         0.06054     1.0000
> Constrained   0.03120     0.5154
> Unconstrained 0.02934     0.4846
> 
> Eigenvalues, and their contribution to the mean squared contingency
> coefficient
> 
> Importance of components:
>                          CCA1     CCA2     CCA3     CCA4     CA1      CA2
>   CA3      CA4
> Eigenvalue            0.01906 0.006717 0.003055 0.002371 0.01433 0.007767
> 0.00482 0.002418
> Proportion Explained  0.31480 0.110960 0.050470 0.039170 0.23673 0.128300
> 0.07963 0.039940
> Cumulative Proportion 0.31480 0.425760 0.476230 0.515400 0.75213 0.880430
> 0.96006 1.000000
> 
> Accumulated constrained eigenvalues
> Importance of components:
>                          CCA1     CCA2     CCA3     CCA4
> Eigenvalue            0.01906 0.006717 0.003055 0.002371
> Proportion Explained  0.61079 0.215280 0.097920 0.076010
> Cumulative Proportion 0.61079 0.826070 0.923990 1.000000
> 
> Scaling 2 for species and site scores
> * Species are scaled proportional to eigenvalues
> * Sites are unscaled: weighted dispersion equal on all dimensions
> 
> 
> Species scores
> 
>                          CCA1      CCA2      CCA3      CCA4        CA1
>    CA2
> Acidobacteria        0.065258  0.038704  0.009574 -0.112006  0.0817235
>  0.0143286
> Actinobacteria       0.077451  0.049255 -0.046415  0.045290  0.0178117
> -0.0231979
> Aquificae            0.137472 -0.057698  0.017360 -0.017047  0.0859391
> -0.0749676
> .
> .
> .
> 
> Site scores (weighted averages of species scores)
> 
>           CCA1    CCA2    CCA3      CCA4      CA1      CA2
> Vit1  -0.35189 -0.7507 -2.6425 -0.961233 -0.72976  0.08807
> Vit2   0.04988 -0.2552 -1.0121  0.321500  0.66991 -0.08085
> .
> .
> .
> 
> Site constraints (linear combinations of constraining variables)
> 
>          CCA1    CCA2    CCA3    CCA4      CA1      CA2
> Vit1  -0.1424 -0.4923 -1.7924 -0.2924 -0.72976  0.08807
> Vit2  -0.1424 -0.4923 -1.7924 -0.2924  0.66991 -0.08085
> .
> .
> .
> 
> Biplot scores for constraining variables
> 
>            CCA1    CCA2    CCA3     CCA4 CA1 CA2
> Depth    0.6576 -0.3701 -0.6555 -0.02914   0   0
> Sal     -0.6385  0.3949  0.6603  0.01846   0   0
> Nitrite  0.5303  0.7679  0.1164 -0.33999   0   0
> Amonia  -0.9195  0.1331  0.3570  0.09710   0   0
> 
> 
> Thank you very much for your help and support!
> 
> All the best!
> 

-- 
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