[R-sig-eco] non-metric MDS comparison - vegan vs. ecodist packages

[Sarah Goslee]

The two packages use slightly different stress calculations. Please see the
documentation for each for details.

Also, note that nmds() is bare-bones, and relies on the user to offer
the correct data, while the vegan function performs scaling and other
transformations by default. The two ordinations you performed are
not equivalent. Again, you'll need to consult the vegan documentation.

Sarah

2012/2/20 Gian Maria Niccolò Benucci <gian.benucci at gmail.com>:
> Hi r-sig-ecology Members,
>
> I would please you to examine the differences I found in metaMDS() and
> nmds() outputs and possibly draw some conclusions. As I wrote in past
> emails I have 24 samples of ectomycorrhizal fungi grouped into two
> different communities (12 natural and 12 cultivated).
>
> here is the code:
>
>> metaMDS(data_matrix2, distance="bray", k=2, autotransform=F) -> metaMDS
>> metaMDS
>
> Call:
> metaMDS(comm = data_matrix2, distance = "bray", k = 2, autotransform = F)
>
> global Multidimensional Scaling using monoMDS
>
> Data:     data_matrix2
> Distance: bray
>
> Dimensions: 2
> *Stress:     0.04536661 *
> Stress type 1, weak ties
> No convergent solutions - best solution after 20 tries
> Scaling: centring, PC rotation, halfchange scaling
> Species: expanded scores based on ‘data_matrix2’
>
>> nmds <- nmds(dist_bray, mindim = 2, maxdim = 2, nits = 100)
> Using random start configuration
> Using random start configuration
> ...
>> nmds_min
>            X1          X2
> 1  -0.66226262  0.16392824
> 2 -0.68844987 -0.20891993
> 3 -0.47717515  0.55323693
> 4 -0.67213392 -0.09195847
> 5 0.03305172  0.41844232
> 6   0.31992006  0.53887910
> 7  -0.61944875  0.34411146
> 8 0.07013849  0.65723057
> 9 0.53053436  0.37444633
> 10  0.26704705  0.39849341
> 11 -0.20981416  0.70391983
> 12 -0.61620355 -0.43568743
> 13 0.14219660 -0.69571194
> 14 0.42365981 -0.43308767
> 15 0.15840330 -0.12872863
> 16 -0.00492407 -0.06889680
> 17 -0.20513513 -0.58052156
> 18 0.46546214  0.12019775
> 19 0.36753709 -0.25048256
> 20 -0.09446486 -0.61943616
> 21  0.15010553 -0.31995009
> 22  0.41540872 -0.29507200
> 23  0.42573367 -0.12321584
> 24  0.48081354 -0.02121688
>> min(nmds$stress)
> [*1] 0.2787161*
>> nmds$r2[which.min(nmds$stress)]
> [1] 0.6338372
>
> Is it possible I got so different stress values??
>
> Thanks for replying,
>
> --
> Gian
>
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>
>
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-- 
Sarah Goslee
http://www.stringpage.com
http://www.sarahgoslee.com
http://www.functionaldiversity.org