Hi Jari,
I have a final (hopefully) question.  I have narrowed down the number of
environmental variables and removed some of the community (and associated
env. data) rows if they are missing too many environmental variables.
Then, when I run the anova.cca by terms I get the following error message.
anova(m2,by='terms',perm=999)
Error in La.svd(x, nu, nv) : error code 1 from Lapack routine 'dgesdd'

any thoughts about why this is happening or how I can avoid it so that I
can run the anova by terms.

Thank you so much for all of your help with this!

colleen



On Tue, Jun 4, 2013 at 1:59 AM, Jari Oksanen [via r-sig-ecology] <
ml-node+s471788n7578184h50@n2.nabble.com> wrote:

> Dear Colleen,
> On 03/06/2013, at 22:32 PM, ckellogg wrote:
>
> > Hello Jari,
> > Thank you for your help with this.  The solution you suggested in your
> > second post worked quite well.  However, i think another subset of my
> data
> > is too 'holey', because when I run CCA on this set of environmental
> > variables (or the a CCA with the previous environmental variables and
> the
> > additional ones), I get an error:
> >
> >> toolik250.cca2
> >>
> <-cca(toolikotus250.ra~logtemp+conductivity+pH+logBacProd+DIC+logDCO2+sqrtDCH4+logDOC+sqrtPhosphate+sqrtNitrate+sqrtTDN+sqrtTDP+logPC+logPN+Ca+Mg+logNa+logK+SO4+logChloride+Silica,toolikenv.s,
>
> >> na.action=na.exclude)
> > Error in predict.cca(x, newdata = excluded, type = "wa", model = "CA") :
> >  model “CA” has rank 0
> >
> > The CCA runs if I use na.action=na.omit, but then when I run the anovas,
> > there is apparently no residual component.  For example,
> > No residual component
> >
> > Model: cca(formula = toolikotus250.ra ~ logtemp + conductivity + pH +
> > logBacProd + DIC + logDCO2 + sqrtDCH4 + logDOC + sqrtPhosphate +
> sqrtNitrate
> > + sqrtTDN + sqrtTDP + logPC + logPN + Ca + Mg + logNa + logK + SO4 +
> > logChloride + Silica, data = toolikenv.s, na.action = na.omit, subset =
> > -toolik250.cca2$na.action)
> >         Df  Chisq F N.Perm Pr(>F)
> > Model    12 5.3003        0
> > Residual  0 0.0000
> >
> Yes, probably too many holes. You have no residual variation which
> indicates that the number
> of predictor variables (constraints) is higher than the number of
> remaining observations.
>
> Cheers, Jari Oksanen
>
> > So, I am thinking that examining the relationship between the microbial
> > community and this subset of environmental variables might not be
> possible
> > without my first manually curating which samples and variables should be
> > included, correct?
> >
> > Thank you,
> > Colleen
> >
> >
> >
> > --
> > View this message in context:
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> >
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> --
> Jari Oksanen, Dept Biology, Univ Oulu, 90014 Finland
> [hidden email] <http://user/SendEmail.jtp?type=node&node=7578184&i=1>,
> Ph. +358 400 408593, http://cc.oulu.fi/~jarioksa
>
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-- 
colleen t.e. kellogg
(c) 206-714-2441




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