search for: canoco

Hi, I want to include a vector representing the sites - environmental data correlation in a PCA. I currently use prcomp (no scaling) to perform the PCA, and envfit to retrieve the coordinates of the environmental data vector. However, the vector length is different from the one obtained in CAnoco when performing a species - environmental biplot (scaling -2). How can I scale the vector in order to be in accordance with Canoco, or which other scaling options are there? Thanks for help, Heike ____________________________________________________________________________ "Dit bericht en...

...s under full model. The model was p<0.05 and the result of the plot was "good for my eyes", however, when I did summary(CCA1), the first two axis accounted 0.04 CCA1 and similar in CCA2....then the variation explained by each axis was small. On the other hand, when I performed CCA in CANOCO, without selecting the option Log-transforming data matrix and without downweighting rare species, the results were the opposite from the CCA performed in R. The axes accounted high percentage of variation, the model was also significant, but the plot had little sense. Thank you very much! [[a...

...m when it comes to getting values for "total inertia" and "R-squared" for my DCA using "decorana" in the package "vegan". I have tried the "goodness" function, but the reply indicates that it does not work with "decorana" class objects. In Canoco one gets the Total inertia in the output together with 4 eigenvalues. In decorana one gets the 4 eigenvalues, but not the Total inertia. Is there a way for me to get the Total inertia without having to go over to Canoco? Best regards, Petter Hedberg ___________________________________ NOCC, ht...

...11) on hypatia.math.ethz.ch X-Spam-Level: **** X-Spam-Status: No, hits=4.2 required=5.0 tests=MSGID_FROM_MTA_HEADER,RCVD_IN_BL_SPAMCOP_NET autolearn=no version=2.63 Dear r-help list, my question is about ordination technics: To decide using a linear model response or a unimodal model response, in Canoco (software for ordination technics) you can calculate a so-called "length of gradient". (from Canoco Help file:) > The length of gradient is a measure of how unimodal the species > responses are along an ordination axis. It is the range of the > sample scores divided by the avera...

...unny-looking tri-plots, etc., I don't really consider it "finished", because i found the references that i had access to very ambiguous in their description of the method, and the desired outputs seem to have changed subtly over the years. In particular, biologists at my lab who used CANOCO got certain kinds of (eigenvectors) output that were not defined or indeed even referred to in the literature. As luck would have it, the CANOCO manual had mysteriously disappeared, so all my confusion may well be a function of not having read the right documentation. And i'm sure that if i h...

Hello, I am trying to obtain f-values for response (independent) variables from a CCA performed in vegan package, to see which ones of them have significative influence in my dependent variables (like the manual selection in canoco), but I can't find any function (or package) that do such a thing. The dependents variables are species data, and the independents are ambiental data. Than you. Fabricius [[alternative HTML version deleted]]

Dear members, I am performing multivariate analysis on marine benthic populations using R. At first glance I found ca and VEGANO packages to be the suitable for the task, but neither has incorporated Detrended Canonical Correspondence Analysis (DCCA), which is just the method I want to apply on my data. I've looked for alternative packages containing the method, but my suspicion is that

...ckfor)" and I get an error message: ----------------------------------------------------------------------------- WARNING: ignoring environment value of R_HOME * Installing *binary* package 'packfor' ... * DONE (packfor) > library(packfor) packfor: R Package for Forward Selection (Canoco Manual p.49) version 0.0-8Error in dyn.load(file, DLLpath = DLLpath, ...) : unable to load shared library '/Library/Frameworks/R.framework/Versions/2.7/Resources/library/packfor/libs/i386/packfor.so': dlopen(/Library/Frameworks/R.framework/Versions/2.7/Resources/library/packfor/libs/i3...

Is there an R function that does canonical correspondence analysis. Can it be done using the VR function corresp()? If not, how hard it be to write R code to do it? I am a population biologist with long but patchy programming experience in C, Smalltalk, Java and other languages. Thanks, Patrick Foley patfoley at csus.edu

Hallo List, I'm trying to implemement a restricted permutation scheme in permutest(). More precisely I have dependence in my data that should be allowed for in the permutation - I simulated the problem in the example of the vegan documentation p.24: library(vegan) data(varespec) ## Bray-Curtis distances between samples dis <- vegdist(varespec) ## First 16 sites grazed, remaining 8 sites

...o, 64:69-77 More general references are: Jongman, RHG., Ter Braak, CJF., and, van Tongeren, OFR. (1995) Data analysis in community and landscape ecology. CUP. Kent, M. & Coker, P. (1992) Vegetation description and analysis: A practical approach. Wiley. As far as I am aware, only MVSP and Canoco carry out CCA. I hope this is of some interest and it does raise the general point that programming literate ecologists don't seem to have yet fully embraced S-Plus or R. Having only recently found S-Plus and R myself I had rather hoped that some of the common ecological statistical tools...

Hi all, I am fairly new to R and I am trying to run mvpart and create a MRT using explanatory variables and covariables. I've been following the procedures in Numerical Ecoogy with R. The command (no covariables) which works fine - ABUNDTMRT <- mvpart(abundance ~ .,factors,margin=0.08,cp=0,xv="1se",xval=nrow(abundance),xvmult=100,which=4) where abundance is 4th root

...ng the same Bray-Curtis distance measure (distance matrices produced by the two programs are the same), and using the same sequential test for significance. Below is a table displaying the order of the model terms and the pseudo-F values computed by R and by PRIMER (we also ran the same analysis in CANOCO which showed the same results in pseudo-F values as PRIMER). We have not been able to figure out why we get very different pseudo-F values, leading us to believe that R calculates pseudo-F values differently than PRIMER for the sequential tests. Furthermore, constrained ordination outputs, i.e., ei...