similar to: environmental data as vector in PCA plots

Dear all at the R-project help list. I have run into a problem 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

Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: 7bit X-Virus-Scanned: by amavisd-new X-Spam-Checker-Version: SpamAssassin 2.63 (2004-01-11) 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:

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.

ID: T8dfe471e360ac80264c6c Dear, I'm using R 2.8.1 with the package reshape version 0.8.2 . It seems that the combine_factor function has problems with combining levels to an empty level: #EXAMPLE WORKING test<-sample(c(1:10),1000,replace=T) testf<-factor(test, c(1:10), LETTERS[1:10]) table(testf,exclude=NULL) testc<-combine_factor(testf, c(1,1,1,1,1,2,2,2,2,2))

Hello R experts, I've used metaMDS to run NMDS on some fish abundance data, and am also working on correlating environmental data to the NMDS coordinates. I'm fairly new to metaMDS and NMDS in general, so I have what are probably some very basic questions. My fish abundance data consists of 66 sites for which up to 20 species of fish were identified and counted. I ran metaMDS on this data

Hi R-experts, I am using the envfit function over an ordination of floristic data. The problem is that every time that I run it changes the results. Sometimes dramatically, selecting variables that the first time were not significant. I do not get what could be the problem or if is normal given the permutations are different. # the NMDS ordination gap_flor_NMDS_chord <- metaMDS(gaps_flor,

Hi R experts, I'm looking for some help with plotting vectors from envfit in vegan, onto a 3d plot using ordiplot3d. So far I have data.mds <- metaMDS(data, k=3,trace = FALSE) vect_data<-envfit(data.mds,vegdata[,3:21],choices=1:3,permu=9999) ordiplot3d(data.mds,envfit=vect_data) ordixyplot(data.mds,pch=pts,envfit=vect_data) (my data's not really called data, I thought it might be

Hello there, I'm trying to plot vectors with p<0.1 in a NMDS ordination plot using p.max. Below the scripts I'm using. I guess I'm missing something! could you please give me a hand? species<-metaMDS(species_matrix)ef<-envfit(species,environmentaldata_file,permu=999,na.rm=TRUE)efplot(species, dis="sites")plot(ef,p.max=0.1) Error in plot.envfit(ef, p.max = 0.1) :

I'm getting lots of grief from reviewers about figures generated with the envfit function in the Vegan package. Has anyone else struggled to effectively explain this analysis? If so, can you share any helpful tips? The most recent comment I've gotten back: "What this shows is which NMDS axis separates the communities, not the relationship between the edaphic factor and the

Dear r-helpers! Jan Thiele asked r-help-list in february, but I could not find an answer to his question. I have the same problem: While preparing figures of 'envfit' plots with vegan for publication, I ran into a layout problem, that I found no solution for in the literature or the help archive: The labels of the vectors that indicate correlations of environental variables sometimes

Hello, I'm a new user to R, and I was trying to install "packfor" in my R console and I always run into an error. I tried to search, in in the forum, someone that already might have made the same question, but all I could find was a general information how to install libraries in R. Pass through all that procedure (Package&Data->Package Installer->Local Source

Dear all, I did a RDA and when I looked to the signification of the test with permutest, the output was non-significant. But when I used the envfit function, some of the vectors are significant. All the test's conditions are respected. What it means? Is it an error in the script? Commands and output: > permutest(rda.ind, perm=999, first=TRUE) Permutation test for rda  Call:

Hello, I am using vegan to do an NMDS plot and I would like to suppress the labels for the loading vectors. Is this possible? Alternatively, how can I avoid overlap? Many thanks for the help. Example code: #perform NMDS using metaMDS() function spe.nmds<-metaMDS(data, distance='bray',k=2 , engine = "isoMDS", autotransform=F, trymax=1000) #calculate the loading (i.e.,

I'm pretty new to R and would appreciate some help interpreting the output of a function that was recommended to me. I've used the *envfit *function in the vegan package to plot vectors of four climate variables onto a species matrix ordination. The output indicates that only a single variable (mean_temp) is significant: ***VECTORS NMDS1 NMDS2 r2

Hi all, I have site data with plant species cover and am looking for trends. I'm kind of new to this, but have done lots of reading and can't find an answer. I tried decorana (I know it's been replaced by ca.) and see a trend, but I'm not sure what it means. Is there a way to get the loadings/eigenvectors of the axes (like in PCA)? Is there a way to do this with rda() too? How

Dear r-Community, Step1: I would like to calculate a NMDS (package vegan, function metaMDS) with species data. Step2: Then I want to plot environmental variables over it, using function envfit. The Problem: One of these environmental variables is cos(EXPOSURE). But for flat releves there is no exposure. The value is missing and I can't call it 0 as 0 stands for east and west. Therefore I

Hi R users, I have two data matrix, one with community data and another with environmental data. Prior to preform the CCA, I have used PCA to select some environmental variables and to avoid redundance information. The result is that I have 4 environmental variables and my community data matrix where, following bibliography, I have eliminated rare species. All variables were log-transformed (x+1)

I think i mentioned this in private communication a while back, but in case anyone else cares: I have a version of canonical correspondence analysis (CCA) coded up in R. I based it on Ter Braak and Prentice (1988) Adv. Ecol. Res. 18:271-317, Ter Braak (1986) Ecol. 67(5):1167-1179, and Ter Braak (1995) Section 5.9 in Jongman, Ter Braak, and van Tongeren "Data Analysis in

Hi Im currently trying to plot my NMDS data together with fitted variables (envfit funct) on an ordination plot. The plot function shows two displays="sites" and "sp". I was wondering how to plot it so that the sites come up as different points for different sites but the species come up as actual names? It looks a little busy at the moment with everything in. Sya -- View

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