similar to: "predict"-fuction for metaMDS (vegan)

Dear all, I would like to calculate a cca (package vegan) with species and environmental data. One of these environmental variables is cos(EXPOSURE). The problem: 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. The cca does not run with missing values. What can I do to make vegan cca ignoring these missing values? Thanks a lot,

Dear r-helpers, I just read in an article by Virtanen et al. (2006) where vegetation-environment relationships are studied by fitting smoothed surfaces on an NMDS ordination using GAMs (Wood 2000). The authors describe, that they used R? as goodness-of-fit statistic, which they compare to the R? of fitted vectors. Calculations were carried out using the package vegan (Oksanen). I know that I can

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

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

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.,

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,

Dear R-community, dear Jari Oksanen! I use metaMDS (package vegan) to calculate NMDS. In a lot of papers I read that it is recommended to use previous best solutions as a new starting configuration to get better results and to avoid local minima. On the help page I found that a previous.best-command is already implemented in metaMDS: metaMDS(comm, distance = "bray", ...,plot = FALSE,

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

Hi, I've been using R for a while now but I've got a problem with metaMDS (in the vegan package) that I can't quite figure out. I have a set of proportion data (from 0-1, rows sum to 1) that I apply metaMDS to using the command: nMDS.set=metaMDS(sqrt(test.set),distance="euclidean",k=3,zerodist="add",autotransform=FALSE) I am using a squared-chord distance

Dear vegan team, Vegan development happens now completely in github. R-Forge repository is no more in sync with github. I tried to commit all github changes to R-Forge, but a week ago I got a conflict in file and I haven't had time to resolve that conflict. You can follow vegan development and vegan discussion also without signing to github. The system seems to be completely open and does not

Dear r-helpers! How can I integrate other distances (in the form of a dist object) into function metaMDS? The problem: metaMDS needs the original data.frame for the calculation and only the default distances of function vegdist are allowed. Any suggestions are greatly appreciated! Thank you, Kim -- Jetzt kostenlos herunterladen: Internet Explorer 8 und Mozilla Firefox 3.5 - sicherer, schneller

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 am using the function metaMDS with jaccard distances to ordinate a set of constituent by site matrix. I can post this data if it would be helpful, but it is large to include in an email. I can also provide reproducable code if necessary. I would like to get an R^2 value for the axes of the ordination configuration that I get with metaMDS in the vegan package is there a way to do this- is it

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, I'm trying to use metaMDS with a dissimilarity matrix of angles, not Bray-Curtis, and I wanted to know if there is an in-built function to produce a plot of stress values against dimensions, that could be used to determine the 'true' dimension of the solution. The number of objects is only a lowly 8 so any solution higher than 2-dimensional is not likely to be interpretable,

The design decision in metaMDS says that it uses: Minchin, P.R. (1987) An evaluation of relative robustness of techniques for ecological ordinations. Vegetatio 71, 145-156. This is the paper that I found by the same name. Is this the correct reference? Minchin, Peter R.1987. An Evaluation of the Relative Robustness of Techniques for Ecological Ordination. Vegetatio. Vol. 69, No. 1/3: 89-107.

What does Generalized Cross Validation score mean. I preform and ordisurf on an ordination (nmds) with an environmental variable. I am trying to figure out "how well" the environmental varibles predict/explain the sites placements in species space. Any help would be greatly appreciated. Any pointers to literature... would be welcome. thanks in advance, -- Stephen Sefick Research

Hi, I'm using nmds command (library vegan) to analyze some fishing data. I'd like to plot not only points, but also the names of species and stations in a specified position. I used the command text(nmds$points[,1], nmds $points[,2],labels=row.names(nmds $points),pos=3,cex=0.5) But the labels are sometimes overlapped. Is there any way to use identify, or a similar command, to plot the

Dr. Stevens, Hi, my name is Trey Scott, and I'm a grad student of Brian McCarthy's. He referred me to you because of your expertise in handling complex R problems. We were hoping you could help us solve a nagging problem that is prohibiting me from producing graphicl output. Here is a simple mock-up of the matrix I'm using a b c d e f 1i 1 4

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