similar to: CCA plot

I performed canonical correspondence analysis (cca) with the example data of vegan, but I'm not able to obtain a table like scores() for the constraining variables. I can see them in the summary() mode, but it would be great to have in a separate table. Any suggestion?, thanx Gianandrea require(vegan) data(varespec) data(varechem) vare.cca<-cca(varespec,varechem) scores(vare.cca)

Dear all, I realised a correspondence analysis with function cca() of vegan library. Just like in Okansen (2010) in the example of R help: library(vegan) data(varespec) data(varechem) vare.cca<-cca(varespec~ Al + P + K, varechem) With plot.cca() function I represented the species matrix in the next way: plot(vare.cca,display="species") Being similar to: plot((c(-2,2)),(c(-2,2)),

Estimados, Buenas Tardes, Estoy teniendo problema para testar la significancia de los ejes del RDA. NO se cual seria el error. Alguien me podría ayudar? Desde ya muchas gracias. Saludos, Luis # Tests of all canonical axes anova.cca(ssp.rda.hel, by="axis", step=1000)#Para saber la significancia de cada eje Error in anova.cca(ssp.rda.hel, by = "axis", step = 1000) :

Hello, I am interested in using the capscale function of vegan package of R. I already have a dissimilarity matrix and I am intended to use it as 'distance' argument. But then, I don't know what kind of data must be in 'comm' argument. I don't understand what type of data must be referred as 'species scores' and 'community data frame' since my data refer to

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

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 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 I tried decorana (I know it's been replaced by ca.)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

Hii rstudio members I am learning rstudio, For my manuscript I am trying to plot CCA using species and environmental data. But I am getting error like Error in cca.default(sptrans, envtrans) : all row sums must be >0 in the community data matrix *My code is like * library(vegan) library(ggplot2) library(dplyr) rassspec<-read.csv("C:/Users/hp/Desktop/R_data/rassspec.csv",

If you submit these lines, you end up with variable "vare.dis". I want to export vare.dis to csv. Stuck I am. library(vegan,logical.return = TRUE) #return=true verifies package is available library(MASS,logical.return=TRUE) #return=true verifies package is available data(varespec) #varespec is an example data file in the vegan package vare.dis <- vegdist(varespec)

Hi Listers, I am trying to reflect a PCA biplot in the x-axis (i.e. PC1) but am not having much success. In theory I believe all I need to do is multiply the site and species scores for the PC1 by -1, which would effectively flip the biplot. I am creating a blank plot using the plot command and accessing the results from a call to rda. I then use the calls to scores to obtain separate site and

Hello This is a simple question but I couldn't google an answer. In the procrustes function of the vegan package, one uses plot(procrustes_object, kind=2) to obtain a plot of the residual differences. For instance: data(varespec) vare.dist <- vegdist(wisconsin(varespec)) library(MASS) mds.null <- isoMDS(vare.dist, tol=1e-7) mds.alt <- isoMDS(vare.dist,

Hi All, I am using canonical correspondence analysis to compare a community composition matrix to a matrix of sample spatial relationships and environmental variables. In order to parse out how much variance is explained purely by space (S/E) or the environment (E/S) I am using a conditional (partial) CCA. I want to test significance via Monte Carlo but I can not find a way to do this with a

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

Dear List, I am writing a custom panel function and xyplot method to plot the results of a procrustes analysis from the vegan package. I am having trouble getting the call to panel.arrows to work as I wish when conditioning. The attached file contains the function definitions for the xyplot method and the custom panel and prepanel functions I am using. This example, using data and functions from

Dear List, I am trying to plot the result of cca using matplot but failed. Pls kindly help and thanks. Elaine The error message was error in xy.coords(x, y, xlabel, ylabel, log = log) : (list) object cannot be coerced to type 'double' code rm(list=ls()) library(vegan) library(MASS) # input richness birdrich

I've been unable to find a R package that provides the means of performing Clarke & Ainsworth's BIO-ENV procedure or something comparable. Briefly, they describe a method for comparing two separate sample ordinations, one from species data and the second from environmental data. The analysis includes selection of the 'best' subset of environmental variables for explaining

Hi, I?m doing cca for a community data set in R and I have made a biplot for my data. Otherwise everything seems to be allright but the biplot is so messy I can?t read it well enough or publish it. I would like to get the row numbers out of the plot: I want the species position and the environmental variables in it as vectors but not the station numbers. How do I get them out? I have a raw

Hi list, I am using the capscale function in vegan_2.0-7 to do a constrained principal coordinates analysis, and I kept getting the following error message: Error in Y.r[, oo, drop = FALSE] : subscript out of bounds I googled but I couldn't find an answer. Could anyone tell me why this error msg and what to do? Here is the command I used:

Hi All I am not clear quite how one could use cca from package vegan and the associated predict.cca to predict species abundance from environmental data (or if this is possible in a generalised way). In other words, can one derive a cca object based on known community data and use that to predict e.g. species abundances in a different number of samples based on environmental data? The help

Dear List, I am running constrained correspondence analysis for abundance data of 7 birds. However, I would like to check which bird prefers which environment gradient by showing the species with different colors of the dots in cca plot (package vegan). Please kindly help and thank you Elaine [[alternative HTML version deleted]]