similar to: Abundance data ordination in R

Hello. Does anyone know of an existing function that takes a list in the form of: Plot1 Species1 Abundance1 Plot1 Species2 Abundance2 Plot2 Species1 Abundance1 Plot2 Species3 Abundance3 . . . PlotN SpeciesN AbundanceN and translates into a matrix in the form of Species1 Species2.... SpeciesN Plot1 Abundance1 Abundance2... AbundanceN Plot2 Abundance1

Can anyone point me in the right direction of figuring out what downweight() is doing? I am using vegan to perform CCA on diatom assemblage data. I have a lot of rare species, so I want to reduce the influence of rare species in my CCA. I have read that some authors reduce rare species by only including species with an abundance of at least 1% in at least one sample (other authors use 5% as a

hello all R experts, how do I calculate the reliability between the two groups using the ICCs? I'll appreciate your reply, Thanks Sincerely, Supreet kaur, Biomedical research engineer, Nationwide Childrens Hospital, Columbus, OH (614)355-3509 [[alternative HTML version deleted]]

Dear list, I am trying to predict species volume from bioclimatic data, I have various sites and I have a data frame with species volume and the corresponding bioclimatic data for each site. I read on a discussion forum that you can use ordination to predict species abundance (in my case volume) from 'new' climate data for sites where you do not know the abundance. Unfortunately I

Hello I've been asked to help evaluate a vegetation data set, specifically to examine it for community similarity. The initial problem I see is that the data is ordinal. At best this only captures a relative ranking of abundance and ordinal ranks are assigned after data collection. I've been trying to find a procedure in R that can handle ordinal based classification and so far have

Hi, I am working with a species-by-trait .csv file (columns=traits, rows=species) and get the following warning message when trying to plot results of both metaMDS and pcoa:  "Warning message: In ordiplot(x, choices = choices, type = type, display = display,  :   Species scores not available" I am using a Gower's transformation in both procedures within the metaMDS or pcoa

I am trying to understand my population abundance data and am looking into analyses of change point to try and determine, at approximately what point do populations begin to change (either decline or increasing). Can anyone offer suggestions on ways to go about this? I have looked into bcp and strucchange packages but am not completely convinced that these are appropriate for my data. Here is

Hi! I wish to know if there is any R forum which is meant only for Statistics? I mean where we can clarify our statistics doubts and seek knowledge. I know there are lot many books and internet sites, but 'R forum' has altogether different standard and very high level and one can learn a lot from them. Regards Vincy [[alternative HTML version deleted]]

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

Hello, please excuse the simplicity of this question as I am not very good with stats. I am taking a class, using R which I am learning at the same time, and the questions asks us to "Estimate the average abundance using Poisson regression with a log link". I can estimate the abundance from "x", but I can seem to figure out how to get the average abundance in this method. Any

Hello, How can I randomly sample individuals within a sites from a site (row) X species abundance (column) data frame or matrix? As an example, the matrix "abund2" made below. ##### (sorry, Im a newbie and this is the only way I know to get an example on here) abund1 <- c(150, 300, 0, 360, 150, 300, 0, 240, 150, 0, 60, 0, 150, 0, 540, 0, 0, 300, 0, 240, 300, 300,

I am currently testing species co-occurrence patterns using null models and the oecosimu() function within the vegan() package. My issue is that none of the methods appear to be the ones that I want. The methods listed are r0, r1, r2, r2dtable, swap, tswap. However, I want to know how to go about implementing fixed row algorithms, as suggested in Gotelli 2000 in Ecology. Also, the null models

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

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

Dear All, I am using a Procrustes analysis to compare two NMDS ordinations for the same set of sites. One ordination is based on fish data, the other is based on invertebrate data. Ordinations were derived using metaMDS() from the {vegan} library as follows: fish.mds<-metaMDS(fish.data, distance="bray", k=3, trymax=100, wascores=TRUE, trace=TRUE, zero="add")

Hello, R-Help - I am trying to plot the results of an ordination from package vegan. The tricky part for me right now is getting the colors of the ellipses denoting the 95% confidence intervals of the group centroids to match the colors of the points for those same groups. >From and earlier post, I saw the code to make a plot of the ordination using different colors for my different groups.

Hi, I could use a hand solving a fairly straightforward ordination plot problem: I am conducing NMDS on some community data for roughly 300 localities and 650 species. I have a community matrix, a species attribute matrix, and an environmental attributes matrix. After running metaMDS {vegan} on the community matrix, I can successfully use either of the other two matrices to draw hulls around

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

I have a general question about using thin plate splines in the surf and ordisurf routines. My rudimentary knowledge of a gam is that with each predictive variable there is a different smooth for each one and then they are added together with no real interaction term (because they don't handle this well?). Now, If I have two variables that have a high D^2 score and a low GCV score (I am

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