similar to: vegan CCA I am Completely new to ordination analyses

Dear all, I am a new member to the list - and to the analysis that I am attempting. I have the following case A group of us have been monitoring (over a period of a few years) a number of paired plots that were flooded and / or burnt. The plots are located in two topographical settings, some were burnt, some were flooded, some were burnt & flooded and some were not affected at all. At

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)

Hello Sir I am getting problem in plotting in CCA . Could you please help me? I wrote the below command but I don't know why it is taking only first 5 env data rather than all 9. > strain.data <- read.xlsx("Dee rhiz.xlsx", sheetName="strain", header = T, row.names = 1) > env.data <- read.xlsx("Dee rhiz.xlsx", sheetName="env", header = T,

We need to keep the discussion on the list. When I run your code, there are several problems. strain.data <- read.xlsx("Dee rhiz.xlsx", sheetName ="strain", header = T, row.names = 1) str(strain.data) # lists 9 columns at the end with all NAs strain.data1 <- (strain.data, sqrt.dist = TRUE) # this is not a valid R line. I get Error: unexpected ',' in

Hello, I am trying to cycle through a csv and make some summary statistics. I need to select rows based on the number in the row name that comes after the letter 'y'. For example, ? BA1y1 would equal 1, ?C3A2r3y1 would equal 1 and ?MA3r3y1r3 would equal 1. I currently have my code ?cycling through by the 5th character but my rows have variable length and the y can occur in several

I'd appreciate advice on the following: I've written an R function that uses 3 vectors (temperature, precipitation and potential evapotranspiration) for a given site, calculates a water budget (which implies few (<4) iterations), and, from thresults of this water budget, calculates a number of bioclimatic indices. Now I want to calculate these indices for a large number of sites

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 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

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 all, How can I run a constrained correspondence analysis with the following data: 15 animals were measured repeatedly month-wise (over to 2 years) according to ther diet composition (8 food categories). our data.frame looks like this: food 1 2 ... 8 sex season year animal freq 12 8 ... 1 0 summer 2011 1 freq 0 7 ... 0 1 winter 2011 1 ... freq 0 7 ... 0 1 spring 2011 15 We

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)

Hi, I have a couple questions about fitting environmental (land use factors, plant species presence-absence, and soil variables) constraints to my CCA biplot. 1. After successfully plotting species and site scores in my CCA, I have been trying to insert the biplot arrows of the environmental constraints in my data set using the text() function. When I do that, the plot changes completely. Is there

Dear List, I tried to conduct cca using csv data but failed. The message said that data.frame is required. Please kindly share how to convert a csv-imported file to a data.frame. Thank you. Elaine code rm(list=ls()) spec <-read.csv("c:/migration/M_R_20100718_winterM_spec_vegan.csv",header=T, row.names=1) dim(spec) spec[1,] envi

Dear R community, I'm working with PCA and CCA methods, and I have a theoretical question. Why is it necesary to have more temporal values than variables when the CCA O PCA are going to be used? Could you advise to me some any paper about it? Thanks in advance, [[alternative HTML version deleted]]

Dear List, I used spec and envi for cca in ade4. (both are data.frame) However, there is a message telling that error in if (nf > rank) nf <- rank R missing value in TRUE/FALSE Please kindly help how to modify the code below. Thank you. Elaine code rm(list=ls()) spec <-read.csv("c:/migration/M_R_20100718_winterM_spec_vegan.csv",header=T, row.names=1) dim(spec) spec[1,]

Hello I am using Jari Oksanen's CCA routine from the Vegan package on some estuary data, following a technique applied in (Anderson, M.J. & Gribble, N.A., 1998, Partitioning the variation among spatial, temporal and environmental components in a multivariate data set, Australian Journal of Ecology 23, 158-167). Some steps in the process require that the dependent matrix be constrained by

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)),

Hello all, I'm hoping this is a simple problem. I'm trying to do cca of my data. I have my plant data and environmental data as 2 separate files. I have 3 years of data, stacked vertically, within these files. I want to conduct the cca for each year and am trying to create separate year files using the following: cnts94 <- cnts[1:27,] env94 <- env[1:27,] when I run

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.

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