similar to: Vegan: Anova.CCA accessing original data using option by="margin"

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

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, 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,

I am trying to use the cca/rda/capscale functions in vegan to analyse genetic distance data ( provided as a dist object calculated using dist.genpop in package adegenet) with geographic distance partialled out ( provided as a distance object using dist function in veganthis method is attempting to follow the method used by Geffen et al 2004 as suggested by Legendre and . FORTIN (2010). I

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

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

Dear List, I tried to do cca based on species data and environmental variables (formula instead of community data). However, there was an error saying row sums must be >0. I searched the previous related messages but found few solutions. Please kindly help and thank you in advance. code This is vegan 1.17-3 Warning message: package 'vegan' was built under R version 2.10.1

Hi, I've just started using R and am having some problems with CCA using vegan. I'm looking at abundance p/m2 (hence decimals) vs environmental variables and have been using http://ecology.msu.montana.edu/labdsv/R/labs/lab12/lab12.html to guide me through. My organism data looks like this: Sample "Species_1" "Species_2" "Species_3" etc Sample_1

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

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

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 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

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)),

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, 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.

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 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)

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, 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

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",