similar to: Find pattern in matrix

Dear List, I have a 47 species * 83 samples matrix containing percentage abundance data. I have two cluster analyses one of the samples and one of the species, and have ordered the rows and columns of the species by samples matrix according to these two cluster analyses. So far so good! Now what I want to do is create a plot with the species dendrogram at the top of the plot, the samples

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

Dear, I would like to post the following question to the r-help on Nabble (thanks in advance for the attention, Gustavo Vieira): Hi there. I have a data set on hands with 5,220 cases and I'd like to automate some procedures (but I have almost no programming knowledge). The data has some continuous variables that are grouped by 2 others: the name of species and the locality where they were

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

Hi, I am doing canonical discriminant analysis using candisc function from the candisc package. My input is a table of species distribution (columns = abundance of each species in each sample) in samples that are split by categories (rows), and I want to know whether each category is associated with a particular set of species and their abundances. I have 20 rows (samples) split into 6

Dear Lists, At several stations distributed regularly in space[1], we sampled repeatedly (4 times) the abundance of organisms and measured environmental parameters. I now want to compare the spatial distribution of various species (and test wether they differ or not), or to compare the distribution of a particular organism with the distribution of some environmental variable.

Hi there, I'm using the lattice package to create an xy plot of abundance vs. depth for 5 stages of barnacle larvae from 5 species. Each panel of the plot represents a different stage, while different loess smoothers within each panel should represent different species. However, I would like depth to be on the y-axis and abundance to be on the x-axis, because this is more intuitive as an

Hi again all, Several replied ASAP that I also needed reshape loaded and not just reshape2. Hmmm tried that and I had some output but not the correct format. What I need is to run simulations of time overlap between species as per the simulation program data input constraints: The basis for the simulations is a species by _time-use matrix in which species are arranged in rows, and time

Greetings, I am new to R and am hoping to get some tips from experienced R-programmers. I have a dataset that I've read into R as a dataframe. There are 5 columns: Plot location,species name, a species number code (unique to each species name), abundance, and treatment. There are 272 plots in each treatment, but only the plots in which the species was recorded have an abundance value. For

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,

Hi fellow R users, I have a dataset that looks something like this. species class abundance K 1 592 K 2 288 G 1 254 G 2 239 C 2 173 D 2 123 E 3 89 F 2 87 B 2 86 H 2 82 I 1 79 J 2 76 B 1 73 D 3 72 A 2 62 L 2 58 I want to plot a stacked barchart. species is the x-axis, abundance is y-axis, and class will appear as the stacks in different colours. I need the species to be displayed in descending

The background: I'm trying to fit a Poisson-lognormal distrbutuion to some data. This is a way of modelling species abundances: N ~ Pois(lam) log(lam) ~ N(mu, sigma2) The number of individuals are Poisson distributed with an abundance drawn from a log-normal distrbution. To fit this to data, I need to integrate out lam. In principle, I can do it this way: PLN1 <- function(lam, Count,

Hi R community, I am trying to obtain a sample from a matrix but sample(my.matrix) doesn't do what I need. I have a matrix of 1287 interactions between the species in columns and the species in rows and I want to obtain a smaller matrix with say, 800 interactions, that may or may not have the same number of columns and/or rows (i.e., some interactions may not be retrieved in a smaller sample).

Hi, I am a new R user and am trying to construct a palaeoenvironmental transfer function (weighted averaging method) using the package rioja. I've managed to insert the two matrices (the species abundance and the environmental data) and have assigned them to the y and x values respectively. When I try and enter the 'WA' function though, I get an 'Error in FUN' message (see

I hope you can help with this one. I have two matricies: 1. A species abundance matrix: <http://r.789695.n4.nabble.com/file/n4643979/2species_matrix.jpg> 2. A species trait score matrix: <http://r.789695.n4.nabble.com/file/n4643979/2trait_matrix.jpg> The trait matrix lists trait scores for each species as listed in the species abundance matrix. I would like to create a script

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Dear List, I have a data set stored in the following format: > head(dat, n = 10) id sppcode abundance 1 10307 10000000 1 2 10307 16220602 2 3 10307 20000000 5 4 10307 20110000 2 5 10307 24000000 1 6 10307 40210000 83 7 10307 40210102 45 8 10307 45140000 1 9 10307 45630000 1 10 10307 45630600 41 >

I've written a function that regularly throws the "cannot allocate vector of size X Kb" error, since it contains a loop that creates large numbers of big distance matrices. I'd be very grateful for any simple advice on how to reduce the memory demands of my function. Besides increasing memory.size to the maximum available, I've tried reducing my "dist" objects to 3

Apologies for the empty email earlier! I have species abundance data sampled at a weekly frequency or sometimes monthly depending on the year. The goal is to identify the dates in an annual cycle in which the cumulative abundance of a species reaches some threshold. Here's an example of the data for 1 species over an annual period: "mc_pheno" is the object created from this data:

Hi all I have been trying to use the randomForest package to model insect species abundance in different habitats and identify the key variables (landscape/climate etc) in determining abundance, which has all worked fine and I get nice variable importance plots etc. Many thanks to everyone on this help forum who has given tips/advice along the way. But the percentage variance explained /pseudo r