entropart (version 1.4-6)

MetaCommunity: Metacommunity class

Description

Methods for objects of type "MetaCommunity".

Usage

MetaCommunity(Abundances, Weights = rep(1, ncol(Abundances)))
is.MetaCommunity(x)
"summary"(object, ...)
"plot"(x, ...)

Arguments

Abundances

A dataframe containing the number of observations (lines are species, columns are communities). The first column of the dataframe may contain the species names.

Weights

A vector of positive numbers equal to community weights or a dataframe containing a vector named Weights. It does not have to be normalized. Weights are equal by default.

x

An object to be tested or plotted.

object

A MetaCommunity object to be summarized.

...

Additional arguments to be passed to the generic methods.

Value

An object of class MetaCommunity is a list:is.MetaCommunity returns TRUE if the object is of class MetaCommunity.summary.MetaCommunity returns a summary of the object's value.plot.MetaCommunity plots it.

Details

In the entropart package, individuals of different "species" are counted in several "communities" which are agregated to define a "metacommunity". This is a naming convention, which may correspond to plots in a forest inventory or any data organized the same way. Alpha and beta entropies of communities are summed according to Weights and the probability to find a species in the metacommunity is the weighted average of probabilities in communities. The simplest way to import data is to organize it into two text files. The first file should contain abundance data: the first column named Species for species names, and a column for each community.

Species	NameOfCommunity1
NameOfCommunity2	NameOfSpecies1
1	5
NameOfSpecies2	4
2	Species

The second file should contain the community weights and be organized as follows:

Communities

Weights

NameOfCommunity1

3

Files can be read and data imported by code such as:

  Abundances <- read.csv(file="Abundances.csv", row.names = 1)
  Weights <- read.csv(file="Weights.csv")
  MC <- MetaCommunity(Abundances, Weights)
  

The number of individuals of the meta-community $N is not explicitly specified. It is calculated as the number of individuals of the lower-weighted community divided by its weight. For example, if the community with the smallest weight (5%) contains 100 individuals, the total number of individuals is set to 2000. The number of individuals per species of the meta-community $Ns is the product of $N and $Ps. In the special case where weights are proportional to the number of individuals of communities, the resulting number of individuals of the meta-community is simply the sum of the number of individuals of communities. In other cases, the numbers of individuals of the meta-community may not be integers. This does not appear to be a problem.

Examples

  # Use BCI data from vegan package
  if (require(vegan, quietly = TRUE)) {
    # Load BCI data (number of trees per species in each 1-ha plot of a tropical forest)
    data(BCI)
    # BCI dataframe must be transposed (its lines are plots, not species)
    BCI.df <- as.data.frame(t(BCI))
    # Create a metacommunity object from a matrix of abundances and a vector of weights
    # (here, all plots have a weight equal to 1)
    MC <- MetaCommunity(BCI.df)
  }