randAssort: Random Assortment Model

In MarioJose/nicheApport: Tokeshi's Niche Apportionment Species Abundance Distributions Models

Description

Simulate ranked abundance distribution for Random Assortment model. Each fraction size is independent of others fractions, resulting in a random collection of arbitrary fractions sizes. If niches are ordered in rank from largest to the smallest, each rank is more abundant that next one. Then, if the first rank takes value 1, the second rank takes any value less than the first, the thirty takes any value less then the second and so on until all species has a fraction of niche.

Usage

  randAssort(N, S, count = FALSE)

Arguments

N	Total abundance. See 'Details' for more information.
S	Number of species.
count	Define if measure of abundance is number of individuals. See 'Details' for more information.

Details

Abundance is a measure of the amount of each species and can be represented by number of individuals or biomass, dry weight or cover (Pielou 1975). If the argument count is TRUE, than each specie will have amount of individual in accordance with model rules. Note that some species may have zero individual if model rules result in hight dominance. But, since that premise of Random Assortment is that each specie has independent abundance, than each specie will have at least one individual. If count is FALSE (default), than each species will have a fraction of total abundance. The values randomly generated to represent amount of niche to be divided follow uniform distribution. All the fraction totalize more than 1, like described in 'Description' section. Thus, relative abundance is calculated and multiplied to total abundance informed to result a correct abundance for each rank.

Value

A vector of ranked species abundance from the most abundant (rank 1) to the least abundant (rank S).

Author(s)

Mario J. Marques-Azevedo

Maintainer: Mario J. Marques-Azevedo <[e-mail]>

References

Pielou, E. C. 1975. Ecological diversity. Wiley, New York.

Tokeshi, M. 1990. Niche apportionment or random assortment: species abundance patterns revisited. J. Anim. Ecol. 59: 1129-1146.

See Also

For others models see dominanceDecay, dominancePreemp, MacArthurFraction, randFraction and powerFraction.

For fit models see fitmodel and fitmodelCl to fit using parellel computation. To find best w parameter to powerFraction see findPFw.

Examples

  set.seed(42)
  randAssort(100, 10)

MarioJose/nicheApport documentation built on May 7, 2019, 2:52 p.m.