Description Usage Arguments Details Value Author(s) References See Also Examples

Simulate ranked abundance distribution for Dominance Preemption model. The total niche is sequential divided, always with amount between 0.5 and 1, and smaller fraction is always selected to be divided. First, total niche is divided, with amount between 0.5 and 1, in two fraction. Then, the smallest of this two fraction is selected and divided again in two fraction (with amount between 0.5 and 1). The smallest of this three fraction is selected and divided again in two fraction. This procedures is repeated until all species has a fraction of total niche. This model result in abundance distribution with hight dominance.

1 | ```
dominancePreemp(N, S, count = FALSE)
``` |

`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. |

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`

, then 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. If `count`

is `FALSE`

(default), then each species will have a fraction of total abundance. The values randomly generated to represent amount of niche to be divided follow uniform distribution. In `dominancePreemp`

this randomly values are always between 0.5 and 1.

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

).

Mario J. Marques-Azevedo

Maintainer: Mario J. Marques-Azevedo <[email protected]>

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.

For others models see `dominanceDecay`

, `MacArthurFraction`

, `randFraction`

, `randAssort`

and `powerFraction`

.

For fit models see `fitmodel`

and `fitmodelCl`

to fit using parellel computation. To find best `w`

parameter to `powerFraction`

see `findPFw`

.

1 2 | ```
set.seed(42)
dominancePreemp(100, 10)
``` |

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

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