mixture {BAT}

Mixture model.

Description

Mixture model by Hilario et al. subm.

Usage

mixture(
  comm,
  tree,
  q = 0,
  precision = 0.1,
  replace = TRUE,
  alpha = 0.05,
  param = TRUE,
  runs = 1000
)

Arguments

comm

A sites x species matrix, with abundance data.

tree

A phylo or hclust object (used only for PD or FD) or alternatively a species x traits matrix or data.frame to build a functional tree. Will only be used if q = 0, in which case phylogenetic or functional richness are calculated instead of species richness.

q

Hill number order: q(0) = species richness, q(1) ~ Shannon diversity, q(2) ~ Simpson diversity.

precision

Precision of the proportion of each habitat type to be tested.

replace

Boolean indicating whether simulations should be with or without (default) replacement.

alpha

alpha value for significance level.

param

Value is calculated with parametric or non-parametric method. The later is preferable when distribution of estimated values is not normally distributed.

runs

Number of runs for the bootstrap providing confidence limits.

Details

A tool to assess biodiversity in landscapes containing varying proportions of n environments.

Value

A matrix with expected diversity at each proportion of different habitats in a landscape.

Author(s)

Renato Hilario & Pedro Cardoso

References

Chao et al. (2019) Proportional mixture of two rarefaction/extrapolation curves to forecast biodiversity changes under landscape transformation. Ecology Letters, 22: 1913-1922. https://doi.org/10.1111/ele.13322

Hilario et al. (subm.) Function ‘mixture’: A new tool to quantify biodiversity change under landscape transformation.

Examples

comm <- matrix(c(20,20,20,20,20,9,1,0,0,0,1,1,1,1,1), nrow = 3, ncol = 5, byrow = TRUE)
tree = hclust(dist(1:5))

hill(comm)
alpha(comm, tree)

mixture(comm, runs = 10)
mixture(comm, tree, replace = TRUE, runs = 10)