FD (version 1.0-12)

simul.dbFD: Simulations to Explore Relationships Between Functional Diversity Indices

Description

simul.dbFD generates artificial communities of species with artificial functional traits. Different functional diversity (FD) indices are computed from these communities using dbFD to explore their inter-relationships.

Usage

simul.dbFD(s = c(5, 10, 15, 20, 25, 30, 35, 40), t = 3, 
          r = 10, p = 100, tr.method = c("unif", "norm", "lnorm"),
          abun.method = c("lnorm", "norm", "unif"), w.abun = TRUE)

Arguments

s

vector listing the different levels of species richness used in the simulations

t

number of traits

r

number of replicates per species richness level

p

number of species in the common species pool

tr.method

character string indicating the sampling distribution for the traits. "unif" is a uniform distribution, "norm" is a normal distribution, and "lnorm" is a lognormal distribution.

abun.method

character string indicating the sampling distribution for the species abundances. Same as for tr.method.

w.abun

logical; should FDis, FEve, FDiv, and Rao's quadratic entropy (Q) be weighted by species abundances?

Value

A list contaning the following elements:

results

data frame containing the results of the simulations

traits

matrix containing the traits

abun

matrix containing the abundances

abun.gamma

species abundances from the pooled set of communities

FDis.gamma

FDis of the pooled set of communities

FDis.mean

mean FDis from all communities

FDis.gamma and FDis.mean can be used to explore the set concavity criterion (Ricotta 2005) for FDis.

A graph plotting the results of the simulations is also returned.

Warning

The simulations performed by simul.dbFD can take several hours if length(s) and/or r is large. Run a test with the default parameters first.

References

Lalibert<e9>, E. and P. Legendre (2010) A distance-based framework for measuring functional diversity from multiple traits. Ecology 91299:305.

Ricotta, C. (2005) A note on functional diversity measures. Basic and Applied Ecology 6:479-486.

See Also

dbFD, the function called in simul.dbFD

Examples

# NOT RUN {
# this should take just a few minutes
# }
# NOT RUN {
ex1 <- simul.dbFD(s = c(10, 20, 30, 40, 50), r = 5)
ex1
# }