metricTester (version 1.3.6)

multiCDM: Wrapper for deriving CDMs from the results of multiple spatial simulations

Description

Given the results of a call to runSimulations(), this function places plots down randomly (though identically across simulations).

Usage

multiCDM(simulations.result, no.plots, plot.length)

Arguments

simulations.result

List of data frames of three columns: "individuals", "X", and "Y"

no.plots

Number of plots to place

plot.length

Length of one side of desired plot

Value

A list of data frames.

Details

Both the size and number of plots are determined by the user. A conservative check (perhaps overly so) is in place to ensure the function doesn't get stuck looking for solutions for how to randomly place non-overlapping plots. Either decreasing the number or size of plots is necessary if this throws an error.

References

Miller, E. T., D. R. Farine, and C. H. Trisos. 2016. Phylogenetic community structure metrics and null models: a review with new methods and software. Ecography DOI: 10.1111/ecog.02070

Examples

# NOT RUN {
#simulate tree with birth-death process
tree <- geiger::sim.bdtree(b=0.1, d=0, stop="taxa", n=50)

prepped <- prepSimulations(tree, arena.length=300, mean.log.individuals=2,
	length.parameter=1000, sd.parameter=50, max.distance=20, proportion.killed=0.2,
competition.iterations=5)

#run the spatial simulations
arenas <- runSimulations(prepped)

#derive CDMs. plots are placed in the same places across all spatial simulations.
#density of individuals per arena is low enough in this example that sometimes all
#plots contain < 2 species, and are cut, causing an error. this not run so as not to
#throw errors on CRAN
#cdms <- multiCDM(arenas, no.plots=10, plot.length=20)
# }