metricTester (version 1.2.2)

multiLinker: Run multiple simulations and calculations to test metric + null performance

Description

This function runs multiple iterations of the linker function, saving results to file.

Usage

multiLinker(no.taxa, arena.length, mean.log.individuals, length.parameter, sd.parameter, max.distance, proportion.killed, competition.iterations, no.plots, plot.length, concat.by, randomizations, cores, iterations, prefix, simulations, nulls, metrics)

Arguments

no.taxa

The desired number of species in the input phylogeny

arena.length

A numeric, specifying the length of a single side of the arena

mean.log.individuals

Mean log of abundance vector from which species abundances will be drawn

length.parameter

Length of vector from which species' locations are drawn. Large values of this parameter dramatically decrease the speed of the function but result in nicer looking communities

sd.parameter

Standard deviation of vector from which species' locations are drawn

max.distance

The geographic distance within which neighboring indivduals should be considered to influence the individual in question

proportion.killed

The percent of individuals in the total arena that should be considered (as a proportion, e.g. 0.5 = half)

competition.iterations

Number of generations over which to run competition simulations

no.plots

Number of plots to place

plot.length

Length of one side of desired plot

concat.by

Whether to concatenate the randomizations by richness, plot or both

randomizations

The number of randomized CDMs, per null, to generate. These are used to compare the significance of the observed metric scores.

cores

The number of cores to be used for parallel processing.

iterations

The number of complete tests to be run. For instance, 1 iteration would be considered a complete cycle of running all spatial simulations, randomly placing plots in the arenas, sampling the contents, creating a community data matrix, calculating observed metric scores, then comparing these to the specified number of randomizations of the original CDMs.

prefix

Optional character vector to affix to the output RData file names, e.g. "test1".

simulations

Optional list of named spatial simulation functions to use. These must be defined in the defineSimulations function. If invoked, this option will likely be used to run a subset of the defined spatial simulations.

nulls

Optional list of named null model functions to use. If invoked, this option will likely be used to run a subset of the defined null models.

metrics

Optional list of named metric functions to use. If invoked, this option will likely be used to run a subset of the defined metrics.

Value

A list of lists of data frames. The first level of the output has one element for each simulation. The second level has one element for each null model. Each of these elements is a list of two data frames, one that summarizes the plot-level significance and another and arena-level significance.

Details

This function wraps a number of other wrapper functions into one big metric + null performance tester function. Unlike the basic linker function, multiple tests can be run, with results saved as RDS files.

References

Miller, E. T., D. R. Farine, and C. H. Trisos. 2015. Phylogenetic community structure metrics and null models: a review with new methods and software. bioRxiv 025726.

Examples

#not run
#system.time(multiLinker(no.taxa=50, arena.length=300, mean.log.individuals=3.2, 
	#length.parameter=5000, sd.parameter=50, max.distance=20, proportion.killed=0.3, 
#competition.iterations=2, no.plots=20, plot.length=30, concat.by="richness", 
#randomizations=3, cores="seq", iterations=2, prefix="test",
#nulls=list("richness"=metricTester:::my_richnessNull,
#"frequency"=metricTester:::my_frequency)))