prepNulls: Prep data for null randomizations
In metricTester: Test Metric and Null Model Statistical Performance

Description Usage Arguments Details Value References Examples

Given a phylo object, a picante-style community data matrix (sites are rows, species are columns), and an optional vector of regional abundance, prepare data for randomizations.

1 2	prepNulls(tree, picante.cdm, regional.abundance = NULL, distances.among = NULL)

`tree`	Phylo object
`picante.cdm`	A picante-style community data matrix with sites as rows, and species as columns
`regional.abundance`	A character vector in the form "s1, s1, s1, s2, s2, s3, etc". Optional, will be generated from the input CDM if not provided.
`distances.among`	An optional symmetric distance matrix describing the distances among plots/etc, for use with null models like the dispersal null.

Returns a named list with four elements: the original phylogenetic tree, the original picante-style CDM, a spacodi-style CDM, and vector of regional abundance.

A list of class nulls.input

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

#simulate tree with birth-death process
tree <- geiger::sim.bdtree(b=0.1, d=0, stop="taxa", n=50)

sim.abundances <- round(rlnorm(5000, meanlog=2, sdlog=1)) + 1

cdm <- simulateComm(tree, richness.vector=10:25, abundances=sim.abundances)

prepped <- prepNulls(tree, cdm)