Generate regional abundance vector
Calculate alpha metrics under specified tree and community parameters
Calculate functional dispersion (FDis)
Calculate mean root distance
Parallelized function that calculates beta metrics on randomized matrices
Calculate beta metrics under specified tree and community parameters
Calculate phylogenetic and trait fields
Read in and calculate type I and II error rates of a set of beta metric tests
Run spatial simulations, null and beta metric calculations
Wrapper for summarizing error rates of beta metric randomizations
Calculate phylogenetic community structure metrics
Calculate SES of each observed metric + null model combination
Run multiple simulations and calculations to test beta metric + null performance
Calculate phylogenetic community structure beta metrics
Calculate plot-level distances to most recent common ancestors
Calculate weighted centroids
Wrapper for summarizing randomizations and testing significance of observed metrics
Confirm that a CDM will run
Confirm that the metric functions are in suitable format
Confirm that the spatial simulation functions are in suitable format
Run spatial simulations, null and metric calculations to test metric + null performance
Confirm that the metric functions are in suitable format
Confirm that the null model functions are in suitable format
Randomize community data matrix with dispersal null model
Output all spatial simulations as a list of named functions
Simulate competitive exclusion over multiple generations
Evolve two traits up a tree
Generate expectations for null+metric combinations
Wrapper for creating a CDM from a spatial simulation result
Output all beta metrics as a list of named functions
Wrapper for prepping and calculating observed beta metrics
Parallelized function that calculates metrics on randomized matrices
Calculate different versions of abundance-weighted MPD
Remove most closely related individuals for large arenas
Randomize community data matrix with regional null model
Output all null models as a list of named functions
Summarize metric performance of a series of summarized simulation results
Output all metrics as a list of named functions
Create a road map for use in FDis-related functions
Calculate a species' phylogenetic field
Randomize community data matrix with second-gen regional null model
Run defined spatial simulations
Prep data to to calculate phylogenetic fields
Summarize null model performance of a series of summarized simulation results
Calculate the species richness of a vector from a CDM
Calculate a species' standardized trait field
Prep data for null randomizations
Prep data for spatial simulations
Identify individuals contained within a plot
Simulate a community assembled according to habitat filtering
Randomly settle individuals in a spatial arena
Plot simulated plots in arena
Randomly place plots in arena
Wrapper for prepping and calculating observed metrics
Overall per simulation-null-metric plot test
Calculate corrected PSC
Generate a simulated community data matrix
Convert absolute abundance matrix to relative abundance
Calculate a species' standardized trait field
Create synthetic community niche space
Calculate a species' trait field
Calculate a species' standardized trait field
Generate a random spatial arena
Remove most closely related individuals
Randomize input CDM according to defined null models
Wrapper for deriving CDMs from the results of multiple spatial simulations
Read in the results of multiple metric/null/simulation tests
Return summary statistics from a data frame of randomized metric values
Summarize correlations among metrics over a result from a varyX function
Summary statistics of SES results
Run multiple simulations and calculations to test metric + null performance
Calculate if single, observed metrics deviate beyond expectations
Prep data to test phylogenetic community structure metrics
Reduce randomized results to a manageable list of dataframes
Reduce results from multiLinker into a manageable format
Overall per simulation-null-metric SES test
Create landscapes with varying degrees of heterogeneity
Calculate alpha or beta metrics across a set of parameters