#' Standardized effect size of inter-community MPD (betaMPD, betaNRI)
#'
#' Standardized effect size of MPD (mean pairwise distance) separating taxa in two communities, a measure of phylogenetic beta diversity
#' @param samp Community data matrix with samples as rows
#' @param dis Distance matrix (generally a phylogenetic distance matrix)
#' @param null.model Null model to use (see Details section for description)
#' @param abundance.weighted Should mean nearest taxon distances for each species be weighted by species abundance? (default = FALSE)
#' @param runs Number of randomizations
#' @param iterations Number of iterations to use for each randomization (for independent swap and trial null models)
#' @param cores Number of cores to use for parallel computing
#' @details Currently implemented null models (arguments to null.model):
#' \itemize{
#' \item taxa.labels - Shuffle distance matrix labels (across all taxa included in distance matrix)
#' \item richness - Randomize community data matrix abundances within samples (maintains sample species richness)
#' \item frequency - Randomize community data matrix abundances within species (maintains species occurence frequency)
#' \item sample.pool - Randomize community data matrix by drawing species from pool of species occurring in at least one community (sample pool) with equal probability
#' \item phylogeny.pool- Randomize community data matrix by drawing species from pool of species occurring in the distance matrix (phylogeny pool) with equal probability
#' \item independentswap - Randomize community data matrix with the independent swap algorithm (Gotelli 2000) maintaining species occurrence frequency and sample species richness
#' \item trialswap - Randomize community data matrix with the trial-swap algorithm (Miklos & Podani 2004) maintaining species occurrence frequency and sample species richness
#' }
#' @keywords ses MPD bMPD bNRI betaMPD betaNRI
#' @return A list of results:
#' \itemize{
#' \item ntaxa - Number of taxa in community
#' \item comdist.obs - Observed mpd between communities
#' \item comdist.rand.mean - Mean mpd between null communities
#' \item comdist.rand.sd - Standard deviation of mpd between null communities
#' \item comdist.obs.rank - Rank of observed mpd vs. null mpd
#' \item comdist.obs.z - Standardized effect size of mpd vs. null mpd (= (comdist.obs - comdist.rand.mean) / comdist.rand.sd, equivalent to -betaNRI)
#' \item comdist.obs.p - P-value (quantile) of observed mpd vs. null communities (= comdist.obs.rank / runs + 1)
#' \item runs - Number of randomizations
#' }
#' @import picante
#' @export
ses.comdist <- function (samp, dis, null.model = c("taxa.labels", "richness",
"frequency", "sample.pool", "phylogeny.pool", "independentswap",
"trialswap"), abundance.weighted = FALSE, runs = 999, iterations = 1000, cores = 1){
dis <- as.matrix(dis)
comdist.obs <- as.matrix(comdist.par(samp, dis, abundance.weighted = abundance.weighted, cores = cores, progress = FALSE))
null.model <- match.arg(null.model)
comdist.rand <- switch(null.model,
taxa.labels = replicate(runs, as.matrix(comdist.par(samp, taxaShuffle(dis), abundance.weighted, cores = cores, progress = FALSE)), simplify = FALSE),
richness = replicate(runs, as.matrix(comdist.par(randomizeMatrix(samp,
null.model = "richness"), dis, abundance.weighted, cores = cores, progress = FALSE)), simplify = FALSE),
frequency = replicate(runs, as.matrix(comdist.par(randomizeMatrix(samp,
null.model = "frequency"), dis, abundance.weighted, cores = cores, progress = FALSE)), simplify = FALSE),
sample.pool = replicate(runs, as.matrix(comdist.par(randomizeMatrix(samp,
null.model = "richness"), dis, abundance.weighted, cores = cores, progress = FALSE)), simplify = FALSE),
phylogeny.pool = replicate(runs, as.matrix(comdist.par(randomizeMatrix(samp,
null.model = "richness"), taxaShuffle(dis), abundance.weighted, cores = cores, progress = FALSE)), simplify = FALSE),
independentswap = replicate(runs, as.matrix(comdist.par(randomizeMatrix(samp,
null.model = "independentswap", iterations), dis, abundance.weighted, cores = cores, progress = FALSE)), simplify = FALSE),
trialswap = replicate(runs,as.matrix(comdist.par(randomizeMatrix(samp,
null.model = "trialswap", iterations), dis, abundance.weighted, cores = cores, progress = FALSE)), simplify = FALSE))
comdist.rand.mean <- apply(X = simplify2array(comdist.rand), MARGIN = 1:2, FUN = mean, na.rm = TRUE)
comdist.rand.sd <- apply(X = simplify2array(comdist.rand), MARGIN = 1:2, FUN = sd, na.rm = TRUE)
comdist.obs.z <- (comdist.obs - comdist.rand.mean)/comdist.rand.sd
comdist.obs.rank <- apply(X = simplify2array(c(list(comdist.obs),comdist.rand)), MARGIN = 1:2, FUN = rank)[1,,]
comdist.obs.rank <- ifelse(is.na(comdist.rand.mean), NA, comdist.obs.rank)
diag(comdist.obs.rank) <- NA
comdist.obs.p <- comdist.obs.rank/(runs + 1)
list(ntaxa = specnumber(samp), comdist.obs = comdist.obs, comdist.rand.mean = comdist.rand.mean,
comdist.rand.sd = comdist.rand.sd, comdist.obs.rank = comdist.obs.rank, comdist.obs.z = comdist.obs.z, comdist.obs.p = comdist.obs.p, runs = runs)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.