betasim: Simulate communities with specified diversity characteristics

In bbolker/betararef: Beta Diversity with Rarefaction

Description

Simulate communities with specified diversity characteristics

Usage

betasim(n.abund = 5, p.abund = 0.5, diff.abund = NULL, spcat = 2,
  totsp = 30, n.site = 3, n.indiv.site = 100, n.indiv.tot = NULL,
  p.mix = rep(0, n.abund), seed = NULL, rand = c("none", "multinom",
  "poisson", "trpoisson"), rarefy = 1, pred.spec = c("none", "focal",
  "abund"), pred.rand = c("binom", "none"), pred.gamma = -Inf,
  pred.alpha = 0, pred.gamma.sd = 0, no.zero.patch = TRUE)

Arguments

n.abund	number of abundance categories
p.abund	relative ranking of subsequent abundance categories
diff.abund	alternative parameterization: difference between most and least abundant category
spcat	number of species per abundance category PER SITE (overdetermined)
totsp	total species pool size (FIXME)
n.site	number of sites
n.indiv.site	individuals per site
n.indiv.tot	total number of individuals
p.mix	mixing parameter: probability of among-site mixing for each abundance category: 0=endemic, 1=homogeneous
seed	random number seed
rand	randomization type: 'none' to keep numbers==expected numbers; 'multinom' for fixed total per site; 'poisson' for Poisson sampling, 'trpoisson' for truncated Poisson sampling
rarefy	degree of rarefaction (1=none)
pred.spec	predator specification (stub?)
pred.rand	predator randomness
pred.gamma	predation intensity (-Inf==none)
pred.alpha	predator preference parameter; if pred.spec=="abund" 0=neutral, -1=pref. rare, +1=pref. common; if pred.spec=="focal" 0=neutral, -1=pref non-endemic, +1=pref endemic
pred.gamma.sd	patch-to-patch variability in predation intensity (0=none)
no.zero.patch	force all patches to have positive occupancy?

Examples

## Use default values: 3 sites (rows) with a total of
## 30 species: 5 abundance classes x 2 species per site x 3 sites.
## By default there is no mixing among sites (100% beta diversity).
## The default plot (rows=sites, columns=species) shows that each site
## has blocks of 2 species from each abundance class (grayscale indicates
## prevalence). The default for \code{betasim} is to do a deterministic
## simulation, simply returning a matrix with the expected number of
## individuals of each species at each site.
set.seed(101)
b0 <- betasim()
plot(b0)
## Specify 100% mixing now all species are present at all sites in
## the same numbers:
plot(betasim(p.mix=1))
## Partial mixing:
plot(betasim(p.mix=0.5))
## Add Poisson randomness:
plot(betasim(p.mix=0.5,rand="poisson"))
## Change the number sites or the number of abundance classes: by
## default, spcat (number of species per site per abundance
## category) will be adapted to try to make the total number of species
## come out correctly (i.e. spcat will be set to
## totsp/(n.site*n.abund)).  If totsp is not an even multiple of
## n.site*n.abund, the results may be unpredictable.
plot(betasim(n.site=5,n.abund=3,p.mix=0.25,rand="poisson"))

bbolker/betararef documentation built on Sept. 17, 2021, 8:49 a.m.