Description Usage Arguments Examples
Simulate communities with specified diversity characteristics
1 2 3 4 5 6 | 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)
|
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.gamma.sd |
patch-to-patch variability in predation intensity (0=none) |
no.zero.patch |
force all patches to have positive occupancy? |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ## 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"))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.