rarefy(x, sample, se = FALSE, MARGIN = 1)
rrarefy(x, sample)
drarefy(x, sample)
rarecurve(x, step = 1, sample, xlab = "Sample Size", ylab = "Species", label = TRUE, col, lty, ...)
rareslope(x, sample)x
(logical).par. Can be a vector of length nrow(x), one per
sample, and will be extended to such a length internally.sample and se = TRUE, function rarefy returns a
2-row matrix with rarefied richness (S) and its standard error
(se). If sample is a vector in rarefy, the
function returns a matrix with a column for each sample size,
and if se = TRUE, rarefied richness and its standard error are
on consecutive lines.Function rarecurve returns invisible list of
rarefy results corresponding each drawn curve.
rarefy gives the expected species richness in random
subsamples of size sample from the community. The size of
sample should be smaller than total community size, but the
function will work for larger sample as well (with a warning)
and return non-rarefied species richness (and standard error =
0). If sample is a vector, rarefaction of all observations is
performed for each sample size separately. Rarefaction can be
performed only with genuine counts of individuals. The function
rarefy is based on Hurlbert's (1971) formulation, and the
standard errors on Heck et al. (1975). Function rrarefy generates one randomly rarefied community
data frame or vector of given sample size. The sample
can be a vector giving the sample sizes for each row. If the
sample size is equal to or smaller than the observed number
of individuals, the non-rarefied community will be returned. The
random rarefaction is made without replacement so that the variance
of rarefied communities is rather related to rarefaction proportion
than to the size of the sample.
Function drarefy returns probabilities that species occur in
a rarefied community of size sample. The sample can be
a vector giving the sample sizes for each row. If the sample
is equal to or smaller than the observed number of individuals, all
observed species will have sampling probability 1.
Function rarecurve draws a rarefaction curve for each row of
the input data. The rarefaction curves are evaluated using the
interval of step sample sizes, always including 1 and total
sample size. If sample is specified, a vertical line is
drawn at sample with horizontal lines for the rarefied
species richnesses.
Function rareslope calculates the slope of rarecurve
(derivative of rarefy) at given sample size; the
sample need not be an integer.
specaccum for species accumulation curves
where sites are sampled instead of individuals. specpool
extrapolates richness to an unknown sample size.data(BCI)
S <- specnumber(BCI) # observed number of species
(raremax <- min(rowSums(BCI)))
Srare <- rarefy(BCI, raremax)
plot(S, Srare, xlab = "Observed No. of Species", ylab = "Rarefied No. of Species")
abline(0, 1)
rarecurve(BCI, step = 20, sample = raremax, col = "blue", cex = 0.6)
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