spec_sample_curve: Non-spatial and spatially-explicit species sampling curves

Description Usage Arguments Details Value Examples

View source: R/SAC_spatial.R

Description

Expected species richness as function of sample size (no. of individuals), when individuals are sampled randomly (rarefaction) or when nearest-neighbours are samples (accumulation).

Usage

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spec_sample_curve(comm, method = c("accumulation", "rarefaction"))

Arguments

comm

Community object

method

Partial match to accumulation or rarefaction. Also both methods can be included at the same time.

Details

Non-spatial sampling corresponds to the species rarefaction curve, which only depends on the species abundance distribution and can thus be also calculated from abundance data (see rare_curve).

In contrast the species-accumulation curve starts from a focal individual and only samples the nearest neighbours of the focal individual. The final species accumulation curves is calculated as the mean over the accumulation curves starting from all individuals.

In contrast to the rarefaction curve the accumulation curve is not only influenced by the species abundance distribution, but also by the spatial distribution of individuals.

Value

A dataframe with 2-3 columns. The first column indicates the sample size (numbers of individuals), and the second and third column indicate the expected species richness for spatial sampling (column: "spec_accum") and/or random sampling (column "spec_rarefied")

Examples

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sim_com1 <- sim_thomas_community(s_pool = 100, n_sim = 1000)
sac1 <- spec_sample_curve(sim_com1, method = c("rare","acc"))

head(sac1)
plot(sac1)

MoBiodiv/MoBspatial documentation built on July 24, 2021, 6:09 p.m.