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

In MoBiodiv/MoBspatial: Spatial Simulation and Scale-Dependent Analysis of Biodiversity Changes

Non-spatial and spatially-explicit species sampling curves

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

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

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 April 1, 2024, 8:33 a.m.