population_to_sample_partition: Calculate sample-level partition

Description Usage Arguments Value Examples

View source: R/partitioning_functions.R

Description

takes a complete sample of all Q species in a community, and estimates sample-level selection and complementarity effects expected from a subset of N species drawn randomly from that community

Usage

1
2
population_to_sample_partition(DRY, M, N, Q = length(M),
  smallQ_correction = TRUE, uncorrected_cov = FALSE)

Arguments

DRY

change in relative yield, as calculated by the calculate_DRY function

M

monoculture biomass

N

number of species in the sample of the full community (i.e. the "sample") - defaults to length(M)

Q

total number of species in the full community (i.e. the "population")

smallQ_correction

tells whether to apply the correction for small Q, as shown in Eq. 3c in the main text - defaults to TRUE

uncorrected_cov

A character, which can be TRUE, FALSE, or COMP. Tells whether to use the standard sample-size corrected covariance function (FALSE), or a covariance function that is not corrected for sample size (TRUE), or a "compromise" function that resembles the standard function for N < Q, and that resembles the non-corrected function for N ~ Q If TRUE, then SS + CS = YO - YE, sensu Loreau and Hector 2001 defaults to FALSE note - we do not recommend setting this to TRUE or "COMP", unless you require SS+CS=YO-YE

Value

a list with elements SS (the sample-level selection effect), CS (the sample-level complementarity effect), SP (the population-level selection effect), and CP (the population-level complementarity effect),

Examples

1
# Please see package help file (?partitionBEFsp) for examples.

partitionBEFsp documentation built on Aug. 21, 2019, 9:05 a.m.