subdiv: Calculate subcommunity-level diversity

In rdiversity: Measurement and Partitioning of Similarity-Sensitive Biodiversity

Calculate subcommunity-level diversity

Description

Generic function for calculating subcommunity-level diversity.

Usage

subdiv(data, qs)

## S4 method for signature 'powermean'
subdiv(data, qs)

## S4 method for signature 'relativeentropy'
subdiv(data, qs)

## S4 method for signature 'metacommunity'
subdiv(data, qs)

Arguments

data	matrix of mode numeric; containing diversity components
qs	vector of mode numeric containing q values

Details

data may be input as one of three different classes:

• powermean: raw or normalised metacommunity alpha, rho or gamma diversity components; will calculate subcommunity-level raw or normalised metacommunity alpha, rho or gamma diversity

• relativeentropy: raw or normalised metacommunity beta diversity components; will calculate subcommunity-level raw or normalised metacommunity beta diversity

• metacommunity: will calculate all subcommunity measures of diversity

Value

subdiv() returns a standard output of class rdiv

References

Reeve, R., T. Leinster, C. Cobbold, J. Thompson, N. Brummitt, S. Mitchell, and L. Matthews. 2016. How to partition diversity. arXiv 1404.6520v3:1–9.

See Also

inddiv for type-level diversity and metadiv for metacommunity-level diversity.

Examples

# Define metacommunity
pop <- data.frame(a = c(1,3), b = c(1,1))
row.names(pop) <- paste0("sp", 1:2)
pop <- pop/sum(pop)
meta <- metacommunity(pop)

# Calculate subcommunity gamma diversity (takes the power mean)
g <- raw_gamma(meta)
subdiv(g, 0:2)

# Calculate subcommunity beta diversity (takes the relative entropy)
b <- raw_beta(meta)
subdiv(b, 0:2)

# Calculate all measures of subcommunity diversity
subdiv(meta, 0:2)

rdiversity documentation built on May 6, 2022, 9:06 a.m.