rdiversity (version 1.0)

norm_sub_beta: Normalised subcommunity beta diversity

Description

Calculates similarity-sensitive normalised subcommunity beta diversity (an estimate of the effective number of distinct subcommunities). This measure may be calculated for a series of orders, repesented as a vector of qs.

Usage

norm_sub_beta(meta, qs)

Arguments

meta

object of class metacommunity

qs

vector of q values

Value

Returns a standard output of class tibble, with columns: measure, (norm beta), q (parameter of conservatism), type_level (), type_name (label attributed to type), partition_level (level of diversity, i.e. subcommunity), partition_name (label attributed to partition), and diversity.

References

Reeve, R., T. Leinster, C. Cobbold, J. Thompson, N. Brummitt, S. Mitchell, and L. Matthews. 2014. How to partition diversity. arXiv 1404.6520:1<U+2013>9.

Examples

# NOT RUN {
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 normalised subcommunity beta diversity
norm_sub_beta(meta, 0:2)

# }