Normalised beta (low level diversity component)

Calculates the low-level diversity component necessary for calculating normalised beta diversity.

norm_beta(meta)

Arguments

meta

object of class metacommunity

Value

norm_beta returns an object of class relativeentropy

Details

Values generated from norm_beta() may be input into subdiv() and metadiv() to calculate normalised subcommunity and metacommunity beta diversity.

References

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

Examples

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 beta component
b <- norm_beta(meta)
subdiv(b, 1)
#>           measure q type_level type_name partition_level partition_name
#> 1 normalised beta 1      types              subcommunity              a
#> 2 normalised beta 1      types              subcommunity              b
#>   diversity dat_id transformation normalised  k max_d
#> 1  1.016552  naive             NA         NA NA    NA
#> 2  1.060660  naive             NA         NA NA    NA
metadiv(b, 1)
#>           measure q type_level type_name partition_level partition_name
#> 1 normalised beta 1      types             metacommunity               
#>   diversity dat_id transformation normalised  k max_d
#> 1  1.031047  naive             NA         NA NA    NA