Calculates similarity-sensitive normalised metacommunity alpha diversity (the average similarity-sensitive diversity of subcommunities). This measure may be calculated for a series of orders, represented as a vector of qs.

norm_meta_alpha(meta, qs)



object of class metacommunity


vector of mode numeric containing q values


norm_meta_alpha returns a standard output of class rdiv


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.


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 metacommunity alpha diversity
norm_meta_alpha(meta, 0:2)
#>            measure q type_level type_name partition_level partition_name
#> 1 normalised alpha 0      types             metacommunity               
#> 2 normalised alpha 1      types             metacommunity               
#> 3 normalised alpha 2      types             metacommunity               
#>   diversity dat_id transformation normalised  k max_d
#> 1  2.000000  naive             NA         NA NA    NA
#> 2  1.832973  naive             NA         NA NA    NA
#> 3  1.714286  naive             NA         NA NA    NA