Calculates similarity-sensitive raw subcommunity beta diversity (the
distinctiveness of subcommunity j). This measure may be calculated
for a series of orders, represented as a vector of qs.
raw_sub_beta(meta, qs)object of class metacommunity
vector of mode numeric containing q values
raw_sub_beta 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 raw subcommunity beta diversity
raw_sub_beta(meta, 0:2)
#> measure q type_level type_name partition_level partition_name diversity
#> 1 raw beta 0 types subcommunity a 0.6666667
#> 2 raw beta 0 types subcommunity b 0.3333333
#> 3 raw beta 1 types subcommunity a 0.6777015
#> 4 raw beta 1 types subcommunity b 0.3535534
#> 5 raw beta 2 types subcommunity a 0.6875000
#> 6 raw beta 2 types subcommunity b 0.3750000
#> dat_id transformation normalised k max_d
#> 1 naive NA NA NA NA
#> 2 naive NA NA NA NA
#> 3 naive NA NA NA NA
#> 4 naive NA NA NA NA
#> 5 naive NA NA NA NA
#> 6 naive NA NA NA NA