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Calculates similarity-sensitive normalised subcommunity alpha diversity
(the diversity of subcommunity j in isolation. This measure may be
calculated for a series of orders, repesented as a vector of qs
.
norm_sub_alpha(meta, qs)
object of class metacommunity
vector
of q values
Returns a standard output of class tibble
, with columns:
measure
, (norm alpha),
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
.
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.
# 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 alpha diversity
norm_sub_alpha(meta, 0:2)
# }
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