Shannon's Diversity (Entropy) Index
Calculates Shannon's Diversity Index and Shannon's Evenness Index
shannons(x, counts = TRUE, ens = FALSE, margin = "row")
x |
data.frame object containing counts or proportions |
counts |
Are data counts (TRUE) or relative proportions (FALSE) |
ens |
Calculate effective number of species (TRUE/FALSE) |
margin |
Calculate diversity for rows or columns. c("row", "col") |
data.frame with "H" (Shannon's diversity) and "evenness" (Shannon's evenness where H / max( sum(x) ) ) and ESN
The expected for H is 0-3+ where a value of 2 has been suggested as medium-high diversity, for evenness is 0-1 with 0 signifying no evenness and 1, complete evenness.
Jeffrey S. Evans <jeffrey_evans@tnc.org>
Shannon, C. E. and W. Weaver (1948) A mathematical theory of communication. The Bell System Technical Journal, 27:379-423.
Simpson, E. H. (1949) Measurement of diversity. Nature 163:688
Roth, D. S., I. Perfecto, and B. Rathcke (1994) The effects of management systems on ground-foraging ant diversity in Costa Rica. Ecological Applications 4(3):423-436.
# Using Costa Rican ant diversity data from Roth et al. (1994)
data(ants)
# Calculate diversity for each covertype ("col")
shannons(ants[,2:ncol(ants)], ens = TRUE, counts = FALSE, margin = "col")
# Calculate diversity for each species ("row")
ant.div <- shannons(ants[,2:ncol(ants)], ens = TRUE, counts = FALSE,
margin = "row")
row.names(ant.div) <- ants[,1]
ant.divPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.