# shannons

0th

Percentile

##### Shannon's Diversity (Entropy) Index

Calculates Shannon's Diversity Index and Shannon's Evenness Index

##### Usage
shannons(x, counts = TRUE, ens = FALSE, margin = "row")
##### Arguments
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")

##### Value

data.frame with "H" (Shannon's diversity) and "evenness" (Shannon's evenness where H / max( sum(x) ) ) and ESN

##### Note

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.

##### References

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.

• shannons
##### Examples
# NOT RUN {
# 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.div

# }

Documentation reproduced from package spatialEco, version 1.3-2, License: GPL-3

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