diversity {tabula} | R Documentation |
Alpha Diversity
Description
Computes multiple alpha diversity indices.
Usage
diversity(object, ...)
## S4 method for signature 'matrix'
diversity(object, ..., evenness = FALSE, unbiased = FALSE)
## S4 method for signature 'data.frame'
diversity(object, ..., evenness = FALSE, unbiased = FALSE)
Arguments
object |
A |
... |
Currently not used. |
evenness |
A |
unbiased |
A |
Details
Alpha diversity refers to diversity at the local level, assessed within a delimited system. It is the diversity within a uniform habitat of fixed size.
Diversity measurement assumes that all individuals in a specific taxa are equivalent and that all types are equally different from each other (Peet 1974). A measure of diversity can be achieved by using indices built on the relative abundance of taxa. These indices (sometimes referred to as non-parametric indices) benefit from not making assumptions about the underlying distribution of taxa abundance: they only take relative abundances of the species that are present and species richness into account. Peet (1974) refers to them as indices of heterogeneity.
Diversity indices focus on one aspect of the taxa abundance and emphasize either richness (weighting towards uncommon taxa) or dominance (weighting towards abundant taxa; Magurran 1988).
Evenness is a measure of how evenly individuals are distributed across the sample.
Value
A data.frame
with the following columns:
size
Sample size.
observed
Number of observed taxa/types.
shannon
brillouin
simpson
berger
menhinick
margalef
chao1
ace
squares
Note
The berger
and simpson
methods return a dominance index, not the
reciprocal or inverse form usually adopted, so that an increase in the value
of the index accompanies a decrease in diversity.
Author(s)
N. Frerebeau
References
Magurran, A. E. (1988). Ecological Diversity and its Measurement. Princeton, NJ: Princeton University Press. doi:10.1007/978-94-015-7358-0.
Peet, R. K. (1974). The Measurement of Species Diversity. Annual Review of Ecology and Systematics, 5(1), 285-307. doi:10.1146/annurev.es.05.110174.001441.
See Also
Other diversity measures:
evenness()
,
heterogeneity()
,
occurrence()
,
plot.DiversityIndex()
,
plot.RarefactionIndex()
,
profiles()
,
rarefaction()
,
richness()
,
she()
,
similarity()
,
simulate()
,
turnover()
Examples
## Data from Conkey 1980, Kintigh 1989
data("cantabria")
## Alpha diversity
diversity(cantabria)
## Shannon diversity index
(h <- heterogeneity(cantabria, method = "shannon"))
(e <- evenness(cantabria, method = "shannon"))
as.data.frame(h)