div_hurlbert {divent} | R Documentation |
Hurlbert Diversity of a Community
Description
Estimate the diversity sensu stricto, i.e. the effective number of species number of species Dauby and Hardy (2012) from abundance or probability data.
Usage
div_hurlbert(x, k = 1, ...)
## S3 method for class 'numeric'
div_hurlbert(
x,
k = 2,
estimator = c("Hurlbert", "naive"),
as_numeric = FALSE,
...,
check_arguments = TRUE
)
## S3 method for class 'species_distribution'
div_hurlbert(
x,
k = 2,
estimator = c("Hurlbert", "naive"),
...,
check_arguments = TRUE
)
Arguments
x |
An object, that may be a numeric vector containing abundances or probabilities, or an object of class abundances or probabilities. |
k |
The order of Hurlbert's diversity. |
... |
Unused. |
estimator |
An estimator of asymptotic diversity. |
as_numeric |
If |
check_arguments |
If |
Details
Several estimators are available to deal with incomplete sampling.
Bias correction requires the number of individuals.
Estimation techniques are from Hurlbert (1971).
Hurlbert's diversity cannot be estimated at a specified level of interpolation or extrapolation, and diversity partioning is not available.
Value
A tibble with the site names, the estimators used and the estimated diversity.
References
Dauby G, Hardy OJ (2012).
“Sampled-Based Estimation of Diversity Sensu Stricto by Transforming Hurlbert Diversities into Effective Number of Species.”
Ecography, 35(7), 661–672.
doi:10.1111/j.1600-0587.2011.06860.x.
Hurlbert SH (1971).
“The Nonconcept of Species Diversity: A Critique and Alternative Parameters.”
Ecology, 52(4), 577–586.
doi:10.2307/1934145.
Examples
# Diversity of each community
div_hurlbert(paracou_6_abd, k = 2)