Hurlbert Entropy of a Community

Estimate the Hurlbert entropy (Hurlbert 1971) of species from abundance or probability data. Several estimators are available to deal with incomplete sampling.

Usage

ent_hurlbert(x, k = 2, ...)

# S3 method for class 'numeric'
ent_hurlbert(
  x,
  k = 2,
  estimator = c("Hurlbert", "naive"),
  as_numeric = FALSE,
  ...,
  check_arguments = TRUE
)

# S3 method for class 'species_distribution'
ent_hurlbert(
  x,
  k = 2,
  estimator = c("Hurlbert", "naive"),
  as_numeric = FALSE,
  ...,
  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 entropy.
as_numeric: if TRUE, a number or a numeric vector is returned rather than a tibble.
check_arguments: if TRUE, the function arguments are verified. Should be set to FALSE to save time when the arguments have been checked elsewhere.

Value

A tibble with the site names, the estimators used and the estimated entropy.

Details

Bias correction requires the number of individuals. See div_hurlbert for estimators.

Hurlbert's entropy cannot be estimated at a specified level of interpolation or extrapolation, and entropy partitioning is not available.

References

Hurlbert SH (1971). “The Nonconcept of Species Diversity: A Critique and Alternative Parameters.” Ecology, 52(4), 577–586. doi:10.2307/1934145 .

Examples

# Entropy of each community
ent_hurlbert(paracou_6_abd, k = 2)
#> # A tibble: 4 × 5
#>   site      weight estimator order entropy
#>   <chr>      <dbl> <chr>     <dbl>   <dbl>
#> 1 subplot_1   1.56 Hurlbert      2    1.98
#> 2 subplot_2   1.56 Hurlbert      2    1.98
#> 3 subplot_3   1.56 Hurlbert      2    1.98
#> 4 subplot_4   1.56 Hurlbert      2    1.97