Estimate the diversity sensu stricto, i.e. the effective number of species number of species Dauby2012;textualdivent from abundance or probability data.
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
)An object, that may be a numeric vector containing abundances or probabilities, or an object of class abundances or probabilities.
The order of Hurlbert's diversity.
Unused.
An estimator of asymptotic diversity.
If TRUE, a number or a numeric vector is returned rather than a tibble.
If TRUE, the function arguments are verified.
Should be set to FALSE to save time when the arguments have been checked elsewhere.
A tibble with the site names, the estimators used and the estimated diversity.
Several estimators are available to deal with incomplete sampling.
Bias correction requires the number of individuals.
Estimation techniques are from Hurlbert1971;textualdivent.
Hurlbert's diversity cannot be estimated at a specified level of interpolation or extrapolation, and diversity partioning is not available.
# Diversity of each community
div_hurlbert(paracou_6_abd, k = 2)
#> # A tibble: 4 × 5
#> site weight estimator order diversity
#> <chr> <dbl> <chr> <dbl> <dbl>
#> 1 subplot_1 1.56 Hurlbert 2 42.3
#> 2 subplot_2 1.56 Hurlbert 2 44.6
#> 3 subplot_3 1.56 Hurlbert 2 48.9
#> 4 subplot_4 1.56 Hurlbert 2 36.0