Counts the number of species observed the same number of times.

AbdFreqCount(Ns, Level = NULL, PCorrection="Chao2015", Unveiling="geom", 
  RCorrection="Rarefy", CheckArguments = TRUE)

Arguments

Ns

A numeric vector containing species abundances.

Level

The level of interpolation or extrapolation. It may be an an arbitrary sample size (an integer) or a sample coverage (a number between 0 and 1).

PCorrection

A string containing one of the possible corrections to estimate a probability distribution in as.ProbaVector: "Chao2015" is the default value. Used only for extrapolation.

Unveiling

A string containing one of the possible unveiling methods to estimate the probabilities of the unobserved species in as.ProbaVector: "geom" (geometric: the unobserved species distribution is geometric) is the default value. Used only for extrapolation.

RCorrection

A string containing a correction recognized by Richness to evaluate the total number of species in as.ProbaVector. "Rarefy" is the default value to estimate the number of species such that the richness of the asymptotic distribution rarefied to the observed sample size equals the observed number of species in the data. Used only for extrapolation.

CheckArguments

Logical; if TRUE, the function arguments are verified. Should be set to FALSE to save time when the arguments have been checked elsewhere.

Details

The Abundance Frequency Count (Chao et al., 2015) is the number of species observed each number of times.

It is a way to summarize the species distribution.

It can be estimated at a specified level of interpolation or extrapolation. Extrapolation relies on the estimation of the estimation of the asymptotic distribution of the community by as.ProbaVector and eq. (5) of Chao et al. (2014).

Value

A two-column matrix. The first column contains the number of observations, the second one the number of species observed this number of times.

References

Chao, A., Gotelli, N. J., Hsieh, T. C., Sander, E. L., Ma, K. H., Colwell, R. K., Ellison, A. M (2014). Rarefaction and extrapolation with Hill numbers: A framework for sampling and estimation in species diversity studies. Ecological Monographs, 84(1): 45-67.

Chao, A., Hsieh, T. C., Chazdon, R. L., Colwell, R. K., Gotelli, N. J. (2015) Unveiling the Species-Rank Abundance Distribution by Generalizing Good-Turing Sample Coverage Theory. Ecology 96(5): 1189-1201.

See also

Examples

# Load Paracou data (number of trees per species in two 1-ha plot of a tropical forest
#      and their taxonomy)
data(Paracou618)
# Ns is the vector of abundances of the first plot
Ns <- Paracou618.MC$Nsi[, 1]

# Return the abundance frequency count
(AbdFreqCount(Ns) -> afc)
#>       Abundance NbSpecies
#>  [1,]         1        68
#>  [2,]         2        29
#>  [3,]         3        14
#>  [4,]         4         5
#>  [5,]         5         8
#>  [6,]         6         3
#>  [7,]         7         4
#>  [8,]         9         1
#>  [9,]        10         2
#> [10,]        13         1
#> [11,]        14         1
#> [12,]        16         1
#> [13,]        19         1
#> [14,]        21         1
#> [15,]        23         1
#> [16,]        25         1
#> [17,]        26         1
#> [18,]        30         1
#> [19,]        31         1
#> [20,]        38         1
#> [21,]        39         1
#> [22,]        45         1
#> attr(,"class")
#> [1] "AbdFreqCount" "matrix"       "array"       
plot(afc, xlab="Number of observations", ylab="Number of species")
lines(afc)