R: Indicator Power of Species

indpower {vegan} | R Documentation

## Indicator Power of Species

### Description

Indicator power calculation of Halme et al. (2009) or the congruence between indicator and target species.

### Usage

    indpower(x, type = 0)

### Arguments

`x` | Community data frame or matrix.
`type` | The type of statistic to be returned. See Details for explanation.

### Details

Halme et al. (2009) described an index of indicator power defined as IP_I = sqrt(a*b), where a = S / O_I and b = 1 - (O_T - S) / (N - O_I). N is the number of sites, S is the number of shared occurrences of the indicator (I) and the target (T) species. O_I and O_T are number of occurrences of the indicator and target species. The `type` argument in the function call enables to choose which statistic to return. `type = 0` returns IP_I, `type = 1` returns a, `type = 2` returns b. Total indicator power (TIP) of an indicator species is the column mean (without its own value, see examples). Halme et al. (2009) explain how to calculate confidence intervals for these statistics, see Examples.

### Value

A matrix with indicator species as rows and target species as columns (this is indicated by the first letters of the row/column names).

### Author(s)

Peter Solymos

### References

Halme, P., Mönkkönen, M., Kotiaho, J. S, Ylisirniö, A-L. 2009. Quantifying the indicator power of an indicator species. Conservation Biology 23: 1008–1016.

### See Also

`indval` (package labdsv) for the indicator species analysis of Dufrêne & Legendre. Function `beals` estimates individual cell probabilities of species occurrences.

### Examples

    data(dune)
    ## IP values
    ip <- indpower(dune)
    ## and TIP values
    diag(ip) <- NA
    (TIP <- rowMeans(ip, na.rm=TRUE))

    ## p value calculation for a species
    ## from Halme et al. 2009
    ## i is ID for the species
    i <- 1
    fun <- function(x, i) indpower(x)[i,-i]
    ## 'c0' randomizes species occurrences
    os <- oecosimu(dune, fun, "c0", i=i, nsimul=99)
    ## get z values from oecosimu output
    z <- os$oecosimu$z
    ## p-value
    (p <- sum(z) / sqrt(length(z)))
    ## 'heterogeneity' measure
    (chi2 <- sum((z - mean(z))^2))
    pchisq(chi2, df=length(z)-1)
    ## Halme et al.'s suggested output
    out <- c(TIP=TIP[i],
        significance=p,
        heterogeneity=chi2,
        minIP=min(fun(dune, i=i)),
        varIP=sd(fun(dune, i=i)^2))
    out

[Package vegan version 2.4-3 Index]