indpower | R Documentation |
Indicator power calculation of Halme et al. (2009) or the congruence between indicator and target species.
indpower(x, type = 0)
x |
Community data frame or matrix. |
type |
The type of statistic to be returned. See Details for explanation. |
Halme et al. (2009) described an index of indicator power defined as
IP_I = \sqrt{a \times 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.
A matrix with indicator species as rows and target species as columns (this is indicated by the first letters of the row/column names).
Peter Solymos
Halme, P., Mönkkönen, M., Kotiaho, J. S, Ylisirniö, A-L. 2009. Quantifying the indicator power of an indicator species. Conservation Biology 23: 1008–1016.
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
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