indicspecies (version 1.6.7)

coverage: Coverage of a set of indicators

Description

Function coverage calculates the proportion of sites of the target site group where one or another indicator (a species or a species combination) is found. Parameters are used to select valid indicators before calculating coverage. Function plotcoverage plots the coverage against the positive predictive value threshold used to select indicators.

Usage

coverage(x, y=NULL, selection=NULL, minstat=NULL, At=NULL, Bt=NULL, type="stat", alpha=0.05) 
plotcoverage(x, y=NULL, by=0.05, type="stat", max.order=NULL, group = NULL,  alpha = 0.05, add=FALSE, ...)

Value

When used with an object of class 'indicators', function coverage returns the proportion of sites of the target site group where one or another indicator (species combination) is found. When used with an object of class 'indicators', function coverage returns a vector containing the coverage value for each site group or site group combination.

encoding

UTF-8

Details

The coverage of a set of indicators was defined in De Cáceres{Caceres} et al. (2012) as the proportion of sites in a given site group where one or several indicators are found. This value allows assessing how often the site group will be able to be determined. If all indicators of a site group are rare, then the indication system will not be useful, regardless of how much restricted to the site group the indicators are. The coverage value is a generalization of quantity B of IndVal, that applies to a group of indicators instead of a single one. Function plotcoverage plots the coverage against the positive predictive value threshold (At) used to select indicators, as in De Cáceres{Caceres} et al. (2012). Functions coverage and plotcoverage can be executed using either an object of class 'indicators', or an object of class 'multipatt'. However, the parameters that apply to each case are slightly different. When using coverage and plotcoverage on objects of class 'multipatt' one is expected to calculate the coverage for those indicators that are significant (see alpha parameter), although other constraints to select valid indicators can be used. When using coverage and plotcoverage on objects of class 'indicators' one is expected to calculate the coverage for indicators that have values of A larger than a specified threshold (see At parameter). In this latter case, it may be advisable to use stat="lowerCI", so that indicators with broad confidence intervals are not included in the selection.

References

De Cáceres{Caceres}, M., Legendre, P., Wiser, S.K. and Brotons, L. 2012. Using species combinations in indicator analyses. Methods in Ecology and Evolution 3(6): 973-982.

See Also

indicators, multipatt, pruneindicators

Examples

library(stats)

data(wetland) ## Loads species data

## Creates three clusters using kmeans
wetkm = kmeans(wetland, centers=3) 

## Determine sensitivity of individual species
B=strassoc(wetland, cluster=wetkm$cluster,func="B") 

## Select species with more than 20% of sensitivity for the first group
sel=which(B[,1]>0.2) 

## Run indicator analysis with species combinations for the first group
sc= indicators(X=wetland[,sel], cluster=wetkm$cluster, group=1, verbose=TRUE, At=0.5, Bt=0.2)

## Determine the coverage of the selected set of indicators
coverage(sc)

## Plot the coverage against the threshold At
plotcoverage(sc)
plotcoverage(sc, max.order=2, add=TRUE, lty=2)

## Runs the combination analysis using IndVal.g as statistic
wetpt = multipatt(wetland, wetkm$cluster, control = permControl(nperm=999)) 
## Determines the coverage for each site group combination
coverage(wetland, wetpt)