indicspecies (version 1.7.15)

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 = NULL
)
plotcoverage(
  x,
  y = NULL,
  by = 0.05,
  type = "stat",
  max.order = NULL,
  group = NULL,
  alpha = NULL,
  add = FALSE,
  xlab = expression(A[t]),
  ...
)

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.

Arguments

x

An object of class 'indicators' or a community data table with sites in rows and species in columns (in this second case, an object of class 'multipatt' must be supplied for y).

y

An object of class 'multipatt'.

selection

A logical vector restricting the set of indicators used to calculate the coverage.

minstat

Minimum value of the statistic for selecting indicators.

At

Minimum value of positive predictive value (A) for selecting indicators.

Bt

Minimum value for sensitivity (B) for selecting indicators.

type

Specifies how to select indicators: (1) using the value of the statistic (type = "stat"); (2) the lower bound of its confidence interval (type = "lowerCI"); or (3) the upper bound of its confidence interval (type = "upperCI"). This parameter makes sense when the function is called using objects of class 'indicators' and bootstrap confidence intervals are available for this object. Otherwise type has no effect and the value of the statistic is used for selection. In function coverage, the value of type applies to selection using minstat, At and Bt. In function plotcoverage, the value of type applies to selection using At.

alpha

Significance level for selecting indicators.

by

Rate of increase in the predictive value threshold (At).

max.order

The maximum number of species conforming species combinations (allows examining the effects of increasing the order of combinations).This parameter is only used when the function is called using objects of class 'indicators'.

group

Either an integer or a character string indicating the site group or site group combination for which plot is desired. This parameter is only used when the function is called using objects of class 'multipatt'.

add

Flag indicating whether the function should draw on the existing plot.

xlab

Label for the x-axis.

...

Additional plotting parameters that are passed to the plot function.

Author

Miquel De Cáceres Ainsa, EMF-CREAF

Details

The coverage of a set of indicators was defined in De Cáceres 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 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, 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) 

## Run indicator analysis with species combinations for the first group
sc <- indicators(X=wetland, 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 = how(nperm=999))
 
## Determines the coverage for each site group combination
coverage(wetland, wetpt, alpha = 0.05)