Description Usage Arguments Details Value Author(s) References See Also Examples
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.
1 2 3 4 |
x |
An object of class ' |
y |
An object of class ' |
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. |
alpha |
Significance level for selecting indicators. This parameter is only used when the function is called using objects of class ' |
type |
Specifies how to select indicators: (1) using the value of the statistic ( |
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 ' |
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 ' |
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 |
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.
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.
Miquel De Cáceres Ainsa, CTFC
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.
indicators
, multipatt
, pruneindicators
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | 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 = how(nperm=999))
## Determines the coverage for each site group combination
coverage(wetland, wetpt)
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