sperich (version 1.3-7)

adjustment: Adjustment of interpolated species richness

Description

This routine adjusts the weighted species richness for sampling effort.

Usage

adjustment(species.richness, noninterpolatedgrid, clusterlist)

Arguments

species.richness

The grid that should be adjusted. It contains the result of species richness estimation or cross-validation.

noninterpolatedgrid

A grid containing the species occurences (could be created via function 'createNonInterpolatedGrid').

clusterlist

A list of vectors of pixelpositions (created by 'searchClusters') which are spatial related.

Value

• This function returns a grid containing the adjusted species richness information.

Details

This routine adjusts the interpolated species richness for sampling effort by incorporating an additional weighting factor. Therefor, it needs clusters of pixels of the result grid to find centers of species richness and to create these weighting factor.

References

Raedig, C., Dorman, C.F., Hildebrandt, A. and Lautenbach, S. (2010). Reassessing Neotropical angiosperm distribution patterns based on monographic data: a geometric interpolation approach. Biodivers Conserv, 19, 1523-1546.

Examples

##load data
data(dataset.all.species)
data(dataset.landwater)

##create grid parameters
dimension <- getDimension(dataset.all.species, resolution=1)
shift <- getShift(dataset.all.species)

##create landwatermask
landwatermask.nocoast <- createLandwatermask(dataset.landwater, 
					dimension, shift, resolution=1)

##estimate species richness
species.richness.weighted <- species.richness(dataset.all.species, 
		landwatermask.nocoast, distances=1:10, weight=0.5, dimension, shift, resolution=1,
		upperbound=5, narrow.endemic=FALSE, narrow.endemic.limit=5, 
		all.species=1:20)

##prepare adjustment
noninterpolatedgrid <- createNonInterpolatedGrid(dataset.all.species, 
				dimension, shift, resolution=1, all.species=-1)
clusterlimit <- 100

clusterlist <- searchClusters(species.richness.weighted, 
		dimension, shift, resolution=1, clusterlimit)

##adjust species richness
species.richness.weighted.adjusted <- adjustment(species.richness.weighted, 
		noninterpolatedgrid, clusterlist)