species.richness.cv | R Documentation |
This function cross-validates the species richness based on given species occurrences.
species.richness.cv(dataset.all.species, landwatermask, fold=5,
loocv.limit=10, distances=3:10, weight=0.5, dimension, origin,
resolution=1, upperbound, all.species=-1,
silent=TRUE, do.parallel=FALSE)
dataset.all.species |
A dataset containing the species with their ID (named: speciesID)and the longitude (named: long) and latitude (named: lat) of their occurrence location. |
landwatermask |
A grid containing the land-water-information of the observed area. If a grid cell containes no land, the value of the cell in the landwatermask is -1, otherwise it is 0. Additional, height-informations could be added for land surfaces. In this case, take care of the 'upperbound' value. |
fold |
The number of groups which should be created if the number of occurrences is greater than loocv.limit. |
loocv.limit |
The limit below which the subsamples are created for a leave-one-out-cross-validation instead of a k-fold-cross-validation. |
distances |
The distances which will be used for species range estimation. |
weight |
The tuning parameter of the weighting procedure (details in Raedig et al. 2010). |
dimension |
The dimension of the processed grid. |
origin |
The geographic coordinates of the origin of the grid. |
resolution |
The resolution of the grid in (geographical) degree. |
upperbound |
This value determines the height (based on values in 'landwatermask') which is considered to be a barrier for species distribution. |
all.species |
The vector with the numbers of the species which should be mentioned. If the first value is -1, all species in the database will be used for species richness estimation. |
silent |
A boolean flag that determines wether the report of status messages should be suppressed or not. |
do.parallel |
A boolean flag determining wether the function uses the 'foreach'-package to cross-validate via parallel processing. |
This routine cross-validates the species richness based on given species occurrences through a geometric interpolation model (details in Raedig et al. 2010).
This function returns a grid which contains the cross-validated species richness information.
Maximilian Lange, Sven Lautenbach, Claudia Raedig
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.
##load data
data(dataset.all.species)
data(dataset.landwater)
##create grid parameters
dimension <- getDimension(dataset.all.species, resolution=1)
origin <- getOrigin(dataset.all.species)
##create landwatermask
landwatermask.nocoast <- createLandwatermask(dataset.landwater,
dimension, origin, resolution=1)
##estimate species richness
species.richness.weighted <- species.richness.cv(dataset.all.species,
landwatermask.nocoast, fold=5, loocv.limit=10, distances=2:5,
weight=0.5, dimension, origin, resolution=1, upperbound=5,
all.species=1:2)
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