rangerarity: Range rarity metric of endemism
In adamkocsis/obigeo: Occurrence-based biogeography
rangerarity R Documentation
Range rarity metric of endemism
Description
The function calculates the cumulated range rarity for every geographic cell given an occurrence table
Usage
rangerarity(dat, tax, loc, fine = NULL)
Arguments
dat
data.frame or RasterStack The occurrence table.
tax
character Variable name of the taxon names.
loc
character Variable name of the locality information (e.g. geographic cells). Range rarity will be output for every entry in this column.
fine
character Variable name of the basic geographic information (optional) that is clustered to coarser units (in loc).
Details
The metric was originally impelmented by Selig et al., 2014 (Plos ONE). For every cell or locality (loc argument),
the function sums up the inverse occupancy (1/occupancy) of every taxon that occurrs there.
If available, the function will weigh each of these taxon/locality specific values by a fraction.
As in Selig et al. (2014), this is the proportion of finer-scale occurrence-points (e.g. coordinates) in the locality (cell) compared to the maximum observed number of fine-scale occurrences in that particular locality (cell).
In other words, entries in loc cluster entries in fine. The weights will be the number a taxon has compared to the maximum number observed in the whole dataset.
adamkocsis/obigeo documentation built on Oct. 14, 2024, 8:46 a.m.
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| rangerarity | R Documentation |
Range rarity metric of endemism
Description
The function calculates the cumulated range rarity for every geographic cell given an occurrence table
Usage
rangerarity(dat, tax, loc, fine = NULL)
Arguments
dat |
|
tax |
|
loc |
|
fine |
|
Details
The metric was originally impelmented by Selig et al., 2014 (Plos ONE). For every cell or locality (loc argument),
the function sums up the inverse occupancy (1/occupancy) of every taxon that occurrs there.
If available, the function will weigh each of these taxon/locality specific values by a fraction.
As in Selig et al. (2014), this is the proportion of finer-scale occurrence-points (e.g. coordinates) in the locality (cell) compared to the maximum observed number of fine-scale occurrences in that particular locality (cell).
In other words, entries in loc cluster entries in fine. The weights will be the number a taxon has compared to the maximum number observed in the whole dataset.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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