Compute areas of occupancy (AOO) for multiple taxa in square kilometers
AOO.computing( XY, Cell_size_AOO = 2, nbe.rep.rast.AOO = 0, parallel = FALSE, NbeCores = 2, show_progress = TRUE, export_shp = FALSE )
XY |
|
---|---|
Cell_size_AOO | numeric, value indicating the grid size in kilometers used for estimating Area of Occupancy. By default, equal to 2 |
nbe.rep.rast.AOO | numeric , indicate the number of raster with random starting position for estimating the AOO. By default, it is 0 but some minimal translation of the raster are still done |
parallel | logical, whether running in parallel. By default, it is FALSE |
NbeCores | string integer, register the number of cores for parallel execution. By default, it is 2 |
show_progress | logical, whether a bar showing progress in computation should be shown. By default, it is TRUE |
export_shp | logical, whether a shapefile of occupied cells should be exported. By default, it is FALSE |
If export_shp
if FALSE a vector of AOO estimates for each taxa
If export_shp
if TRUE a list with two elements
a vector of AOO estimates for each taxa
a list of SpatialPolygonsDataFrame for each taxa
Input as a dataframe
should have the following structure:
It is mandatory to respect field positions, but field names do not matter
[,1] | ddlat | numeric, latitude (in decimal degrees) |
[,2] | ddlon | numeric, longitude (in decimal degrees) |
[,3] | tax | character or factor, taxa names |
The argument of nbe.rep.rast.AOO
ideally should be higher than 20 for increasing
the chance to get the minimal number of occupied cell. Increasing nbe.rep.rast.AOO
however also increase the computing time.
So this is a trade-off that depend on the importance to get the minimal AOO and the sie of the dataset.
Gaston & Fuller 2009 The sizes of species'geographic ranges, Journal of Applied Ecology, 49 1-9
data(dataset.ex) if (FALSE) { AOO <- AOO.computing(dataset.ex) } # This would estimate AOO for all taxa by overlaying randomly a # grid 100 times. For each taxa, the minimum value is kept if (FALSE) { AOO <- AOO.computing(dataset.ex, nbe.rep.rast.AO = 100) }