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The package contains three grid data sets. The grid data sets (64 × 64 sampling units) feature one simulation (`grid_patchy_associated`) and two simulation derivatives (`grid_random and grid_n_ISC`) have been produced by randomization. A spatially explicit individual-based simulation model (PATPRO) was selected to produce a realistic grid community pattern `grid_patchy` and features interspecific and intraspecific spatial dependence due to simulated abiotic and biotic interactions. The `grid_random` and `grid_patchy_n_isc` data sets were produced by CSR and RS randomizations of the original simulation `grid_patchy`. The `grid_patchy_n_isc` data set only features intraspecific spatial dependence; interspecific relationships were removed by randomizations. The `grid_random` data set only features random distributions; both intra- and interspecific relationships were removed by randomizations.

Usage

grid_random

Format

A data frame with 1551 species observations on the following three variables.

X

X coordinates

Y

Y coordinates

Species

Species

Details

The `X` and `Y` coordinates refer to the sampling unit of the species in the sampling universe.

Examples

data("grid_random", package = "comspat")
str(grid_random)
#> 'data.frame':	1551 obs. of  3 variables:
#>  $ Species: Factor w/ 6 levels "Sp1","Sp2","Sp3",..: 1 1 1 1 1 1 1 1 1 1 ...
#>  $ X      : num  37 38 19 22 32 5 31 54 63 12 ...
#>  $ Y      : num  1 1 2 2 3 5 5 5 5 7 ...
barplot(
  table(grid_random$Species),
  ylab = "Count (no.)",
  space = 0.5
)
box()