Skip to contents

Aggregate sites or rasters across grains (MAUP helpers)

geo_grain.Rd

Rebins point sites into square cells of one or more grain sizes and recomputes Hill numbers per cell, so users can see how richness patterns change with grain (Dungan et al. 2002; Wagner and Fortin 2005). Also aggregates SpatRaster layers with terra::aggregate() when raster is supplied. Recomputing Hill numbers needs the tidydiversity package.

Usage

geo_grain(
  data = NULL,
  grains,
  lon = lon,
  lat = lat,
  site = site,
  species = species,
  abundance = NULL,
  q = 0,
  raster = NULL,
  fun = "mean",
  .by = NULL
)

Arguments

data

Long community table with coordinates.

grains

Numeric vector of cell sizes in the same units as the coordinates (degrees for lon/lat, metres for local plots).

lon, lat, site, species, abundance

Column selections.

q

Hill-number orders passed to tidydiversity::div_hill().

raster

Optional SpatRaster to aggregate instead of (or as well as) the community table.

fun

Raster aggregation function ("mean", "sum", "modal", ...).

.by

Optional grouping columns preserved inside each grain.

Value

When data is supplied, a tibble (tmr_geo_grain) with columns grain, cell, coordinates of cell centres, and Hill estimates. When only raster is supplied, a named list of SpatRasters.

Examples

set.seed(1)
pts <- expand.grid(lon = seq(145, 145.4, by = 0.1),
                   lat = seq(-5.9, -5.5, by = 0.1))
pts$site <- paste0("s", seq_len(nrow(pts)))
com <- expand.grid(site = pts$site, species = paste0("sp", 1:8),
                   stringsAsFactors = FALSE)
com$abundance <- rpois(nrow(com), 2)
com <- dplyr::left_join(com, pts, by = "site")
geo_grain(com, grains = c(0.15, 0.3), q = 0)
#> # A tibble: 20 × 7
#>        q     n diversity grain   lon   lat cell          
#>    <dbl> <int>     <dbl> <dbl> <dbl> <dbl> <chr>         
#>  1     0    18         8  0.15  145. -5.92 144.975_-5.925
#>  2     0    16         7  0.15  145. -5.92 145.125_-5.925
#>  3     0    35         8  0.15  145. -5.92 145.275_-5.925
#>  4     0    17         7  0.15  145. -5.92 145.425_-5.925
#>  5     0    13         7  0.15  145. -5.78 144.975_-5.775
#>  6     0    13         6  0.15  145. -5.78 145.125_-5.775
#>  7     0    28         8  0.15  145. -5.78 145.275_-5.775
#>  8     0    32         8  0.15  145. -5.62 144.975_-5.625
#>  9     0    33         8  0.15  145. -5.62 145.125_-5.625
#> 10     0    67         8  0.15  145. -5.62 145.275_-5.625
#> 11     0    36         8  0.15  145. -5.62 145.425_-5.625
#> 12     0    23         8  0.15  145. -5.48 144.975_-5.475
#> 13     0    12         6  0.15  145. -5.48 145.125_-5.475
#> 14     0    28         8  0.15  145. -5.48 145.275_-5.475
#> 15     0    19         8  0.15  145. -5.48 145.425_-5.475
#> 16     0    19         7  0.15  145. -5.78 145.425_-5.775
#> 17     0    60         8  0.3   145. -5.85 145.05_-5.85  
#> 18     0    99         8  0.3   145. -5.85 145.35_-5.85  
#> 19     0   100         8  0.3   145. -5.55 145.05_-5.55  
#> 20     0   150         8  0.3   145. -5.55 145.35_-5.55