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Sensitivity of niche breadth to the grouping radius

Source: R/coverage.R
radius_sensitivity.Rd

Groups sites with group_sites() at each radius and estimates niche breadth with niche_breadth(), showing how the number of sampling units, their completeness and the estimates change with the radius.

Usage

radius_sensitivity(
  data,
  species = NULL,
  site,
  habitat,
  abundance,
  effort = NULL,
  lon,
  lat,
  radii_km = c(0, 0.5, 1, 2, 5),
  linkage = "complete",
  ...
)

Arguments

data

Long-format data: one row per species x site x habitat.

species, site, habitat, abundance, effort

Long format: names of the columns holding species (optional; without it the data are one species), site (or other replicate), habitat, abundance (counts) and sampling effort (optional; without it every row has effort 1).

lon, lat

Names of the longitude and latitude columns (decimal degrees; one location per site).

radii_km

Radii (km) to compare.

linkage

"complete" or "single".

...

Passed to niche_breadth() (for example dim, n_boot; the default here is n_boot = 0).

Value

A tibble with one row per radius x species: radius_km, species (if given), n_units (sampling units with the species), complete_share (share of those units in which every habitat was sampled), nb_di, spillover_abundance, nb_dd and flags.

See also

group_sites()

Examples

set.seed(1)
d <- simulate_isodars(1.5, 1.5, 5, 5, n = 20, p_missing = 0.3,
                      format = "long")
xy <- data.frame(site = unique(d$site), lon = stats::runif(20, 0, 0.1),
                 lat = stats::runif(20, 0, 0.1))
d <- merge(d, xy)
radius_sensitivity(d, site = "site", lon = "lon", lat = "lat",
                   habitat = "habitat", abundance = "abundance",
                   radii_km = c(0, 2, 5), diagnostics = list(n_null = 0))
#> # A tibble: 3 × 7
#>   radius_km n_units complete_share nb_di spillover_abundance nb_dd flags        
#>       <dbl>   <int>          <dbl> <dbl>               <dbl> <dbl> <chr>        
#> 1         0      20          0.35  0.383                  25 0.743 ""           
#> 2         2      14          0.643 0.447                  16 0.736 "di_extrapol…
#> 3         5       6          1     0.390                 160 0.251 "few_sites, …