Calculate Biodiversity Indicators Over Space — calc

This function provides a flexible framework for calculating various biodiversity indicators on a spatial grid or as a time series. It prepares the data, creates a grid, calculates indicators, and formats the output into an appropriate S3 object ('indicator_map'). Specific implementations for different indicator types are provided using the appropriate wrappers.

Usage

# S3 method for class 'completeness'
calc_map(x, ...)

# S3 method for class 'hill0'
calc_map(x, ...)

# S3 method for class 'hill1'
calc_map(x, ...)

# S3 method for class 'hill2'
calc_map(x, ...)

# S3 method for class 'relative_occupancy'
calc_map(x, occ_type = 0, ...)

# S3 method for class 'obs_richness'
calc_map(x, ...)

# S3 method for class 'total_occ'
calc_map(x, ...)

# S3 method for class 'newness'
calc_map(x, newness_min_year = NULL, ...)

# S3 method for class 'spec_richness_density'
calc_map(x, ...)

# S3 method for class 'occ_density'
calc_map(x, ...)

# S3 method for class 'williams_evenness'
calc_map(x, ...)

# S3 method for class 'pielou_evenness'
calc_map(x, ...)

# S3 method for class 'ab_rarity'
calc_map(x, ...)

# S3 method for class 'area_rarity'
calc_map(x, ...)

# S3 method for class 'spec_occ'
calc_map(x, ...)

# S3 method for class 'spec_range'
calc_map(x, ...)

# S3 method for class 'tax_distinct'
calc_map(x, ...)

calc_map(x, ...)

Arguments

x

A data cube object ('processed_cube').

...

Additional arguments passed to specific indicator calculation functions.

occ_type

Integer controlling the occupancy denominator (default 0):

0 — Total-area occupancy: number of grid cells occupied by the species (across all years) / total number of grid cells in the study region (including unsampled cells). Presence-only caveat: empty cells cannot be assumed truly unoccupied; they may simply be unsampled.
1 — Relative-to-ever-occupied occupancy: species' cells / cells with at least one occurrence (any species, any year). Conditions on cells where sampling effort is documented.
2 — Temporal mean annual occupancy: for each year, compute the proportion of that year's occupied cells (any species) in which the species was recorded; then average those annual proportions across all years in the data. This captures how consistently a species occupies the active sampling footprint over time.

Note on presence-only data: All three types rely on presence-only records. A cell with no records cannot be assumed to be truly unoccupied. Types 1 and 2 condition on cells with documented occurrences, but those still reflect sampling effort rather than true species absence.

Note on cell aggregation: When a coarser cell_size is chosen, data are aggregated to coarser grid cells before this calculation. All denominators count post-aggregation cells (cellid).

newness_min_year

(Optional) If set, only shows values above this (e.g. 1970). Values below the minimum will be replaced with NA. This can be useful e.g. if you have outlier cells where the data is very old causing the legend gradient to stretch in a way that makes other cell values difficult to discern.

Value

An S3 object of the class 'indicator_map' containing the calculated indicator values and metadata.

Examples

observed_richness_map <- obs_richness_map(example_cube_1, level = "country",
                                          region = "Denmark")
plot(observed_richness_map)