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Calculate Mean Year of Occurrence Over Time or Space

Source: R/indicator_wrappers.R
newness_map.Rd

This function estimates the relative newness of records in a data cube by calculating the mean year of occurrence over a gridded map or as a time series (see 'Details' for more information).

Usage

newness_map(data, ...)

newness_ts(data, ...)

Arguments

data

A data cube object (class 'processed_cube').

...

Arguments passed on to compute_indicator_workflow

ci_type

Type of bootstrap confidence intervals to calculate. (Default: "norm". Select "none" to avoid calculating bootstrap CIs.)

cell_size

Length of grid cell sides, in km. (Default: 10 for country, 100 for continent or world)

level

Spatial level: 'cube', 'continent', 'country', 'world', 'sovereignty', or 'geounit'. (Default: 'cube')

region

The region of interest (e.g., "Europe"). (Default: "Europe")

ne_type

The type of Natural Earth data to download: 'countries', 'map_units', 'sovereignty', or 'tiny_countries'. (Default: "countries")

ne_scale

The scale of Natural Earth data to download: 'small' - 110m, 'medium' - 50m, or 'large' - 10m. (Default: "medium")

output_crs

The CRS you want for your calculated indicator. (Leave blank to let the function choose a default based on grid reference system)

first_year

Exclude data before this year. (Uses all data in the cube by default.)

last_year

Exclude data after this year. (Uses all data in the cube by default.)

spherical_geometry

If set to FALSE, will temporarily disable spherical geometry while the function runs. Should only be used to solve specific issues. (Default is TRUE)

make_valid

Calls st_make_valid() from the sf package. Increases processing time but may help if you are getting polygon errors. (Default is FALSE).

num_bootstrap

Set the number of bootstraps to calculate for generating confidence intervals. (Default: 1000)

crs_unit_convert

Force a particular output CRS even when it has different units than the input CRS. (Default: FALSE)

shapefile_path

Path of an external shapefile to merge into the workflow. For example, if you want to calculate your indicator particular features such as protected areas or wetlands.

invert

Calculate an indicator over the inverse of the shapefile (e.g. if you have a protected areas shapefile this would calculate an indicator over all non protected areas)

Value

An S3 object with the classes 'indicator_map' or 'indicator_ts' and 'newness' containing the calculated indicator values and metadata.

Details

The mean year of occurrence is calculated per cell, giving an indication of how recent the data is for each cell. A recent mean year is not necessarily an indication of quality, as some countries or regions have been conducting comprehensive biodiversity monitoring for many years and will therefore reflect an older mean year of occurrence, while others may show a recent mean year due to e.g., the sudden availability of large amounts of citizen science data.

Functions

  • newness_map():

  • newness_ts():

See also

compute_indicator_workflow

Examples

if (FALSE) { # \dontrun{
n_map <- newness_map(example_cube_1, level = "country", region = "Denmark")
plot(n_map)
} # }
if (FALSE) { # \dontrun{
n_ts <- newness_ts(example_cube_1, first_year = 1985)
plot(n_ts)
} # }