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Flag records that are close to each other in the enviromnetal space

Source: R/thin_env.R
thin_env.Rd

Flags occurrence records for thinning by keeping only one record per species within the same environmental block/bin.

Usage

thin_env(
  occ,
  species = "species",
  long = "decimalLongitude",
  lat = "decimalLatitude",
  env_layers,
  n_bins = 5,
  prioritary_column = NULL,
  decreasing = TRUE,
  flag_for_NA = FALSE
)

Arguments

occ

(data.frame or data.table) a data frame containing the occurrence records. Must contain columns for species, longitude, and latitude.

species

(character) the name of the column in occ that contains the species scientific names. Default is "species".

long

(character) the name of the column in occ that contains the longitude values. Default is "decimalLongitude".

lat

(character) the name of the column in occ that contains the latitude values. Default is "decimalLatitude".

env_layers

(SpatRaster) object containing environmental variables.

n_bins

(numeric) number of bins into which each environmental variable will be divided.

prioritary_column

(character) name of a numeric columns in occto define retention priority (e.g., quality score, year). See details.

decreasing

(logical) whether to sort records in decreasing order using the prioritary_column (e.g., from most recent to oldest when the variable is "year"). Only applicable when prioritary_column is not NULL. Default is TRUE.

flag_for_NA

(logical) whether to treat records falling in NA cells of env_layers as passing (TRUE) or failing (FALSE) this test. Default is FALSE.

Value

The original occ data frame with two additional columns:

  • thin_env_flag: logical indicating whether each record was retained (TRUE) or flagged as redundant (FALSE). As with all other flagging functions in RuHere, TRUE indicates that the record passed this test and is eligible for retention; FALSE indicates it failed and is flagged as potentially problematic, and can be removed using remove_flagged().

  • bin: environmental bin ID assigned to each record. Each component of the ID corresponds to the bin of one environmental variable.

Details

This function used get_env_bins() to create a multidimensional grid in environmental space by splitting each environmental variable into n_bins equally sized intervals. Records falling into the same environmental bin are considered redundant; only one is kept (based on retention priority when provided), and the remaining records are flagged.

Examples

# Load example data
data("occurrences", package = "RuHere")
# Get only occurrences from Araucaria
occ <- occurrences[occurrences$species == "Araucaria angustifolia", ]
# Load example of raster variables
data("worldclim", package = "RuHere")
# Unwrap Packed raster
r <- terra::unwrap(worldclim)
# Flag records that are close to each other in the enviromnetal space
occ_env_thin <- thin_env(occ = occ, env_layers = r)
# Number of flagged (redundant) records
sum(!occ_env_thin$thin_env_flag) #Number of flagged records
#> [1] 867