evaluate_range_map: Evaluate S4DM range map quality

In bmaitner/pbsdm: Small Sample Size Species Distribution Modeling

Evaluate S4DM range map quality

Description

This function uses 5-fold, spatially stratified, cross-validation to evaluate distribution model quality.

Usage

evaluate_range_map(
  occurrences,
  env,
  method = NULL,
  presence_method = NULL,
  background_method = NULL,
  bootstrap = "none",
  bootstrap_reps = 100,
  quantile = 0.05,
  constraint_regions = NULL,
  background_buffer_width = NULL,
  standardize_preds = TRUE,
  ...
)

Arguments

occurrences	Presence coordinates in long,lat format.
env	Environmental SpatRaster(s)
method	Optional. If supplied, both presence and background density estimation will use this method.
presence_method	Optional. Method for estimation of presence density.
background_method	Optional. Method for estimation of background density.
bootstrap	Character. One of "none" (the default, no bootstrapping), "numbag" (presence function is bootstrapped), or "doublebag" (presence and background functions are bootstrapped).
bootstrap_reps	Integer. Number of bootstrap replicates to use (default is 100)
quantile	Quantile to use for thresholding. Default is 0.05 (5 pct training presence). Set to 0 for minimum training presence (MTP).
constraint_regions	See get_env_bg documentation
background_buffer_width	Numeric or NULL. Width (meters or map units) of buffer to use to select background environment. If NULL, uses max dist between nearest occurrences.
standardize_preds	Logical. Should environmental layers be scaled? Default is TRUE.
...	Additional parameters passed to internal functions.

Details

Current plug-and-play methods include: "gaussian", "kde","vine","rangebagging", "lobagoc", and "none". Current density ratio methods include: "ulsif", "rulsif".

Value

A list containing 1) a data.frame containing cross-validated model performance statistics (fold_results), and 2) a data.frame containing model performance statistics evaluated on the full dataset (overall_results).

Note

Either method or both presence_method and background_method must be supplied.

Examples

{

# load in sample data

 library(S4DM)
 library(terra)

 # occurrence points
   data("sample_points")
   occurrences <- sample_points

 # environmental data
   env <- rast(system.file('ex/sample_env.tif', package="S4DM"))

 # rescale the environmental data

   env <- scale(env)

# Evaluate a gaussian/gaussian model calculated with the numbag approach
# using 10 bootstrap replicates.

 evaluate_range_map(occurrences = occurrences,
                    env = env,
                    method = NULL,
                    presence_method = "gaussian",
                    background_method = "gaussian",
                    bootstrap = "numbag",
                    bootstrap_reps = 10,
                    quantile = 0.05,
                    constraint_regions = NULL,
                    background_buffer_width = 100000)



}

bmaitner/pbsdm documentation built on Feb. 8, 2025, 2:27 p.m.