Run the Percentile Climate-Smart Approach

splnr_climate_percentileApproach() implements the Percentile Approach to climate-smart conservation planning by filtering features to their most climate-resilient areas and adjusting targets accordingly.

Usage

splnr_climate_percentileApproach(
  features,
  metric,
  targets,
  direction,
  percentile = 35,
  metric_col = "metric"
)

Arguments

features

An sf object of conservation features.

metric

An sf object with a column named metric.

targets

A data.frame with columns feature and target.

direction

1 or -1.

percentile

Numeric (0-100). Defaults to 35.

metric_col

A single character string giving the name of the column in metric that contains the climate metric values. Defaults to "metric" for backwards compatibility. Use this argument when your climate data column has a different name (e.g. "sst_trend").

Value

A list with:

• Features: sf object filtered to climate-smart occurrences.

• Targets: data.frame with adjusted targets.

Details

This function orchestrates two steps:

1. Preprocessing via splnr_climate_percentile_preprocess().

2. Target Assignment via splnr_climate_percentile_assignTargets().

Examples

if (FALSE) { # \dontrun{
initial_targets <- dat_species_bin %>%
  sf::st_drop_geometry() %>%
  colnames() %>%
  data.frame() %>%
  setNames(c("feature")) %>%
  dplyr::mutate(target = 0.3)

Percentile_result <- splnr_climate_percentileApproach(
  features   = dat_species_bin,
  metric     = dat_clim,
  targets    = initial_targets,
  direction  = 1,
  percentile = 35
)
out_sf_percentile <- Percentile_result$Features
targets_percentile <- Percentile_result$Targets
} # }