ecometric_model_qual: Run an ecometric model for qualitative environmental...

In commecometrics: Ecometric Models of Trait–Environment Relationships at the Community Level

Run an ecometric model for qualitative environmental variables

Description

Builds an ecometric trait space for qualitative environmental variables, estimating the most probable category and the probability of each category at each trait bin combination. Also calculates prediction accuracy and anomalies for each point.

Usage

ecometric_model_qual(
  points_df,
  category_col,
  grid_bins_1 = NULL,
  grid_bins_2 = NULL,
  min_species = 3
)

Arguments

points_df	Output first element of the list from summarize_traits_by_point(). A data frame with columns: summ_trait_1, summ_trait_2, count_trait, and the environmental variable.
category_col	Name of the column containing the categorical trait.
grid_bins_1	Number of bins for the first trait axis. If NULL (default), the number is calculated automatically using Scott's rule via optimal_bins().
grid_bins_2	Number of bins for the second trait axis. If NULL (default), the number is calculated automatically using Scott's rule via optimal_bins().
min_species	Minimum number of species with trait data per point (default = 3).

Value

A list containing:

points_df	Filtered input data frame with the following added columns: bin_1 Bin assignment code for first trait axis. bin_2 Bin assignment code for second trait axis. prob_category Estimated probability of each environmental category per trait bin (e.g., prob_1, prob_2, etc.). observed_probability Probability assigned to the observed category for each point. predicted_probability Probability assigned to the predicted (most likely) category for each point. predicted_category Predicted environmental category for each point. correct_prediction Indicator for whether the predicted category matches the observed category ("Yes" or "No"). env_anom Difference between predicted and observed category probabilities.
eco_space	Raster-format data frame representing trait space bins with estimated environmental categories.
diagnostics	Summary stats about bin usage and data coverage.
settings	Metadata including the modeled trait.
prediction_accuracy	Overall percentage of correct predictions.

Examples

# Load internal data
data("geoPoints", package = "commecometrics")
data("traits", package = "commecometrics")
data("spRanges", package = "commecometrics")

# Step 1: Summarize trait values at sampling points
traitsByPoint <- summarize_traits_by_point(
  points_df = geoPoints,
  trait_df = traits,
  species_polygons = spRanges,
  trait_column = "RBL",
  species_name_col = "sci_name",
  continent = FALSE,
  parallel = FALSE
)

# Step 2: Run ecometric model using land cover class as qualitative variable
modelResult <- ecometric_model_qual(
  points_df = traitsByPoint$points,
  category_col = "vegetation",
  min_species = 3
)

# View the percentage of correctly predicted categories
print(modelResult$prediction_accuracy)

commecometrics documentation built on Aug. 8, 2025, 6:10 p.m.