Generate predictions for the probability of occurrence

Generate predictions for the probability of occurrence (presence and/or absence) for a given taxon.

predict_occ_taxon(
  taxon,
  predictors,
  pa = "Present",
  limit = NULL,
  holdopt = NULL,
  dp = 3,
  append_predictors = TRUE
)

Arguments

taxon

The taxon_code, see elements::TaxonomicBackbone.

predictors

A data frame of predictors. Must include the following columns: L, M, N, R, S, SD, GP, bio05, bio06, bio16, and bio17

pa

One of "Present", "Absent", or c("Present", "Absent").

limit

A string representing the niche width quantiles, one of "min_max", "q01_q99", "q05_q95", "q10_q90", "q25_q75". Which if set assigns a probability of 0 to the Present column and/or 1 to the Absent column to a set of predictors if one or more of those predictors are outside the stipulated quantile ranges. Optional.

holdopt

Hold one or more variables at their optimum values. NULL by default, else a vector of variable codes, e.g. c("SD", "GP").

dp

The number of decimal places to round the probability values to.

append_predictors

A boolean. If TRUE return the predictors data frame with the results in an additional column.

Value

A data frame containing the probability of occurrence (Present and/or Absent), if specified, appended to the predictors data.

Details

A number of optional arguments provide additional control over the use of the models. First, using the 'limit' argument the probabilities may be set to 0 if one or more of the predictor values are outside a stipulated quantile range, e.g. the 1% and 99% quantiles by setting the 'limit' argument to "q01_q99". This may be used to strictly enforce the assignment of probability values of 0. As the quantile values present in elements::NicheWidths are derived using all presences of each taxon in the EVA, they may better represent the upper and lower tolerances of a taxons ecological niche, especially for taxa where the presences were undersampled. Second, using the 'holdopt' argument one or more predictor variables can be held constant, e.g. to hold soil disturbance constant supply c("SD") to the 'holdopt' argument. This may be useful in instances where you wish to remove the influence of one or more variables on the model results.

NOTE: to use this function you must first run elements::startup()

Examples

if (FALSE) {
elements::startup()
elements::predict_occ_taxon(taxon = "stellaria_graminea", predictors = elements::ExampleData1, pa = "Present", limit = NULL, holdopt = c("SD", "GP"), dp = 3, append_predictors = TRUE)
elements::shutdown() 
}