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Population Model LTRE

Source: R/pop_model_ltre.R
pop_model_ltre.Rd

Run a LTRE for the population model

Usage

pop_model_ltre(
  step_size = 0.05,
  dose = NA,
  sr_wb_dat = NA,
  life_cycle_params = NA,
  HUC_ID = NA,
  n_reps = 100,
  stressors = NA,
  habitat_dd_k = NULL
)

Arguments

step_size

numeric. step size for ltre experiment parameter adjustment.

dose

dataframe. Stressor magnitude dataset imported from StressorMagnitudeWorkbook().

sr_wb_dat

list object. Stressor response workbook imported from StressorResponseWorkbook().

life_cycle_params

dataframe. Life cycle parameters.

HUC_ID

character. HUC_ID for the location unit. Can only be one HUC_ID (not an array).

n_reps

numeric. Number of replicates. Carlo simulations for the Population Model.

stressors

(optional) character vector of stressor names to include in the Population Model. Leave the default value as NA if you wish to include all stressors applicable to the population model.

habitat_dd_k

(optional) dataframe of location and stage-specific habitat capacity k values for the target species. If used this dataframe will override the capacity estimates

Details

Perturbs each life-cycle parameter up and down by step_size and compares mean lambda values across stochastic yearly projection matrices. Three design safeguards (added 2026-09-22): (1) all runs use s0_calibrate = FALSE, so lambda responds to the perturbation instead of being re-tuned to 1 by the fry-survival calibration; (2) the status-quo, increase, and decrease runs for every parameter share one random seed (common random numbers), so Monte-Carlo noise cancels in the increase-vs-decrease differences; (3) the stressors subset is forwarded to the underlying population-model runs.

Examples

if (FALSE) { # \dontrun{
library(CEMPRA)
# in prep
} # }