Simulate_F_critical {SharkDemography}

Estimate F critical through simulations

Description

This is a wrapper function for 'Calculate_demography' which runs this function the specified number of times using a range of F values accross the enture age range of the population. This determines the rate of population increase at each increment of F.

Usage

Simulate_F_critical(
  n = 1000,
  .data,
  M.estimators = NULL,
  max.F = 0.3,
  n_cores = 1
)

Arguments

n

The number of simulations to be run. 1000 is recomended but smaller numbers should be run when testing to avoid long run times.

.data

A multi-level list of the class 'Demography.inputs' produced from the 'create_data_input' function and then manually completed.

M.estimators

Any specific natural mortality estimators to be included in the analysis. Only one will be used in each run which is randomly selected. Must be a single estimator or a vector of estimators. These can include: "Pet.Wro","Jensen.mat","Chen.Yuan", "Then_hoenig","Then_pauly", "Jensen.mat","Charnov" or "Chen.Want". If none are specified then all applicable estimators could be chosen.

max.F

The maximum value of F for simulations

n_cores

The number of cores to be used for parallel processing. It should be 1 core less than the maximum number available.

Value

A list with two data.frames. The first provides the mean F critical with 95% confidence intervals. The second dataframe provides the rate of increase for each increment of F.

Examples

# load Silky shark data produced by create_data_input()
# Type `?create_data_input()` for details
data("Silky_data")

# Run function to get conduct an F critical analysis using
# Monte Carlo Simulations using for all available natural mortality estimators.
# Set n = at least 1000 for full analysis but use n = 10 for testing given long run times

Simulate_F_critical(n = 10, Silky_data, n_cores = 1)