Simulate_harvest_slots {SharkDemography}

Simulate_harvest_slots

Description

This is a wrapper function for 'Calculate_demography' which runs this function using different values of AAFC, AALC and F to simulate Havest Slot options. The Fcritical is retuned for each simulation to show the max level of F needed to sustain a stable population.

Usage

Simulate_harvest_slots(
  n,
  data,
  M.estimators = NULL,
  Age.mid.point = NULL,
  HS.width = NULL,
  max.F = 1
)

Arguments

n

number of iterations for each combination of Age.mid.point, HS.width and F.

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.

Age.mid.point

A vector of ages to be used in the simulation. Each age is used as a mid point and will have HS.Width subtracted and added to it to determine AAFC and AALC, respectively.

HS.width

A vector of widths for the Harvest slots in years. Widths are subtracted and added to mid points to determine the AAFC and AALC in each sim.

max.F

The maximum value of F for simulations

Value

A data.frame with three columns: MinAge, MaxAge and 'F.'. These represent the age at the start of a harvest slot, the age at the end of the harvest slot and the F for that harvest slot.

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 for different harvest slots 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_harvest_slots(n = 10, Silky_data,Age.mid.point = 0:28, HS.width = 0:8)