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Several reference MPs for your operating model to use in the management strategy evaluation. FMSYref (and related) assume perfect information about FMSY (FMSY is taken from the operating model stored at Data@Misc$ReferencePoints$ByYear$FMSY), and set an effort limit (TAE) so that F=FMSY (or some fraction of FMSY) in each year the MP is applied. NFref sets annual catch to zero and is used for looking at variability in stock with no fishing.

Usage

FMSYref(x, Data, reps = 100, plot = FALSE)

FMSYref50(x, Data, reps = 100, plot = FALSE)

FMSYref75(x, Data, reps = 100, plot = FALSE)

NFref(x, Data, reps = 100, plot = FALSE)

curEref(x, Data, reps = 100, plot = FALSE)

Arguments

x

A position in the data object

Data

A data object

reps

The number of stochastic samples of the MP recommendation(s)

plot

Logical. Show the plot?

Value

An object of class Rec with the TAC slot populated with a numeric vector of length reps

Details

Note that you can out-perform FMSYref easily. The requirement for fixed F is actually quite strict and is by no means the upper limit in terms of yield. Don't panic if your method beats this one for yield, especially for short-lived species of high temporal variability in productivity!

Functions

  • FMSYref(): A reference FMSY method that fishes at FMSY

  • FMSYref50(): A reference FMSY method that fishes at 50% of FMSY

  • FMSYref75(): A reference FMSY method that fishes at 75% of FMSY

  • NFref(): A reference MP that sets annual catch to almost zero (1e-15)

  • curEref(): A reference MP that keeps fishing effort at the level of the last historical year

Required Data

See Data for information on the Data object

Author

T. Carruthers, A. Hordyk

Examples

FMSYref(1, MSEtool::SimulatedData, plot=TRUE)
#>   Effort 
#> 1.888558 
FMSYref50(1, MSEtool::SimulatedData, plot=TRUE)
#>    Effort 
#> 0.9442788 
FMSYref75(1, MSEtool::SimulatedData, plot=TRUE)
#>   Effort 
#> 1.416418 
NFref(1, MSEtool::SimulatedData, plot=TRUE)

#> TAC (median) 
#>        1e-15 
curEref(1, MSEtool::SimulatedData)
#> Effort 
#>      1