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Index Slope Tracking MP

Islope1.Rd

A management procedure that incrementally adjusts the TAC to maintain a constant CPUE or relative abundance index.

Usage

Islope1(x, Data, reps = 100, plot = FALSE, yrsmth = 5, lambda = 0.4, xx = 0.2)

Islope2(x, Data, reps = 100, plot = FALSE, yrsmth = 5, lambda = 0.4, xx = 0.3)

Islope3(x, Data, reps = 100, plot = FALSE, yrsmth = 5, lambda = 0.4, xx = 0.4)

Islope4(x, Data, reps = 100, plot = FALSE, yrsmth = 5, lambda = 0.2, xx = 0.4)

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?

yrsmth

Years over which to calculate index

lambda

A gain parameter controlling the speed in update in TAC.

xx

Parameter controlling the fraction of mean catch to start using in first year

Value

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

Details

The TAC is calculated as: $$\textrm{TAC} = \textrm{TAC}^* \left(1+\lambda I \right)$$ where \(\textrm{TAC}^*\) is \(1-xx\) multiplied by the mean catch from the past yrsmth years for the first year and catch from the previous year in projection years, \(\lambda\) is a gain parameter, and \(I\) is the slope of log index over the past yrsmth years.

Functions

  • Islope1: The least biologically precautionary of the Islope methods

  • Islope2: More biologically precautionary. Reference TAC is 0.7 average catch

  • Islope3: More biologically precautionary. Reference TAC is 0.6 average catch

  • Islope4: The most biologically precautionary of the Islope methods. Reference TAC is 0.6 average catch and gain parameter is 0.2

Required Data

See Data-class for information on the Data object

Islope1: Cat, Ind, LHYear, Year

Rendered Equations

See Online Documentation for correctly rendered equations

References

Carruthers et al. 2015. Performance evaluation of simple management procedures. ICES J. Mar Sci. 73, 464-482.

Geromont, H.F., Butterworth, D.S. 2014. Generic management procedures for data-poor fisheries; forecasting with few data. ICES J. Mar. Sci. doi:10.1093/icesjms/fst232

See also

Other Index methods: GB_slope(), GB_target(), Gcontrol(), ICI(), Iratio(), Itarget1_MPA(), Itarget1(), ItargetE1()

Author

T. Carruthers

Examples

Islope1(1, MSEtool::SimulatedData, plot=TRUE)

#> TAC (median) 
#>     1636.087 
Islope2(1, MSEtool::SimulatedData, plot=TRUE)

#> TAC (median) 
#>     1629.304 
Islope3(1, MSEtool::SimulatedData, plot=TRUE)

#> TAC (median) 
#>     1644.498 
Islope4(1, MSEtool::SimulatedData, plot=TRUE)

#> TAC (median) 
#>     1677.275