DLMtool (version 6.0.3)

Islope1: Index Slope Tracking MP

Description

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

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

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.

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()

Examples

# NOT RUN {
Islope1(1, MSEtool::SimulatedData, plot=TRUE)
Islope2(1, MSEtool::SimulatedData, plot=TRUE)
Islope3(1, MSEtool::SimulatedData, plot=TRUE)
Islope4(1, MSEtool::SimulatedData, plot=TRUE)
# }