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 methodsIslope2
: More biologically precautionary. Reference TAC is 0.7 average catchIslope3
: More biologically precautionary. Reference TAC is 0.6 average catchIslope4
: The most biologically precautionary of the Islope methods. Reference TAC is 0.6 average catch and gain parameter is 0.2
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
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