Islope1.Rd
A management procedure that incrementally adjusts the TAC to maintain a constant CPUE or relative abundance index.
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)
A position in the data object
A data object
The number of stochastic samples of the MP recommendation(s)
Logical. Show the plot?
Years over which to calculate index
A gain parameter controlling the speed in update in TAC.
Parameter controlling the fraction of mean catch to start using in first year
An object of class Rec-class
with the TAC
slot populated with a numeric vector of length reps
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.
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
See Online Documentation for correctly rendered equations
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
Islope1(1, MSEtool::SimulatedData, plot=TRUE)
#> TAC (median)
#> 1639.435
Islope2(1, MSEtool::SimulatedData, plot=TRUE)
#> TAC (median)
#> 1651.995
Islope3(1, MSEtool::SimulatedData, plot=TRUE)
#> TAC (median)
#> 1656.359
Islope4(1, MSEtool::SimulatedData, plot=TRUE)
#> TAC (median)
#> 1668.957