Length Target TAE MP
LtargetE1.Rd
A management procedure that incrementally adjusts the TAE to reach a target mean length in catches.
Usage
LtargetE1(x, Data, reps = 100, plot = FALSE, yrsmth = 5, xL = 1.05)
LtargetE4(x, Data, reps = 100, plot = FALSE, yrsmth = 5, xL = 1.15)
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 mean length
- xL
Parameter controlling the magnitude of the target mean length of catches relative to average length in catches.
Value
An object of class Rec-class
with the TAE slot(s) populated
Details
Four target length MPs proposed by Geromont and Butterworth 2014. Tested by Carruthers et al. 2015.
The TAE is calculated as:
If \(L_\textrm{recent} \geq L_0\): $$\textrm{TAE} = 0.5 \textrm{TAE}^* \left[1+\left(\frac{L_\textrm{recent}-L_0}{L_\textrm{target}-L_0}\right)\right] $$
else: $$\textrm{TAE} = 0.5 \textrm{TAE}^* \left[\frac{L_\textrm{recent}}{L_0}^2\right] $$
where \(\textrm{TAE}^*\) is the effort in the previous year,
\(L_\textrm{recent}\) is mean length in last yrmsth
years, \(L_0\) is (except for L95target
) 0.9 average catch in the last
2 x yrsmth
historical (pre-projection years) (\(L_\textrm{ave}\)), and \(L_\textrm{target}\) is
(except for L95target
) xL
\(L_\textrm{ave}\).
Functions
LtargetE1
: The least biologically precautionary TAE-based MP.LtargetE4
: ThexL
argument is increased to 1.15.
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 Length target MPs:
Lratio_BHI()
,
Ltarget1()
Examples
LtargetE1(1, Data=MSEtool::SimulatedData, plot=TRUE)
#> Effort
#> 0.85
LtargetE4(1, Data=MSEtool::SimulatedData, plot=TRUE)
#> Effort
#> 0.85