Length Target TAE MP

A management procedure that incrementally adjusts the TAE to reach a target mean length in catches.

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: The xL argument is increased to 1.15.

Required Data

See Data-class for information on the Data object

LtargetE1: LHYear, ML, MPeff, 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

Author

T. Carruthers

Examples

LtargetE1(1, Data=MSEtool::SimulatedData, plot=TRUE)

#> Effort 
#>   0.85 
LtargetE4(1, Data=MSEtool::SimulatedData, plot=TRUE)

#> Effort 
#>   0.85