GB_target {DLMtool} R Documentation

## Geromont and Butterworth target CPUE and catch MP

### Description

An MP similar to SBT2 that modifies a time-series of catch recommendations and aims for target catch rate and catch level based on BMSY/B0 and MSY, respectively.

### Usage

GB_target(x, Data, reps = 100, plot = FALSE, w = 0.5)


### 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? w A gain parameter

### Details

The TAC is calculated as: If I_\textrm{recent} ≥q I_0:

\textrm{TAC}= C_\textrm{ref} ≤ft(w + (1-w)\frac{I_\textrm{rec}-I_0}{I_\textrm{target}-I_0} \right)

else:

\textrm{TAC}= wC_\textrm{ref} \frac{I_\textrm{rec}}{I_0}^2

where C_\textrm{ref} is a reference catch assumed to be a proxy for MSY (Data@Cref), w is a gain parameter, I_\textrm{rec} is the average index over the last 4 years, I_\textrm{target} is the target Index (Data@Iref), and I_0 is 0.2 x the average index over the past 5 years.

In the MSE C_\textrm{ref} is the calculated MSY subject to observation error defined in Obs@CV_Cref, and I_\textrm{target} is assumed to be the index at MSY subject to observation error (Obs@CV_Iref). Consequently, the performance of this method in the MSE is strongly determined by the specified uncertainty for these parameters.

The TAC is subject to the following conditions:

1. if next TAC > 1.2 last catch, then TAC = 1.2 last catch

2. if next TAC < 0.8 last catch, then TAC = 0.8 last catch

### Value

An object of class Rec-class with the TAC slot populated with a numeric vector of length reps

### Required Data

See Data-class for information on the Data object

GB_target: Cref, Ind, Iref

### Rendered Equations

See Online Documentation for correctly rendered equations

T. Carruthers

### References

Geromont, H.F. and Butterworth, D.S. 2014. Complex assessment or simple management procedures for efficient fisheries management: a comparative study. ICES J. Mar. Sci. doi:10.1093/icesjms/fsu017

Other Index methods: GB_slope(), Gcontrol(), ICI(), Iratio(), Islope1(), Itarget1_MPA(), Itarget1(), ItargetE1()
 GB_target(1, MSEtool::SimulatedData, plot=TRUE)