LstepCE1: Step-wise Constant Effort

In DLMtool: Data-Limited Methods Toolkit

Step-wise Constant Effort

Description

A management procedure that incrementally adjusts the total allowable effort (TAE) according to the mean length of recent catches.

Usage

LstepCE1(
  x,
  Data,
  reps = 100,
  plot = FALSE,
  yrsmth = 5,
  stepsz = 0.05,
  llim = c(0.96, 0.98, 1.05)
)

LstepCE2(
  x,
  Data,
  reps = 100,
  plot = FALSE,
  yrsmth = 5,
  stepsz = 0.1,
  llim = c(0.96, 0.98, 1.05)
)

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 trend in mean length.
stepsz	Parameter controlling the size of update increment in effort.
llim	A vector of length reference points that determine the conditions for increasing, maintaining or reducing the effort.

Details

The TAE is calculated as:

\textrm{TAE} = ≤ft\{\begin{array}{ll} \textrm{TAE}^* - 2 S\textrm{TAE}^* & \textrm{if } r < 0.96 \\ \textrm{TAE}^* - S \textrm{TAE}^* & \textrm{if } r < 0.98 \\ \textrm{TAE}^* & \textrm{if } > 1.058 \\ \end{array}\right.

where \textrm{TAE}^* is effort in the previous year, S is step-size determined by stepsz, and r is the ratio of L_\textrm{recent} and L_\textrm{ave} which are mean length over the most recent yrsmth years and 2 x yrsmth historical years respectively.

The conditions are specified in the llim argument to the function.

Value

An object of class Rec-class with the TAE slot(s) populated

Functions

• LstepCE1: The least biologically precautionary effort-based MP.

• LstepCE2: Step size is increased to 0.1

Required Data

See Data-class for information on the Data object

LstepCE1: LHYear, ML, MPeff, Year

Rendered Equations

See Online Documentation for correctly rendered equations

Author(s)

T. Carruthers

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

LstepCC1

Examples

LstepCE1(1, Data=MSEtool::SimulatedData, plot=TRUE)
LstepCE2(1, Data=MSEtool::SimulatedData, plot=TRUE)

DLMtool documentation built on June 20, 2022, 5:14 p.m.