DLMtool (version 5.2)

LstepCE1: 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 a data-limited methods data object

Data

A data-limited methods data object

reps

The number of stochastic samples of the MP recommendation(s)

plot

Logical. Show the plot?

yrsmth

Years over which to smooth recent estimates of surplus production

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.

Value

An object of class Rec 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 for information on the Data object

LstepCE1: LHYear, ML, MPeff, Year

Rendered Equations

See Online Documentation for correctly rendered equations

Details

The TAE is calculated as: $$\textrm{TAE} = \left\{\begin{array}{ll} \textrm{TAE}^* - 2 S\textrm{TAE}^* & \textrm{if } r < 0.96 \\ \textrm{TAE}^* - S \textrm{TAE}^* & \textrm{if } r < 0.98 \\ \textrm{TAE}^* & \textrm{if } > 1.058 \\ \end{array}\right. $$ 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.

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

# NOT RUN {
LstepCE1(1, Data=DLMtool::SimulatedData, plot=TRUE)
LstepCE2(1, Data=DLMtool::SimulatedData, plot=TRUE)
# }