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Length-Based SPR MPs

LBSPR.Rd

The spawning potential ratio (SPR) is estimated using the LBSPR method and compared to a target of 0.4.

Usage

LBSPR(
  x,
  Data,
  reps = 1,
  plot = FALSE,
  SPRtarg = 0.4,
  theta1 = 0.3,
  theta2 = 0.05,
  maxchange = 0.3,
  n = 5,
  smoother = TRUE,
  R = 0.2
)

LBSPR_MLL(
  x,
  Data,
  reps = 1,
  plot = FALSE,
  SPRtarg = 0.4,
  n = 5,
  smoother = TRUE,
  R = 0.2
)

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?

SPRtarg

The target SPR

theta1

Control parameter for the harvest control rule

theta2

Control parameter for the harvest control rule

maxchange

Maximum change in effort

n

Last number of years to run the model on.

smoother

Logical. Should the SPR estimates be smoothed?

R

variance of sampling noise for smoother

Value

An object of class Rec-class with the TAE slot populated

Details

Effort is modified according to the harvest control rules described in Hordyk et al. (2015b):

Functions

  • LBSPR_MLL: Fishing retention-at-length is set equivalent to slightly higher than the maturity curve if SPR < 0.4

Required Data

See Data-class for information on the Data object

LBSPR: CAL, CAL_bins, L50, L95, LHYear, MPeff, Mort, Year, vbK, vbLinf, wlb

Rendered Equations

See Online Documentation for correctly rendered equations

References

Hordyk, A., Ono, K., Valencia, S., Loneragan, N., and Prince J (2015a). A novel length-based empirical estimation method of spawning potential ratio (SPR), and tests of its performance, for small-scale, data-poor fisheries, ICES Journal of Marine Science, 72 (1), 217-231

Hordyk, A. R., Loneragan, N. R., & Prince, J. D. (2015b). An evaluation of an iterative harvest strategy for data-poor fisheries using the length-based spawning potential ratio assessment methodology. Fisheries Research, 171, 20-32. https://doi.org/10.1016/j.fishres.2014.12.018

Examples

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

#>   Effort 
#> 0.870804 
LBSPR_MLL(1, Data=MSEtool::SimulatedData, plot=FALSE)
#>       LR5       LFR 
#>  99.65718 104.90229