Function operator that creates a management procedure (MP) by combining an assessment model (function of class Assess) with
a harvest control rule (function of class HCR). The resulting function can then be tested in closed-loop simulation via
MSEtool::runMSE().
Use
make_MPto specify constant TAC between assessments; the frequency of assessments is specified inOM@interval.Use
make_projection_MPto set catches according to a schedule set by projections, specify assessment frequency in argumentassessment_intervaland ensure thatOM@interval <- 1.Use
make_interim_MPto use an interim procedure to adjust the TAC between assessments using an index (Huynh et al. 2020), with the frequency of assessments specified in argumentassessment_intervalwhen making the MP; ensure thatOM@interval <- 1.
Usage
make_interim_MP(
.Assess = "SCA",
.HCR = "HCR_MSY",
AddInd = "VB",
assessment_interval = 5,
type = c("buffer", "mean", "loess", "none"),
type_par = NULL,
diagnostic = c("min", "full", "none"),
...
)
make_projection_MP(
.Assess = "SCA",
.HCR = "HCR_MSY",
assessment_interval = 5,
Ftarget = expression(Assessment@FMSY),
proj_args = list(process_error = 1, p_sim = 1),
diagnostic = c("min", "full", "none"),
...
)
make_MP(.Assess, .HCR, diagnostic = c("min", "full", "none"), ...)Arguments
- .Assess
Assessment model, a function of class
Assess.- .HCR
Harvest control rule, a function of class
HCR. Currently not used in projection MPs.- AddInd
A vector of integers or character strings indicating the indices to be used in the assessment model. Integers assign the index to the corresponding index in Data@AddInd, "B" (or 0) represents total biomass in Data@Ind, "VB" represents vulnerable biomass in Data@VInd, and "SSB" represents spawning stock biomass in Data@SpInd. For the interim procedure, the function will use the first index in
AddInd.- assessment_interval
The time interval for when the assessment model is applied (number of years). In all other years, the interim procedure is applied.
- type
How the index is used to calculate the TAC in the interim procedure. See details.
- type_par
A control parameter for the interim procedure. See details.
- diagnostic
A character string describing if any additional diagnostic information from the assessment models will be collected during the closed-loop simulation.
"min"(minimal) will collect information on convergence (default) and"full"will also collect the model estimates of biomass and F generated by.Assess."none"skips this step.- ...
Additional arguments to be passed to
.Assessand.HCR.- Ftarget
An expression that the MP will evaluate to identify the F used in the projection. See projection and example.
- proj_args
Additional arguments for projection.
Details
make_interim_MP creates an MP that runs the interim procedure (updating the TAC according to index observations in between periodic
assessment intervals. Always ensure to set: OM@interval <- 1. The assessment frequency is specified in argument
assessment_interval.
In the year when the assessment is applied, the TAC is set by fitting the model and then running the harvest control rule. Between assessments,
the TAC is updated as
$$
\textrm{TAC}_{y+1} = C_{\textrm{ref}} (I_y + b \times s)/(I_{\textrm{ref}} + b \times s)
$$
where Cref is the TAC calculated from the most recent assessment, Iref is the value of the index when Cref was calculated
(see Equations 6 and 7 of Huynh et al. 2020). The value of I_y depends on type, with b and s equal zero unless
type = "buffer":
"buffer"-I_yis the most recent index withbis specifed bytype_par(default = 1), andsis the standard deviation of index residuals from the most recent assessment."mean"-I_yis the mean value of the index over the most recenttype_paryears (default = 3)."loess"-I_yis the most recent index predicted by a loess smoother applied over the entire time series of the index. Usetype_parto adjust thespanparameter (default = 0.75)."none"-I_yis the most recent index. Index values are not adjusted in the interim procedure.
References
Huynh et al. 2020. The interim management procedure approach for assessed stocks: Responsive management advice and lower assessment frequency. Fish Fish. 21:663–679. doi:10.1111/faf.12453
Examples
# \donttest{
# Interim MPs
MP_buffer_5 <- make_interim_MP(assessment_interval = 5)
MP_buffer_10 <- make_interim_MP(assessment_interval = 10)
OM <- MSEtool::testOM
OM@interval <- 1
MSE <- MSEtool::runMSE(OM, MPs = c("MP_buffer_5", "MP_buffer_10"))
#> ℹ Checking OM for completeness
#> ✔ Loading operating model
#> ✔ Optimizing for user-specified movement
#> ✔ Calculating MSY reference points for each year
#> ✔ Optimizing for user-specified depletion in last historical year
#> ✔ Calculating historical stock and fishing dynamics
#> ✔ Calculating per-recruit reference points
#> ✔ Calculating B-low reference points
#> ✔ Calculating reference yield - best fixed F strategy
#> ✔ Simulating observed data
#> ✔ Running forward projections
#> ✔ 1 / 2 Running MSE for MP_buffer_5
#>
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#>
#> ✔ 2 / 2 Running MSE for MP_buffer_10
#>
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#>
# }
# A statistical catch-at-age model with a 40-10 control rule
SCA_40_10 <- make_MP(SCA, HCR40_10)
# An SCA that will produce convergence diagnostics
SCA_40_10 <- make_MP(SCA, HCR40_10, diagnostic = "min")
# MP with an SCA that uses a Ricker stock-recruit function.
SCA_Ricker <- make_MP(SCA, HCR_MSY, SR = "Ricker")
show(SCA_Ricker)
#> function (x, Data, reps = 1, diagnostic = "min")
#> {
#> dependencies <- "Data@Cat, Data@Ind, Data@Mort, Data@L50, Data@L95, Data@CAA, Data@vbK, Data@vbLinf, Data@vbt0, Data@wla, Data@wlb, Data@MaxAge, Data@steep, Data@CV_Ind, Data@sigmaR, Data@CV_Cat, Data@Mort, Data@CV_Mort, Data@steep, Data@CV_steep, Data@vbLinf, Data@vbK, Data@vbt0, Data@wla, Data@wlb, Data@MaxAge, Data@L50, Data@L95"
#> do_Assessment <- SCA(x = x, Data = Data, SR = "Ricker")
#> Rec <- HCR_MSY(Assessment = do_Assessment, reps = reps)
#> if (diagnostic != "none")
#> Rec@Misc <- Assess_diagnostic(x, Data, do_Assessment,
#> include_assessment = FALSE)
#> if (!is.null(do_Assessment@info$Misc))
#> Rec@Misc <- c(Rec@Misc, do_Assessment@info$Misc)
#> return(Rec)
#> }
#> <environment: 0x557871c5a368>
#> attr(,"class")
#> [1] "MP"
# \donttest{
# TAC is calculated annually from triennial assessments with projections between
# assessments with F = 0.75 FMSY
# Projections by default assume no process error.
OM <- MSEtool::testOM
OM@interval <- 1
pMP <- make_projection_MP(SCA, assessment_interval = 3,
Ftarget = expression(0.75 * Assessment@FMSY),
proj_args = list(process_error = 1))
# }