A management procedure that makes incremental adjustments to TAC recommendations based on the apparent trend in recent surplus production. Based on the theory of Mark Maunder (IATTC)
SPslope(x, Data, reps = 100, plot = FALSE, yrsmth = 4, alp = c(0.9,
1.1), bet = c(1.5, 0.9))
A position in a data-limited methods data object
A data-limited methods data object
The number of stochastic samples of the MP recommendation(s)
Logical. Show the plot?
Years over which to smooth recent estimates of surplus production
Condition for modifying the Data (bounds on change in abundance)
Limits for how much the Data can change among years
An object of class Rec
with the TAC
slot populated with a numeric vector of length reps
See Online Documentation for correctly rendered equations
Note that this isn't exactly what Mark has previously suggested and is stochastic in this implementation.
The TAC is calculated as:
$$\textrm{TAC}_y =
\left\{\begin{array}{ll}
M \bar{C} & \textrm{if } r < \alpha_1 \\
\bar{C} & \textrm{if } \alpha_1 < r < \alpha_2 \\
\textrm{bet}_2 \textrm{SP} & \textrm{if } r > \alpha_2 \\
\end{array}\right.
$$
where \(r\) is the ratio of predicted biomass in next year to biomass in
current year \(\bar{C}\) is the mean catch over the last yrmsth
years, \(\alpha_1\)
and \(\alpha_2\) are specified in alp
, \(\textrm{bet}_1\) and \(\textrm{bet}_2\)
are specified in bet
, \(\textrm{SP}\) is estimated surplus production in most recent year,
and:
$$M = 1-\textrm{bet}_1 \frac{B_y - \tilde{B}_y}{B_y}$$
where \(B_y\) is the most recent estimate of biomass and \(\tilde{B}\)
is the predicted biomass in the next year.
http://www.iattc.org/Meetings/Meetings2014/MAYSAC/PDFs/SAC-05-10b-Management-Strategy-Evaluation.pdf
Other Surplus production MPs: Fadapt
,
Rcontrol
, SPMSY
,
SPSRA
, SPmod
# NOT RUN {
SPslope(1, Data=DLMtool::Atlantic_mackerel, plot=TRUE)
# }
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