GB_slope {DLMtool} | R Documentation |
An MP similar to SBT1 that modifies a time-series of catch recommendations and aims for a stable catch rates.
GB_slope(x, Data, reps = 100, plot = FALSE, yrsmth = 5, lambda = 1)
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 |
Number of years for evaluating slope in relative abundance index |
lambda |
A gain parameter |
The TAC is calculated as:
\textrm{TAC}_y= C_{y-1} ≤ft(1+λ I\right)
where C_{y-1} is catch from the previous year, λ is a gain parameter, and I is
the slope of the linear regression of log Index (Data@Ind
) over the last
yrsmth
years.
The TAC is subject to the following conditions:
if next TAC > 1.2 last catch, then TAC = 1.2 last catch
if next TAC < 0.8 last catch, then TAC = 0.8 last catch
Note that this is my interpretation of their approach and is now stochastic. Currently it is generalized and is not 'tuned' to more detailed assessment data which might explain why in some cases it leads to stock declines.
An object of class Rec-class
with the TAC
slot populated with a numeric vector of length reps
See Data-class
for information on the Data
object
GB_slope
: Cat, Ind, Year
See Online Documentation for correctly rendered equations
T. Carruthers
Geromont, H.F. and Butterworth, D.S. 2014. Complex assessment or simple management procedures for efficient fisheries management: a comparative study. ICES J. Mar. Sci. doi:10.1093/icesjms/fsu017
Other Index methods:
GB_target()
,
Gcontrol()
,
ICI()
,
Iratio()
,
Islope1()
,
Itarget1_MPA()
,
Itarget1()
,
ItargetE1()
GB_slope(1, MSEtool::SimulatedData, plot=TRUE)