RF_U: Reference Fishery Mortalities (alternative)

In IMPRESSPROJECT/ModelingPopulation: Modeling of an exploited population (structured by age)

Description

Return the reference fishery mortality which produces maximum YPR (FM_type="F_max"), the reference fishery mortality at which the slope of the YPR curve is reduced to 0.1 of that estimated at the origin (FM_type="F_0.1") and the reference fishery mortality at which the MSY is attained (FM_type="F_msy"). Furthermore for each of these fishery mortalities the corresponding effort of fishing, YPR, BYR, B, Y and R in equilibrium is also returned. THIS FUNCTION IS EQUIVALENT TO RF FUNCTION, BUT THE IMPLEMENTATION IS A LITTLE DIFFERENT THEN DEPENDING ON THE NUMBERS OF ITERATIONS FOR WHICH THE REFERENCE FISHERY MORTALITIES MUST BE COMPUTED THIS RF_U CAN BE FASTER THAN THE RF FUNCTION IF YOU USE A CODE SIMILAR TO THE ONE IN THE EXAMPLE.

Usage

RF_U(Pop.Mod, Fish.years, Bio.years, Method, par, FM_type, iters)

Arguments

Pop.Mod	A list containing the components returned by Population.Modeling function (main function).
Fish.years	The number of recent years to estimate the mean of SEL (selectivity).
Bio.years	The number of recent years to estimate the mean of M, Mat, WC, and W (natural mortality, maturity, stock weight and capture weight).
Method	The procedure to obtain the age vector of weight (stock and captures), natural mortality, selectivity and maturity. By default is "mean" which means that the mean of the last "Bio.years" is used. The alternative option is "own", the user can introduce these elements.
par	If Method="own" it is a list containing the age vector of weight (stock and captures), natural mortality, selectivity and maturity (for the first iteration). In other case is equal to NULL.
FM_type	which of the three reference fishery mortalities must be computed. The possibilities have been described above: FM_type="F_max", FM_type="F_0.1" and FM_type="F_msy".
iters	A vector containing the iteration for which the reference fishery mortalities must be computed.

Details

The function returns the reference fishery mortality which produces maximum YPR (FM_type="F_max"), the reference fishery mortality at which the slope of the YPR curve is reduced to 0.1 of that estimated at the origin (FM_type="F_0.1") and the reference fishery mortality at which the MSY is attained (FM_type="F_msy"). Furthermore for each of these fishery mortalities the corresponding effort of fishing, YPR, BYR, B, Y and R in equilibrium is also returned. If the fishing effort is equal to 10 can be that optimize process had not found the correct value in the default sequence.

Value

One of the three following elements depending the above selection:

F_max:	the value of F that produces maximum YPR with the corresponding effort of fishing, YPR, BYR, B, Y and R in equilibrium.
F_0.1:	the value of F at which the slope of the YPR curve is reduced to 0.1 of that estimated at the origin with the corresponding effort of fishing, YPR, BYR, B, Y and R in equilibrium.
F_msy:	the value of F at which the MSY is attained with the corresponding effort of fishing, YPR, BYR, B, Y and R in equilibrium.

Author(s)

• Marta Cousido-Rocha

• Santiago Cerviño López

Examples

# If you desire to compute the reference fishery mortalities for a large number of iterations,
# example 1000, the following code using the RF_U function is faster than the one using the RF
# function directly. The basic idea of the code is to divide the task of computing the reference
# fishery mortalities for 1000 iterations in blocks of 20. This is the same that the RF function do
# internally but it is slower than do that outside of the package.
#library(abind)
#start_time <- Sys.time()
#n<-1000
#block<-n%/%20
#seq1<-c(0,(1:(block-1))*20)+1
#seq2<-seq(20,n,by=20)
#ll<-length(seq1)
#Resul<-array(0,dim=c(1,7,n))
#Pop.Mod2<-Pop.Mod
#for(i in 1:ll){
 # Pop.Mod2$Matrices$N<-Pop.Mod$Matrices$N[,,seq1[i]:seq2[i]]
 # Pop.Mod2$Matrices$F<-Pop.Mod$Matrices$F[,,seq1[i]:seq2[i]]
 # Pop.Mod2$Matrices$M<-Pop.Mod$Matrices$M[,,seq1[i]:seq2[i]]
 # Pop.Mod2$Matrices$W<-Pop.Mod$Matrices$W[,,seq1[i]:seq2[i]]
 # Pop.Mod2$Matrices$Mat<-Pop.Mod$Matrices$Mat[,,seq1[i]:seq2[i]]
 # Pop.Mod2$Matrices$C_N<-Pop.Mod$Matrices$C_N[,,seq1[i]:seq2[i]]
 # Pop.Mod2$Matrices$C_W<-Pop.Mod$Matrices$C_W[,,seq1[i]:seq2[i]]
 # Resul[,,seq1[i]:seq2[i]]<-RF_U(Pop.Mod2, 3,3,Method="mean",par=NULL,FM_type="F_max",iters =1:20)
 # }
 # end_time <- Sys.time()

IMPRESSPROJECT/ModelingPopulation documentation built on March 21, 2020, 12:14 a.m.