04: Production Function
FAO: Small Pelagics
L Kell
21 January, 2024
Introduction
- Identify and prioritise Objectivesand trade-offs
- Selection of Hypotheses
- Simulate Data
- Conditioning the Operating Model based on data and knowledge
- Identifying candidate management strategies
- Running the Management Procedure as a feedback controller to simulate the long-term impact of management
- Selection of the Management Strategy that best meets the Objectives
Packages
FLR
library(FLCore)
library(FLBRP)
library(FLasher)
library(FLife)
library(ggplotFL)
library(FLCandy)Plotting and Data wrangling
library(plyr)
library(dplyr)
library(reshape)library(ggplot2)
theme_set(theme_bw())
library(ggpubr)
library(ggcorrplot)
library(GGally)HCRs
eq=lhEql(lhPar(FLPar(linf=100,s=0.6)))
refpts(eq)=properties(eq)
plot(eq,panel=3)
eq1=eq
fbar(eq1)=FLQuant(rep(refpts(eq)[,"harvest",drop=T],each=101),
dimnames=dimnames(propagate(fbar(eq),7)))
om =as(eq1,"FLStock")
om =fwd(om,fbar=fbar(om)[,-1],sr=eq)
om1=iter(om,1)
om2=iter(om,2)
om3=iter(om,4)om1=fwd(om1,fbar=fbar(eq1)[,-1],sr=eq)
om2=fwd(om2,fbar=fbar(eq1)[,-1],sr=eq)
om3=fwd(om3,fbar=fbar(eq1)[,-1],sr=eq)
eq2=eq
fbar(eq2)=FLQuant(c(seq(0,1,length.out=21),
rep(1,50))*c(refpts(eq2)["msy","harvest"]))dat=rbind(cbind(What=2,model.frame(FLQuants(om2[,-1],SSB=ssb,Yield=catch),drop=T)),
cbind(What=3,model.frame(FLQuants(om3[,-1],SSB=ssb,Yield=catch),drop=T)))ggplot(dat)+
geom_line(aes(SSB,Yield),data=model.frame(FLQuants(eq,SSB=ssb,Yield=catch)))+
geom_path( aes(SSB,Yield,group=iter,col =ac(iter)))+
geom_point(aes(SSB,Yield,group=iter,fill=ac(iter)),shape=21,col="grey50")+
facet_grid(What~.)
hcr<-function(ssb,eq){
trgt=(ssb%=%1)%*%refpts(eq)["msy","harvest"]
rtn =(ssb%/%refpts(eq)["msy","ssb"])%*%refpts(eq)["msy","harvest"]
rtn=qmin(trgt,rtn)
dimnames(rtn)$year=ac(an(dimnames(rtn)$year)+1)
rtn}
om2.=iter(om2,1)
om3.=iter(om3,1)
for (iYr in dimnames(om1)$year[-dim(om1)[2]]){
om2.=fwd(om2.,fbar=hcr(ssb(om2.[,iYr]),eq),sr=eq)
om3.=fwd(om3.,fbar=hcr(ssb(om3.[,iYr]),eq),sr=eq)}
dat=rbind(cbind(What=2,model.frame(FLQuants(om2.[,-1],SSB=ssb,Yield=catch,F=fbar),drop=T)),
cbind(What=3,model.frame(FLQuants(om3.[,-1],SSB=ssb,Yield=catch,F=fbar),drop=T)))ggplot(dat)+
geom_line( aes(SSB,Yield),data=model.frame(FLQuants(eq,SSB=ssb,Yield=catch)))+
geom_path( aes(SSB,Yield,group=What),col="grey")+
geom_point(aes(SSB,Yield,group=What),shape=21)+
facet_grid(What~.)
More Information
- For more information on the FLR Project for Quantitative Fisheries Science in R, visit the FLR webpage 1.
Acknowledgements
Software Versions
R version 4.2.1 (2022-06-23)
knitr: 1.43
FLCore: 2.6.19.9105
FLBRP: 2.5.9.9022
FLasher: 0.7.1.9221
FLife: 3.4.0
ggplotFL: 2.7.0.9132
FLCandy: 0.1.0
rfishbase: 3.1.9.99
SPMpriors: 1.0.4
FishLife: 3.0.0
plyr: 1.8.9
dplyr: 1.1.4
reshape: 0.8.9
ggplot2: 3.4.4
ggpubr: 0.6.0
ggcorrplot: 0.1.3
GGally: 2.1.2
Compiled: Sun Jan 21 12:40:24 2024