In flr/mydas: Tools for conducting Management Strategy Evaluation for data limited stocks

library(knitr)
## Global options
opts_chunk$set(cache     =TRUE,
               cache.path='cache/performance/',
               echo      =TRUE,
               eval      =TRUE,
               prompt    =FALSE,
               comment   =NA,
               message   =FALSE,
               warning   =FALSE,
               tidy      =FALSE,
               fig.height=6,
               fig.width =8,
               fig.path  ='tex/performance-')

iFig=0

options(digits=3)

Load Libraries

library(plyr)
library(reshape)
library(ggplot2)

library(FLCore)
library(FLasher)
library(FLBRP)
library(FLife)
library(mydas)

options(scipen = 999)

library(DBI)
library(RPostgreSQL)
drv  = dbDriver("PostgreSQL")

con  = dbConnect(drv, host = 'postgresql-seascope.csffkpr9jjjn.eu-west-2.rds.amazonaws.com',
                 dbname='FLRout',
                 port = 5432,
                 user = 'MydasApplication',
                 password = 'gmit2017!')
mpb  = dbGetQuery(con1, paste("select* from mpb where spp = 'turbot' and year < 94"))

ss_labels = c("0.7"="Ftar=0.7", "1"="Ftar=1")
ggplot(mpb, aes(as.factor(year), ssb/msy_ssb,fill=as.factor(btrig)))+
      geom_boxplot(outlier.size=0.1, position=position_dodge(1),width=0.8, lwd=0.05, notch=TRUE)+
      stat_summary(fun.y=mean, geom="line", aes(group=1))+
      geom_hline(aes(yintercept=1), size=0.75, colour= "red", linetype="dashed")+ 
      facet_wrap(~ftar,ncol=1, labeller = labeller(ftar = ss_labels),scale="free_y") + theme_bw() +
      theme(panel.grid.major = element_blank(),
      text = element_text(size=14),
      panel.grid.minor = element_blank(),
      strip.background = element_blank(),
      panel.border = element_rect(colour = "black"),
      legend.position="bottom") + 
      scale_colour_manual(values=c("white", "#56B4E9"), labels=c("0.5","0.6"))  + 
      scale_fill_manual(name=expression(B[trig]),values=c("white", "#56B4E9"), labels=c("0.5","0.6")) + 
      scale_x_discrete(breaks = c(50,60,70,80,90))+
      scale_y_continuous(breaks = c(0:5))+
      xlab("year")+ylab(expression(B/B[MSY]))

ggplot(mpb, aes(as.factor(year), catch/msy_yield,fill=as.factor(btrig)))+
      geom_boxplot(outlier.size=0.1, position=position_dodge(1),width=0.8, lwd=0.05, notch=TRUE)+
      stat_summary(fun.y=mean, geom="line", aes(group=1))+
      geom_hline(aes(yintercept=1), size=0.75, colour= "red", linetype="dashed")+ 
      facet_wrap(~ftar,ncol=1, labeller = labeller(ftar = ss_labels),scale="free_y") + theme_bw() +
      theme(panel.grid.major = element_blank(),
      text = element_text(size=14),
      panel.grid.minor = element_blank(),
      strip.background = element_blank(),
      panel.border = element_rect(colour = "black"),
      legend.position="bottom") + 
      scale_colour_manual(values=c("white", "#56B4E9"), labels=c("0.5","0.6"))  + 
      scale_fill_manual(name=expression(B[trig]),values=c("white", "#56B4E9"), labels=c("0.5","0.6")) + 
      scale_x_discrete(breaks = c(50,60,70,80,90))+
      scale_y_continuous(breaks = c(0:5))+
      xlab("year")+ylab(expression(catch/catch[MSY]))

ggplot(mpb,aes(as.factor(year), fbar/msy_harvest,fill=as.factor(btrig)))+
      geom_boxplot(outlier.size=0.1, position=position_dodge(1),width=0.8, lwd=0.05, notch=TRUE)+
      stat_summary(fun.y=mean, geom="line", aes(group=1))+
      geom_hline(aes(yintercept=1), size=0.75, colour= "red", linetype="dashed")+ 
      facet_wrap(~ftar,ncol=1, labeller = labeller(ftar = ss_labels),scale="free_y") + theme_bw() +
      theme(panel.grid.major = element_blank(),
      text = element_text(size=14),
      panel.grid.minor = element_blank(),
      strip.background = element_blank(),
      panel.border = element_rect(colour = "black"),
      legend.position="bottom") + 
      scale_colour_manual(values=c("white", "#56B4E9"), labels=c("0.5","0.6"))  + 
      scale_fill_manual(name=expression(B[trig]),values=c("white", "#56B4E9"), labels=c("0.5","0.6")) + 
      scale_x_discrete(breaks = c(50,60,70,80,90))+
      scale_y_continuous(breaks = c(0:5))+
      xlab("year")+ylab(expression(f/f[MSY]))

data(om)

plot(om,iter=7:9)

Figure r iFig=iFig+1; iFig Operating model example for turbot with indiviual random Monte Carlo simulations.

data(eq)

plot(FLQuants(window(om,30),
             F  =function(x) fbar(x)%/%fmsy(eq),
             SSB=function(x) ssb(x)%/%bmsy(eq))
             ,iter=7:9)+
             xlab("Year")

Figure r iFig=iFig+1; iFig Operating model example F and SSB relative to $F_{MSY}$ and $B_{MSY}$, with indiviual random Monte Carlo simulations.

head(omSmry(om))

head(omSmry(om,eq))

lh=FLPar(c(a=0.01111,b=3.15))

head(omSmry(om,eq,lh))

stats=omSmry(om,eq,lh)

library(dplyr)

plot(FLQuants(ssb =as.FLQuant(transmute(stats,data=ssb, year=year,iter=iter)),
              sln =as.FLQuant(transmute(stats,data=sln, year=year,iter=iter)),
              sage=as.FLQuant(transmute(stats,data=sage,year=year,iter=iter)),
              swt =as.FLQuant(transmute(stats,data=swt, year=year,iter=iter))),
     iter=7)

Figure r iFig=iFig+1; iFig Indicators for ssb.

plot(FLQuants(biomass=as.FLQuant(transmute(stats,data=stock, year=year,iter=iter)),
              cln    =as.FLQuant(transmute(stats,data=cln,     year=year,iter=iter)),
              cage   =as.FLQuant(transmute(stats,data=cage,    year=year,iter=iter)),
              cwt    =as.FLQuant(transmute(stats,data=cwt,     year=year,iter=iter))),
     iter=7)