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

To provide advice on the status of data poor stocks ICES uses $MSY$ proxy reference points as part of a Precautionary Approach. Proxy reference point should be robust to uncertainty i.e. they should be able to detect with sufficient power whether a stock is below $B_{MSY}$ (over fished) or fishing mortality greater than $F_{MSY}$ (over fishing).

To identify robust proxy reference point therefore requires identifying the impact of the assumptions and knowledge on the relationship between the proxies and their data rich equivalents. To do this we use life history parameters based on turbot to compute and then compare $F_{MSY}$ and proxy reference points.

knitr::opts_chunk$set(echo = FALSE)

library(knitr)

opts_chunk$set(comment   =NA, 
               warning   =FALSE, 
               message   =FALSE, 
               error     =FALSE, 
               echo      =FALSE,
               fig.width =10, 
               fig.height=10,
               cache     =TRUE, 
               fig.path  ="tex/proxies-",
               cache.path="cache/proxies/")

iFig=0
iTab=0

library(FLCore)
library(FLife)
library(mydas)

library(popbio)
library(plyr)
library(dplyr)
library(reshape)
library(GGally)

data(teleost)
lh=lhPar(teleost[,"Psetta maxima"])
lh=propagate(lh,8)

dat=as(expand.grid(sel3=c(5000,5),
                   s   =c(0.75,0.9),
                   k   =0.28*c(1,0.5)),"FLPar")
lh[c("sel3","s","k")]=dat[c("sel3","s","k")]

#source('~/Desktop/flr/mydas/R/popdyn.R')

smry=popdyn(lh)

lh.lorenzen=lh
lh.lorenzen[c("m1","m2","m3")]=c(0.3,-0.288,NA)

eq=lhEql(lh.lorenzen,m="lorenzen")
smry.lorenzen=popdyn(lh.lorenzen,eq)

Figures

MSY reference points and proxies

dat=rbind(cbind(M="Gislason",model.frame(smry)),
          cbind(M="Lorenzen",model.frame(smry.lorenzen)))

ggpairs(dat[,c("M","fmsy","bmsy","msy","r","rc")],
        mapping = ggplot2::aes(color=as.character(M)),
        lower = list(continuous = wrap(mydas:::my_smooth)),
        diag=list(continuous=wrap(mydas:::my_density,alpha=0.2)),
        title = "")+
  theme(legend.position ="none",
        panel.grid.major =element_blank(),
        axis.ticks       =element_blank(),
        axis.text.x      =element_blank(),
        axis.text.y      =element_blank(),
        panel.border     =element_rect(linetype = 1, colour="black", fill=NA))+
  theme_bw(16)

Figure r iFig=iFig+1; iFig. Relationship between MSY reference points and population growth rate.

ggpairs(dat[,c("M","lopt","sln","mk","fm","lfm","spr0","fmsy")],
        mapping = ggplot2::aes(color=as.character(M)),
        lower = list(continuous = wrap(mydas:::my_smooth)),
        diag=list(continuous=wrap(mydas:::my_density,alpha=0.2)),  
        title = "")+
  theme(legend.position ="none",
        panel.grid.major =element_blank(),
        axis.ticks       =element_blank(),
        axis.text.x      =element_blank(),
        axis.text.y      =element_blank(),
        panel.border     =element_rect(linetype = 1, colour="black", fill=NA))+
  theme_bw(24)

Figure r iFig=iFig+1; iFig. Relationship between MSY reference points and their potential proxies.

idx=transform(merge(ind,refs[,c("slmsy","clmsy","lopt","lfm","iter")]),
              sln=sln/slmsy,cln=cln/clmsy,
              sl50=sln/l50,cl50=cln/l50,
              slopt=sln/lopt,clopt=cln/lopt,
              slfm =sln/lfm,clfm=cln/lfm,
              fmsy=fbar/msy_harvest)[,c("f","CV","AR","s","k","bg","sel3","fmsy",
            "sln","cln","sl50","cl50","slopt","clopt","slfm","clfm")]

dat=melt(idx,id=c("f","CV","AR","s","k","bg","sel3","fmsy"))

ggplot(dat)+
  geom_boxplot(aes(ac(f),value))+
  geom_hline(aes(yintercept=1),col="red")+
  facet_wrap(~variable,ncol=2)+
  xlab("F times FMSY")+ylab("Ratio with FMSY")

References {#References}

\newpage

Session Info

sessionInfo()

flr/mydas documentation built on Jan. 19, 2024, 10:33 a.m.