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

library(knitr)
source("R/ini.R")

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

options(digits=3)

iFig=0

Introduction

This tutorial describes how to simuation test data limited methods in FLR using a variety of other packages.

Required packages

To follow this tutorial you should have installed the following packages:

• FLR: FLCore, FLBRP, FLasher, FLife

for example

install.packages(c("FLCore"),  repos="http://flr-project.org/R")
install.packages(c("FLBRP"),   repos="http://flr-project.org/R")
install.packages(c("FLasher"), repos="http://flr-project.org/R")
install.packages(c("FLife"),   repos="http://flr-project.org/R")

# Load  packages
library(ggplot2)
library(plyr)
library(reshape)

library(FLCore)
library(ggplotFL)
library(FLBRP)
library(FLasher)
library(FLife)

library(MLZ)

Operating Model

Turbot

lh=FLPar(c(linf= 59.1,  k=0.28, t0=-0.4, a=0.01111,b=3.15,a50=4.0, l50=43.25),units="NA")
lh=lhPar(lh)
eq=lhEql(lh)

gTime=c(round(mydas:::gt(eq)))
fbar(eq)=refpts(eq)["msy","harvest"]%*%FLQuant(c(rep(.1,19),
                                              seq(.1,2,length.out=30)[-30],
                                              seq(2,1.0,length.out=gTime)[-1],
                                              rep(1.0,61)))[,1:105]

om=as(eq,"FLStock")
om=fwd(om,f=fbar(om)[,-1], sr=eq)

plot(FLQuants(om, 
          "f" =   function(x) fbar(x)%/%refpts(eq)["msy","harvest"], 
          "ssb" = function(x) ssb(x)%/%refpts( eq)["msy","ssb"], 
          "catch"=function(x) landings(x)%/%refpts(eq)["msy","yield"],
          "rec" = function(x) rec(x)%/%refpts( eq)["msy","rec"])) + 
  geom_hline(aes(yintercept=1),col="red",linetype=2)+
  theme_bw() 

Figure r iFig=iFig+1; iFig Time series relative to MSY benchmarks.

Length Based Methods

Based on Beverton and Holt $L_{F} = \frac{L\infty +\frac{F+M}{K}L_c}{1+\frac{F+M}{K}}$

• $L_{current}/L_{F=M}$
• $M/(Z_{current}-M)$
• $F_{0.1}/(Z_{current}-M)$
• $LBSPR$ Length-based spawning potential ratio (Hordyk et al. 2015)
• $Lime$ (Rudd and Thorson, 2018) mixed effects non-equilibrium

MLZ

MLZ is a package that facilitates data preparation and estimation of mortality with statistical diagnostics using the mean length-based mortality estimator and several extensions.

library(MLZ)

library(popbio)

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

ts   =mydas:::omSmry(om,eq,lh)
mnLen=as.FLQuant(with(ts,data.frame(data=cln,year=year,iter=iter)))

plot(mnLen)

Figure r iFig=iFig+1; iFig Mean length of catch turbot.

#source('~/Desktop/flr/mydas/R/popdyn.R')
#growth<-vonB
prior=mydas:::popdyn(lh)

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

res=mydas:::mlz(mnLen[,ac(40:60)],prior)

res

LB-SPR

LBSPR is a R package for simulation and estimation using life-history ratios and length composition data

library(LBSPR)

ak=mydas:::invAlk(lh)  

lfd=mydas:::lenSample(catch.n(om)[,20:65],ak,nsample=500)

save(lfd,file="lfd.RData") 

ggplot(melt(lfd[,seq(1,45,10)]))+
  geom_histogram(aes(len,weight=value),binwidth=1)+
  facet_grid(year~iter,scale="free")+
  xlab("Length (cm)")+ylab("Frequency")+
  coord_cartesian(xlim=c(0,mean(lh["linf"])))

Figure r iFig=iFig+1; iFig Observation error model for turbot.

library(LBSPR)
library(mydas)
library(popbio)

#growth=vonB

prior=popdyn(lh)
#source("/home/laurence-kell/Desktop/flr/mydas/R/lbspr.R")

lb=mydas:::lbspr(lfd,prior)  

ggplot(melt(sweep(lb[["spr"]],c(1,3),lb[["spr"]][,"40"],"/")))+
  geom_boxplot(aes(ac(year),value))+
  scale_x_discrete(breaks=seq(20,60,10))+
  ylab("SPR")+xlab("Year")+theme_bw()

Figure r iFig=iFig+1; iFig Estimates of SPR for turbot.

ggplot(melt(sweep(lb[["fm"]],c(1,3),lb[["fm"]][,"40"],"/")))+
  geom_boxplot(aes(ac(year),value))+
  scale_x_discrete(breaks=seq(20,60,10))+
  ylab("F")+xlab("Year")+theme_bw()

Figure r iFig=iFig+1; iFig Estimates of $F/M$ for turbot.

References

More information

• You can submit bug reports, questions or suggestions on this tutorial at https://github.com/flr/doc/issues.
• Or send a pull request to https://github.com/flr/doc/
• For more information on the FLR Project for Quantitative Fisheries Science in R, visit the FLR webpage, http://flr-project.org.

Software Versions

• r version$version.string
• FLCore: r packageVersion('FLCore')
• FLasher: r packageVersion('FLasher')
• Compiled: r date()

License

This document is licensed under the Creative Commons Attribution-ShareAlike 4.0 International license.

Author information

Laurence KELL. [e-mail]

Acknowledgements

This vignette and the methods documented in it were developed under the MyDas project funded by the Irish exchequer and EMFF 2014-2020. The overall aim of MyDas is to develop and test a range of assessment models and methods to establish Maximum Sustainable Yield (MSY) reference points (or proxy MSY reference points) across the spectrum of data-limited stocks.

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