In laurieKell/mydas-pkg: 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=4,
               fig.width =6,
               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

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

library(popbio)

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

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(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

LB-SPR

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

ak=alk(lh,cv=0.1)    

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

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"])*1.5))

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

source('~/Desktop/sea++/mydas/pkg/R/lbspr.R')

prior=popdyn(lh)
lb=lbspr(lfd,prior)  

lb=lbspr(lfd[,ac(25:50)],prior)  
plot(as.FLQuant(lb["FM"]))
plot(fbar(om[,ac(25:50)]))

par=rbind(lh,prior["mk"])

fwd.lbspr(par,1)

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.

par=rbind(lh,prior["mk"])

fwd.lbspr(par,1)

fwd.lbspr(propagate(par,2),1)

plot(fbar(om)/m(om)["4"])

prior  =popdyn(lh)
effort=fbar(om)%/%apply(fbar(om),6,mean)

obs=as.FLQuant(ddply(melt(lfd),.(year,iter), with,data.frame(data=sum(as.numeric(len)*value)/sum(value))))

hat=maply(data.frame(year=30:65), function(year){
    lb=FLQuant(lbspr(window(lfd,end=year),prior))
    q=apply(lb["FM"]%/%effort[,dimnames(lb["FM"])$year],6,mean)
    hat=effort[,ac(iyr+1)]%*%q
    fwd.lbspr(par,c(hat))}) 
hat=as.FLQuant(transmute(melt(obs),year=year,params=params,data=value))

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.

laurieKell/mydas-pkg documentation built on Nov. 8, 2019, 10:58 p.m.