inst/Updates/LFA34/2021/6.landingsEffortRelF.R

In LobsterScience/bio.lobster: Lobster Stock Assessment Tools for DFO Maritimes

#landings

require(bio.lobster)
require(PBSmapping)
la()


a = lobster.db('annual.landings')
b = lobster.db('seasonal.landings')
d = lobster.db('historic.landings')
l34 = c("YARMOUTH","DIGBY")
l35 = c("KINGS","ANNAPOLIS", "COLCHESTER" , "CUMBERLAND")
l36 = c('ALBERT','SAINT JOHN','CHARLOTTE')
l38 = c('CHARLOTTE')

d$LFA = ifelse(d$COUNTY %in% l34, 'LFA34',NA)
d = subset(d, !is.na(LFA))
d = aggregate(LANDINGS_MT~SYEAR+LFA,data=d,FUN=sum)
d = subset(d, SYEAR<1947)

names(d) = c('YR','LFA','LAND')

b$YR = substr(b$SYEAR,6,9)
a = subset(a,YR<1976)
b = subset(b,YR>1975 )
fpf1 = file.path(project.figuredirectory('bio.lobster'),"LFA34Update")

LFA = c('LFA34')
for(i in LFA){
		aa = a[,c('YR',i)]
		bb = b[,c('YR',i)]
		dd = subset(d,LFA==i)
		dd$LFA <- NULL
		names(dd)[2] <- i
		aa = rbind(rbind(aa,bb),dd)
		aa = aa[order(aa$YR),]
		file.name = paste('Landings',i,'.png',sep="")
		# png(file=file.path(fpf1,'LandingsL3538.png'),units='in',width=15,height=12,pointsize=18, res=300,type='cairo')
		plot(aa$YR,aa[,i],type='h',lwd=4,col='black',xlab='Year',ylab='Landings (t)')
		lines(aa$YR,runmed(aa[,i],3),col='salmon',lwd=3)
		#dev.off()
		}

#relative F LFA 34
a34 = a[,c('YR','LFA34')]
b34 = b[,c('YR','LFA34')]
c34 = rbind(a34,b34)
c34 = subset(c34,YR>1969)
c34$yr = c34$YR
dadir = file.path(project.figuredirectory('bio.lobster'),'LFA34Update')
df =  read.csv(file.path(dadir,'LFA34-DFOtotalabund.csv'))
df2 = read.csv(file.path(dadir,'LFA34-DFOCommercialB.csv'))
df = subset(df,yr<1999)
df2 = subset(df2,yr>1998)
df = as.data.frame(rbind(df,df2))
df = df[,c('yr','w.Yst','w.ci.Yst.l','w.ci.Yst.u')] #proportion of total weight that is commercial
df$w.Yst[which(df$yr<1999)] <- df$w.Yst[which(df$yr<1999)]*0.71
df$w.ci.Yst.l[which(df$yr<1999)] <- df$w.ci.Yst.l[which(df$yr<1999)]*0.71
df$w.ci.Yst.u[which(df$yr<1999)] <- df$w.ci.Yst.u[which(df$yr<1999)]*0.71

 	 png(file=file.path(fpf1,'LFA34CommBDFOextended.png'),units='in',width=15,height=12,pointsize=18, res=300,type='cairo')
 	 with(df,plot(yr,w.Yst,pch=1,xlab='Year',ylab='Commerical Biomass (t)',ylim=c(0,8500)))
	 with(df,arrows(yr,y0=w.ci.Yst.u,y1=w.ci.Yst.l, length=0))
	 with(subset(df,yr>1998),points(yr,w.Yst,pch=16))
	 xx = rmed(df$yr,df$w.Yst)
	 xx = as.data.frame(do.call(cbind,xx))
	 with(subset(xx,yr<1999),lines(yr,x,col='salmon',lwd=1))
	 with(subset(xx,yr>1998),lines(yr,x,col='salmon',lwd=3))
	 dev.off()
	 

df  =merge(df,c34)
df$rL = df$LFA34/(df$w.ci.Yst.l+df$LFA34)
df$rU =df$LFA34/ (df$w.ci.Yst.u+df$LFA34)
df$rM = df$LFA34/(df$w.Yst+df$LFA34)
 df[which(!is.finite(df[,7])),7] <- NA
 df[which(!is.finite(df[,8])),8] <- NA
 df[which(!is.finite(df[,9])),9] <- NA
rl = median(subset(df,yr %in% 1970:1998,select=rM)[,1])


 	 png(file=file.path(fpf1,'LFA34RelFDFO.png'),units='in',width=15,height=12,pointsize=18, res=300,type='cairo')
		plot(df$yr,df$rM,type='p',pch=16,col='black',xlab='Year',ylab='Relative F')
		arrows(df$yr,y0 = df$rL,y1 = df$rU,length=0)
		with(rmed(df$yr,df$rM),lines(yr,x,col='salmon',lwd=3))
		abline(h=rl,lwd=2,col='blue')
		box(lwd=2)
	 dev.off()
write.csv(df,file=file.path(fpf1,'DFORelf34.csv'))

df = read.csv(file.path(dadir,'LFA34-NEFSCFallCommercialB.csv'))
df = df[,c('yr','w.Yst','w.ci.Yst.l','w.ci.Yst.u')]
df  =merge(df,c34)

df$rL = df$LFA34/df$w.ci.Yst.l
df$rU =df$LFA34/ df$w.ci.Yst.u
df$rM = df$LFA34/df$w.Yst
 df[which(!is.finite(df[,7])),7] <- NA
 df[which(!is.finite(df[,8])),8] <- NA
 df[which(!is.finite(df[,9])),9] <- NA
rl = median(subset(df,yr %in% 1970:1998,select=rM)[,1],na.rm=T)

 	 png(file=file.path(fpf1,'NEFSCFallRelFDFO.png'),units='in',width=15,height=12,pointsize=18, res=300,type='cairo')
		plot(df$yr,df$rM,type='p',pch=16,col='black',xlab='Year',ylab='Relative F')
		arrows(df$yr,y0 = df$rL,y1 = df$rU,length=0)
		with(rmed(df$yr,df$rM),lines(yr,x,col='salmon',lwd=3))
				abline(h=rl,lwd=2,col='blue')
				box(lwd=2)
	dev.off()
write.csv(df,file=file.path(fpf1,'NEFSCSFallRelf34.csv'))


df = read.csv(file.path(dadir,'LFA34-NEFSCSpringCommercialB.csv'))
df = df[,c('yr','w.Yst','w.ci.Yst.l','w.ci.Yst.u')]
df  =merge(df,c34)

df$rL = df$LFA34/(df$w.ci.Yst.l+df$LFA34)
df$rU =df$LFA34/ (df$w.ci.Yst.u+df$LFA34)
df$rM = df$LFA34/(df$w.Yst+df$LFA34)
 df[which(!is.finite(df[,7])),7] <- NA
 df[which(!is.finite(df[,8])),8] <- NA
 df[which(!is.finite(df[,9])),9] <- NA
rl = median(subset(df,yr %in% 1970:1998,select=rM)[,1])

 	 png(file=file.path(fpf1,'NEFSCSpringRelFDFO.png'),units='in',width=15,height=12,pointsize=18, res=300,type='cairo')
		plot(df$yr,df$rM,type='p',pch=16,col='black',xlab='Year',ylab='Relative F')
		arrows(df$yr,y0 = df$rL,y1 = df$rU,length=0)
		with(rmed(df$yr,df$rM),lines(yr,x,col='salmon',lwd=3))
		abline(h=rl,lwd=2,col='blue')
		box(lwd=2)
	dev.off()
write.csv(df,file=file.path(fpf1,'NEFSCSSpringRelf34.csv'))




df = read.csv(file.path(dadir,'ILTSCommB.csv'))
df = df[,c('Year','B','lB','uB')]
df  =merge(df,c34,by.x='Year',by.y='yr')

df$rL = df$LFA34/(df$lB+df$LFA34)
df$rU =df$LFA34/ (df$uB+df$LFA34)
df$rM = df$LFA34/(df$B+df$LFA34)
 df[which(!is.finite(df[,7])),7] <- NA
 df[which(!is.finite(df[,8])),8] <- NA
 df[which(!is.finite(df[,9])),9] <- NA
rl = median(subset(df,Year %in% 1970:1998,select=rM)[,1])

 	png(file=file.path(fpf1,'ILTSRelF.png'),units='in',width=15,height=12,pointsize=18, res=300,type='cairo')
		plot(df$Year,df$rM,type='p',pch=16,col='black',xlab='Year',ylab='Relative F')
		arrows(df$Year,y0 = df$rL,y1 = df$rU,length=0)
		with(rmed(df$Year,df$rM),lines(yr,x,col='salmon',lwd=3))
		abline(h=rl,lwd=2,col='blue')
		box(lwd=2)
	dev.off()

write.csv(df,file=file.path(dadir,'ILTSRelf34.csv'))

replacementRatio.relF(df$LFA34,df$LFA34+df$B, years.lagged.replacement=7)