find_msyr | R Documentation |
one of the functions needed for getting MNPL. MSYR is the same as FMSY.
find_msyr(E.start, lh.params, fmax)
E.start |
a starting guess for bycatch mortality rate that will result in FMSY (numeric value) |
lh.params |
a list of life history parameters (S0, S1plus, nages, AgeMat, lmabdaMax, K1plus, and z) |
fmax |
Max theoretical fecundity (numeric) |
# Set parameters S0.w = 0.5; S1plus.w = 0.944; nages.w = 25; K1plus.w = 9000; AgeMat.w = 18 InitDepl.w = 0.9; z.w = 2.39; lambdaMax.w = 1.04 lh.params = list(S0 = S0.w,S1plus = S1plus.w, nages = nages.w, AgeMat = AgeMat.w,K1plus=9000,z=z.w,lambdaMax = lambdaMax.w) # Get number of individuals per recruit in terms of mature individuals (\eqn{N0.w}) NPROut <- npr(S0 = S0.w, S1plus = S1plus.w, nages = nages.w, AgeMat = AgeMat.w, E = 0) N0 <- NPROut$npr # mature numbers per recruit # Get number of individuals per recruit in terms of individuals aged 1+ (\eqn{P0.w}) P0 <- NPROut$P1r # 1+ nums per recruit fmax <- getfecmax(lambdaMax = lambdaMax.w, S0 = S0.w, S1plus = S1plus.w, AgeMat = AgeMat.w) Fec0 <- 1.0 / N0 A <- (fmax - Fec0) / Fec0 fmsy<-find_msyr(E.start=0.01, lh.params=lh.params, fmax=fmax) cat("fmsy =",fmsy,"\n") results <- matrix(0,ncol=2,nrow=101) results[,1] <- c(0:100)*fmsy/50 for (II in 1:101) results[II,2] <- ce(S0 = S0.w, S1plus = S1plus.w, nages = nages.w, AgeMat = AgeMat.w,z = z.w, E=results[II,1], A = A, P0 = P0, N0 = N0) plot(results[,1],results[,2],xlab="f",ylab="ce",type="l",yaxs="i",ylim=c(0,max(results[,2])*1.2)) abline(v=fmsy)
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