Description Usage Arguments Value Author(s) References See Also Examples
Beverton and Holt biomass and yield per recruit calculation for a given set of parameters. Default method is numerical integration, but also Gulland approximation and relative yield concept are available.
1 2 3 4 | Beverton.Holt(F, M, Tr, Tc, Tmax, Wt, approxim="i")
Beverton.Holt(F, M, Tr, Tc, Tmax, Winf, K, t0, b=3, approxim="i")
Beverton.Holt(F, M, Tr, Tc, Winf, K, t0, b=3, approxim="g")
Beverton.Holt(FZ, Lc, Linf, MK, approxim="r")
|
F |
fishing mortality rate. |
M |
natural mortality rate. |
Tr |
age at recruitment. |
Tc |
age at first capture. |
Tmax |
maximum age attained. |
Wt |
weight at age (function). |
Winf |
asymptotic weight. |
K |
growth rate. |
t0 |
age at zero length. |
b |
exponent in length-weight relationship. |
FZ |
exploitation rate, F/Z. |
Lc |
length at first capture, L50. |
Linf |
asymptotic length. |
MK |
M/K. |
approxim |
method for estimate the integral. |
An object of the class BH
or BH.rel
with the components
YR |
yield per recruit. |
BR |
biomass per recruit. |
... |
input parameters. |
Sandro Klippel
Beverton, R., Holt, S., 1957. On the dynamics of exploited fish populations. Vol. 2. Sea Fish. Min. Agric. Fish Food G. B.
Beverton, R., Holt, S., 1966. Manual of methods for fish stock assessment - Part 2. Tables of yield functions. Vol. 38/1 de FAO Fisheries Technical Papers. FAO, Rome.
Quinn, T., Deriso, R., 1999. Quantitative fish dynamics. Oxford University Press, New York - Oxford.
Sparre, P., Venema, S., 1998. Introduction to tropical fish stock assessment - Part 1: Manual. Vol. 306/1 of FAO Fisheries Technical Paper. FAO, Rome.
plot.BH
, profile.BH
, F0.1
,
Fmax
, isopleths
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | BHx <- Beverton.Holt(F=0.6, M=0.2, Winf=3000, K=0.25, t0=-0.2, Tr=1, Tc=5, approxim="g")
BHy <- Beverton.Holt(F=0.6, M=0.2, Winf=3000, K=0.25, t0=-0.2, b=2.8,
Tr=1, Tc=5, Tmax=25, approxim="i")
# It can be of observed values
TWobs <- VBGFw(1:40, Winf=3000, K=0.1, t0=-0.2, b=2.9)
BHz <- Beverton.Holt(F=0.6, M=0.2, Wt=function(t){ TWobs[t] }, Tr=1,
Tc=5, Tmax=40, approxim="i")
## Not run:
## Monte Carlo approach
## This code does not run directly with example()
F <- rep(NA, 500)
for (i in 1:500){
F[i] <- F0.1(Beverton.Holt(
Wt=function(t){rnorm(1,mean=VBGFw(t, Winf=3000, K=0.25, t0=-0.2),
sd=300)}, Tr=1, Tc=5, Tmax=25, F=1,
M=runif(1, min=0.175, max=0.275)))
}
library(MASS)
truehist(F, xlab="F0.1", col="white")
lines(density(F), lwd=2)
## End(Not run)
|
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