Make a list or vector of life history parameters for yield-per-recruit analyses.

Efficiently construct either a vector or list that contains the seven life history parameters required for Beverton-Holt yield-per-recruit analyses. The parameters can be given by the user through function arguments. Alternativvely, the von Bertalanffy parameters (Linf, K, and t0) may be extracted from an nls object created from fitting the von Bertalanffy equation to length-at-age data (object created outside this function). Similarly the log10-transformed weight-length model coefficients may be extracted from an lm object created from fitting the model to transformed weight-length data (object created outside this function). All parameter values are checked for sanity (e.g., Linf>0).

Usage

makeLH(N0, tmax, Linf, K, t0, LWalpha, LWbeta, restype = c("list", "vector"))

Arguments

N0: A single numeric that represents the number of fish in the population at the hypothetical age of t0.
tmax: A single whole number that represents maximum age in the population in years.
Linf: A single numeric that represents the point estimate of asymptotic mean length from the von Bertalanffy growth model OR an nls object created from fitting the von Bertalanffy equation to length-at-age data.
K: A single numeric that represents the point estimate of the Brody growth coefficient from the von Bertalanffy growth model.
t0: A single numeric that represents the point estimate of the x-intercept (i.e., theoretical age at a mean length of 0) from the von Bertalanffy growth model.
LWalpha: A single numeric that represents the point estimate of alpha from the length-weight regression on the log10 scale OR an lm object created from fitting the model to log10-transformed weight-length data.
LWbeta: A single numeric that represents the point estimate of beta from the length-weight regression on the log10 scale.
restype: A character that indicates the type of output (list or vector) returned by the function.

Value

A named list or vector (depending on restype) that contains the given (or extracted) life history parameters values that can be used directly in the yield-per-recruit calculation functions (e.g., yprBH_SlotLL).

Details

Use of this function for putting life history parameters into a list or vector is recommended as (i) values for Linf, K, t0, LWalpha, and LWbeta can be extracted from objects from appropriate model fitting and (ii) checks for impossible or improbable values for each parameter are performed; i.e.,

Author

Derek Ogle

# Best practice for entering life history parameter values
LH <- makeLH(N0=100,tmax=15,Linf=600,K=0.30,t0=-0.6,
             LWalpha=-5.453,LWbeta=3.10)

# Works but no checks on the values
LH <- list(N0=100,tmax=15,Linf=600,K=0.30,t0=-0.6,
           LWalpha=-5.453,LWbeta=3.10)

If a list is returned then values will be displayed with the number of decimals provided by the user. If a vector is returned then the number of decimals displayed will be the same for each value and will match the value supplied by the user with the most decimals. Thus, a list is preferred as it will be easier to match what was given to what was expected to be given.

Examples

library(FSA)
#> ## FSA v0.10.1. See citation('FSA') if used in publication.
#> ## Run fishR() for related website and fishR('IFAR') for related book.
library(FSAdata)
#> ## FSAdata v0.4.1. See ?FSAdata to find data for specific fisheries analyses.
library(dplyr)

# ----- Simple examples with explicity arguments for each -------------------
makeLH(N0=100,tmax=15,Linf=500,K=0.3,t0=-0.5,LWalpha=-5.613,LWbeta=3.1)
#> $N0
#> [1] 100
#> 
#> $tmax
#> [1] 15
#> 
#> $Linf
#> [1] 500
#> 
#> $K
#> [1] 0.3
#> 
#> $t0
#> [1] -0.5
#> 
#> $LWalpha
#> [1] -5.613
#> 
#> $LWbeta
#> [1] 3.1
#> 
makeLH(N0=100,tmax=15,Linf=500,K=0.3,t0=-0.5,LWalpha=-5.613,LWbeta=3.1,
       restype="vector")
#>      N0    tmax    Linf       K      t0 LWalpha  LWbeta 
#> 100.000  15.000 500.000   0.300  -0.500  -5.613   3.100 

# ----- Example of extracting values from model fits ------------------------
# N0 and tmax provided as arguments ... Linf, K, and t0 extracted from nls
#   output and LWalpha and LWbeta extracted from lm output. Note that nls
#   and lm output here are just examples of the function, they should be
#   calculated for the same species from the same waterbody, etc.

# Load data from FSAdata package, restrict to one location and year,
# create log10 values of weight and length
data(WalleyeErie2,package="FSAdata")
tmp <- WalleyeErie2 |>
  filter(loc==2,year==2010) |>
  mutate(logW=log10(w),
         logL=log10(tl))

# Generate LVB results
vb1 <- FSA::makeGrowthFun(type="von Bertalanffy")
fit1 <- nls(tl~vb1(age,Linf,K,t0),data=tmp,
            start=FSA::findGrowthStarts(tl~age,data=tmp))

# Generate length-weight regression results
fit2 <- lm(logW~logL,data=tmp)

# Make life-history list with those results
waeLH <- makeLH(N0=100,tmax=15,Linf=fit1,LWalpha=fit2)
waeLH
#> $N0
#> [1] 100
#> 
#> $tmax
#> [1] 15
#> 
#> $Linf
#> [1] 587.9484
#> 
#> $K
#> [1] 0.4851255
#> 
#> $t0
#> [1] -1.050782
#> 
#> $LWalpha
#> [1] -5.857295
#> 
#> $LWbeta
#> [1] 3.329038
#>