In Craig44/stockassessmenthelper: Package to help plot stock assessment models and functionality

Growth models {#growthmodels}

In the R source code folder for this package, most growth functions are in the growth_oarams.R file. This is encase I forget to update the list of functions below.

Available functions

• vonbert() Von Bertalanffy age-length relationship
• basic_weight() basic length weight allometric relationship, accounts for a distribution of length at age. From memory it is the integrated weight over this distribution for lognormal distribution. However, I think it is fine for the normal distribution as for low CV's they are not that different.
• schnute() Generalised Schnute age-length relationship
• basic() basic length weight allometric relationship. Not as good as basic_weight()
• stretch() does a CV linear interpolation by age used in CASAL to define cv by age
• cv_by_length() does a length based interpolation of cv for the growth function
• transpose_VB() transpose the traditional VB formulation into a linear increment model based
• linear_growth_increment_model() the growth increment model

Illustrate the growth models

Linf = 155.9
k = 0.116
t0 = 2.495
growth_incrs = transpose_VB(L1 = 50, L2 = 100, Linf = Linf, k = k, t0 = t0)
g1 = growth_incrs[1]
g2 = growth_incrs[2]

years = 1:30
length_over_time = vonbert(years, k, Linf, t0)

# annual increment from growth increment formulation
growth_increments = linear_growth_increment_model(length_mid_points = length_over_time, L1 = 50, L2 = 100, g1, g2)

## should be the same as or close enough
## plot the increment model
plot(length_over_time[1:(length(length_over_time) - 1)], diff(length_over_time), xlab = "Length", ylab = "Increment", main = "Length increment over time")
points(x = length_over_time, y = growth_increments, pch = 16, cex = 0.8, col = "red")
## plot the resulting VBs
plot(years, length_over_time, type = "o", xlab = "Time", ylab = "Length", main = "Length over time")
points(x = years, y = c(length_over_time[1],length_over_time[1:(length(length_over_time) - 1)] + growth_increments[1:(length(growth_increments) - 1)]), pch = 16, cex = 0.8, col = "red")

Craig44/stockassessmenthelper documentation built on April 14, 2023, 10:57 a.m.