TropFishR (version 1.6.4)

VBGF: Von Bertalanffy Growth function (VBGF)

Description

This function applies the von Bertalanffy growth function (VBGF). It allows to calculate ages from lengths or lengths from ages based on the special, generalised or seasonalised VBGF.

Usage

VBGF(param, t = NA, L = NA, na.rm = FALSE)

Value

A vector with estimated lengths corresponding to provided ages.

Arguments

param

a list with following potential objects:

• Linf: infinite length for investigated species in cm, or

• Winf: infinite weight for investigated species in gramm

• K: growth coefficent for investigated species per year

• t0: theoretical time zero, at which individuals of this species hatch (default: 0)

• b: exponent of weight length relationship (default: 3)

• D: surface factor (default: 1)

• L0: length at hatching for VBGF with L0

• ts: onset of the first oscillation relative to t0

• C: intensity of (sinusoid) growth oscillations. Default is no oscillation (C = 0)

t

ages for which to calculate corresponding lengths, or

L

lengths for which to calculate corresponding ages

na.rm

logical; should NA in input length or age vector be omitted? (default: FALSE)

Details

Based upon which input parameters are given one of the following VBGF types is applied: "special", "generalised", or "seasonalised" VBGF.

References

Somers, I. F. (1988). On a seasonally oscillating growth function. Fishbyte, 6(1), 8-11

Sparre, P., Venema, S.C., 1998. Introduction to tropical fish stock assessment. Part 1. Manual. FAO Fisheries Technical Paper, (306.1, Rev. 2). 407 p.

Examples

# calculation of lengths
# with t0
t <- seq(0,6,0.1)
Lt <- VBGF(list(Linf=80, K=0.6, t0=-0.1),t=t)
plot(t, Lt, t="l")

# with L0
t <- seq(0,6,0.1)
Lt <- VBGF(list(Linf=80, K=0.6, L0=2),t=t)
plot(t, Lt, t="l")

# with Winf
t <- seq(0,6,0.1)
Wt <- VBGF(list(Winf=4000, K=0.8), t=t)
plot(t, Wt, t="l")

# seasonalised VBGF
t <- seq(0,6,0.1)
Lt <- VBGF(list(Linf=80, K=0.6, t0=-0.1, ts=0.5, C=0.75),t=t)
plot(t, Lt, t="l")


# calculation of ages
L <- seq(2,200,0.1)
t <- VBGF(L = L, list(Linf=210, K=0.8, C= 0.75))
plot(t, L, t="l")