A function to extract von Bertalanffy growth parameters for fishes from back-calculated data

growthreg(
  length,
  age,
  id,
  lmax,
  linf_m = 0.8 * lmax,
  linf_sd = 0.2 * linf_m,
  l0_m,
  l0_sd = 0.2 * l0,
  plot = TRUE,
  ...
)

Arguments

length	`numeric` vector with length (CAUTION: must be in cm).
age	`numeric` vector with age.
id	`character` vector with fish ID.
lmax	Maximum size. Based on this value, maximum growth rate kmax will be computed.
linf_m	Prior for parameter linf, . (in cm)
linf_sd	Prior sd for linf, asymptotic length (default set to 10% of linf_m).
l0_m	Prior for l0, size at hatching. (in cm)
l0_sd	Prior sd for l0 (default set to 10% of l0_m).
plot	`logical` Option to plot model fit. Defaults to TRUE.
...	Additional arguments to `sampling`.

Details

Returns a list with three elements. The first element is a data.frame with estimates for linf, k and t0, sl and gp. There is a hierarchical structure for linf and k, so that there is a unique estimate for these parameters per individual (linf_j, k_j). linf and k are the population level estimates of linf and k. kmax is the standardised growth parameter, depending on lmax (kmax = exp(sl * log(lmax) + gp), see Morais and Bellwood (2018) for details. The second element is a data.frame with model fits for the average regression across individuals (ypred_m, ypred_sd, ypred_lb, ypred_ub), and the fitted regression er individual (yrep_m, yrep_sd, yrep_lb, yrep_ub). The third element is the entire stanfit object.

Author

Nina M. D. Schiettekatte

Examples


if (FALSE) {
library(dplyr)
library(fishgrowbot)
data(coral_reef_fishes_data)
em <- filter(coral_reef_fishes_data,
             species == "Epinephelus merra",
             location == "Moorea")
bc <- bcalc(data = em)$lengths
growthreg(length = bc$l_m/10, age = bc$age, id = bc$id, lmax = 32,
          linf_m = 28, linf_sd = 5, l0_m = 0.15, l0_sd = 0.015,
          iter = 4000, chains = 1)
}