Obtain generalized Linf/K growth increments — get_growth_increment

Evaluate the generalized Schnute growth curve using asymptotic length, growth rate, and shape directly. With gshape = 1, this is the usual von Bertalanffy curve. For positive k, gshape >= 1, and linf above the modelled length range, expected increments are positive and non-increasing with length.

Usage

get_growth_increment_linf(
  midpoint = seq(31, 91, 2),
  linf = 120,
  k = 0.1,
  gshape = 2,
  gcv = 0.5,
  gobs = 1,
  gdd = 0,
  gmin = 0.01,
  biomass = 1,
  tau = 1,
  growth_variance = 1L,
  gsigma = NULL,
  length_power = -1,
  variance_reference_length = 60
)

Arguments

midpoint: a numeric vector of release lengths or length-bin midpoints.
linf: asymptotic length Linf (mm).
k: generalized growth rate K (per year).
gshape: positive shape parameter gamma.
gcv: the process error parameter \(G_{CV}\) as a coefficient of variation.
gobs: the observation error parameter \(G_{obs}\) (mm).
gdd: the density-dependence parameter affecting growth.
gmin: the minimum standard deviation of growth increment (mm).
biomass: the biomass used for density-dependent growth calculations.
tau: the time at liberty (years).
growth_variance: Process-SD parameterization: 1 retains the historical mean-scaled gcv formulation; 2 uses a diffusion SD at variance_reference_length supplied by gsigma.
gsigma: Process diffusion SD at variance_reference_length in mm per square-root year. Used only when growth_variance = 2.
length_power: Power controlling how diffusion SD changes with length. Used only when growth_variance = 2.
variance_reference_length: Reference length for gsigma (mm).

Value

A list containing vectors gi (expected increment) and sigma (increment standard deviation).

Examples

get_growth_increment_linf()
#> $gi
#>  [1] 16.327476 15.535648 14.787217 14.078994 13.408004 12.771488 12.166888
#>  [8] 11.591845 11.044182 10.521894 10.023137  9.546219  9.089581  8.651793
#> [15]  8.231542  7.827620  7.438916  7.064411  6.703164  6.354311  6.017054
#> [22]  5.690659  5.374447  5.067790  4.770111  4.480872  4.199577  3.925764
#> [29]  3.659007  3.398909  3.145100
#> 
#> $sigma
#>  [1] 8.224756 7.831927 7.460928 7.110170 6.778174 6.463569 6.165086 5.881557
#>  [9] 5.611906 5.355143 5.110364 4.876738 4.653506 4.439975 4.235513 4.039543
#> [17] 3.851541 3.671031 3.497585 3.330813 3.170368 3.015941 2.867258 2.724082
#> [25] 2.586211 2.453478 2.325749 2.202931 2.084966 1.971838 1.863575
#>