Gadget3 surplus production model

A simple production model can be used in place of a set of gadget stock dynamics actions.

g3a_spmodel_logistic(
        r = g3_parameterized("spm_r", lower = 0.01, upper = 1, value = 0.5,
            by_stock = by_stock),
        p = g3_parameterized("spm_p", lower = 0.01, upper = 10, value = 1,
            by_stock = by_stock),
        K = g3_parameterized("spm_K", lower = 100, upper = 1e6, value = 1000,
            by_stock = by_stock),
        by_stock = TRUE)

g3a_spmodel(
        stock,
        spm_num = g3a_spmodel_logistic(),
        spm_num_init = g3_parameterized("spm_n0", by_stock = TRUE),
        spm_wgt = 1,
        run_f = TRUE,
        run_at = g3_action_order$initial)

Arguments

r, p, K: Parameters for the logistic model, see value section.
by_stock: Change the default parameterisation (e.g. to be by 'species'), see g3_parameterized.
stock: g3_stock object to apply the simple production model to.
spm_num: formula to calculate the relative change in abundance, one of the g3a_spmodel_* functions.
spm_num_init: Starting point for stock abundance.
spm_wgt: formula to calculate the mean weight, if "1", then abundance in numbers == total biomass.
run_f: formula specifying a condition for running this action, default always runs.
run_at: Integer order that actions will be run within model, see g3_action_order.

Details

The actions will define the following variables in your model, which could be reported with g3a_report_history:

(stock)__renewalnum: Numbers added to the abundance of stock

Note that the input stock should not have g3s_age, if the stock was broken up by age the model would quickly not make sense.

Value

g3a_spmodel_logistic

Returns a formula for use as spm_num:

$$ r s (1 - (\frac{s}{K})^p) $$

$s$
$r$: r argument, by default the (stock)_spm_r model parameter
$p$: p argument, by default the (stock)_spm_p model parameter
$K$: K argument, by default the (stock)_spm_K model parameter

g3a_spmodel

G3 action that maintains stock abundance / mean weight according to simple production model

Examples

# NB: Stock only has one length group, 30:40. So the stocks midlen is 35
stock_a <- g3_stock(c("stock", "a"), c(30, 40), open_ended = FALSE)
stocks <- list(stock_a)
fleet_a <- g3_fleet(c('fleet', "a"))

actions <- list(
    g3a_time(2000, 2010, step_lengths = c(6,6), project_years = 0),

    g3a_spmodel(
        stock_a ),
    g3a_predate(
        fleet_a,
        stocks,
        suitabilities = 1,
        catchability_f = g3a_predate_catchability_linearfleet(
            g3_parameterized("effort", value = 1e-1, by_predator = TRUE) )),

    # NB: Dummy parameter so model will compile in TMB
    ~{nll <- nll + g3_param("x", value = 0, optimise = TRUE)} )
actions <- c(actions, list(
    # NB: Late reporting for abundance
    g3a_report_history(actions, "__num$|__wgt$", out_prefix="dend_"),
    g3a_report_detail(actions) ))
model_fn <- g3_to_r(actions)

attr(model_fn, 'parameter_template') |>
    # Surplus production model parameters
    g3_init_val("*.spm_n0", 1e4) |>
    g3_init_val("*.spm_r", 0.1) |>
    g3_init_val("*.spm_p", 0.01) |>
    g3_init_val("*.spm_K", 1e8, lower = 0, upper = 1e20) |>

    identity() -> params.in
r <- attributes(model_fn(params.in))

barplot(r$dend_stock_a__num, las = 2)

barplot(r$detail_stock_a__renewalnum, las = 2)