Build a stochastic operating model for one species

Apical fishing mortality of fleet \(f\) is \(F_{f,y} = q_f\,\eta_{f,y}\,E_{f,y}\,\delta_{f,y}\) with \(q_f = relq_f \times F_{MSY}\), nominal effort \(E\) and efficiency \(\eta\) from effort_sim() (shared by all species), and optional species-specific catchability noise \(\delta\) (sigmaQ). Fleet F-at-age is apical F times the fleet's selectivity-at-age; total F-at-age is the sum over fleets. The stock is projected with ffwd() under Fbar control and lognormal (optionally AR1) recruitment deviations. The first two years are dropped as burn-in, as in the reef example.

Usage

build_om(
  sp,
  fishery,
  nsim = 100,
  effort = NULL,
  sigmaQ = 0,
  ar1 = FALSE,
  seed = fishery$seed,
  treatment = NULL
)

Arguments

sp: a species().
fishery: a fishery().
nsim: number of iterations.
effort: optional result of effort_sim() for this fishery (pass it when building several species so they share one effort realisation; by default it is regenerated from the fishery seed, which gives the same).
sigmaQ: lognormal SD of species-specific catchability noise.
ar1: use the species' rho for AR1 recruitment deviations.
seed: base seed for recruitment (and sigmaQ) deviations; combined with the species id so species differ but are reproducible.
treatment: optional treatment() (changes to effort, recruitment, selectivity, creep or M); random numbers are unchanged, so a treated and an untreated operating model differ only by the treatment.

Value

an object of class floss_om: a list with stock (FLStockR), sr (FLSR), brp (calibrated equilibrium), sel (fleet selectivities), fapic and f_fleet (FLQuants of apical F and F-at-age by fleet), effort, efficiency, species, fishery and settings.

Details

Reference points are recomputed for the realised exploitation pattern (median F-at-age over iterations, last years) with FLRef::computeFbrp() and stored in the returned FLStockR.