Reads bootstrap estimates from a stock assessment model into a multi-fleet operating model.

A function that develops a multiple fleet operating model (MOM) and either models a unisex or 2-sex stock from arrays of abundance, fishing mortality, and biological parameters. The user still needs to parameterize most of the observation and implementation portions of the operating model.

Usage

Assess2MOM(
  Name = "MOM created by Assess2MOM",
  proyears = 50,
  interval = 2,
  CurrentYr = as.numeric(format(Sys.Date(), "%Y")),
  h = 0.999,
  Obs = MSEtool::Imprecise_Unbiased,
  Imp = MSEtool::Perfect_Imp,
  naa,
  faa,
  waa,
  Mataa,
  Maa,
  laa,
  fecaa,
  nyr_par_mu = 3,
  LowerTri = 1,
  recind = 0,
  plusgroup = TRUE,
  altinit = 0,
  fixq1 = TRUE,
  report = FALSE,
  silent = FALSE,
  ...
)

Arguments

Name

Character string. The name of the multi-OM.

proyears

Positive integer. The number of projection years for MSE.

interval

Positive integer. The interval at which management procedures will update the management advice in multiMSE, e.g., 1 = annual updates.

CurrentYr

Positive integer. The current year (e.g., final year of fitting to data)

h

The steepness of the stock-recruitment curve. Either a single numeric or a length nsim vector.

Obs

Either a single observation model to be used for all sexes and populations (class Obs), or a list where Obs[[f]] is the Obs object for fleet f (identical between sexes).

Imp

Either a single implementation model to be used for all sexes and populations (class Imp), or a list where Imp[[f]] is the Obs object for fleet f (identical between sexes).

naa

Numbers-at-age by sex [first age is age zero]. Four-dimensional numeric array [sim, ages, year, p]. [p] indexes the population, where [p = 1] for females and [p = 2] for males.

faa

Fishing mortality rate-at-age by sex and fleet [first age is age zero]. Five-dimensional numeric array [sim, ages, year, p, f] where [f] indexes fishery fleet.

waa

Weight-at-age [first age is age zero]. Four-dimensional numeric array [sim, ages, year, p].

Mataa

Maturity (spawning fraction)-at-age [first age is age zero]. Four-dimensional numeric array [sim, ages, year, p].

Maa

Natural mortality rate-at-age [first age is age zero]. Four-dimensional numeric array [sim, ages, year, p].

laa

Length-at-age [first age is age zero]. Four-dimensional numeric array [sim, ages, year, p].

fecaa

Fecundity at age [first age is age zero]. If missing, default fecundity is the product of maturity and weight at age.

nyr_par_mu

Positive integer. The number of recent years that natural mortality, age vulnerability, weight, length and maturity parameters are averaged over for defining future projection conditions.

LowerTri

Integer. The number of recent years for which model estimates of recruitment are ignored (not reliably estimated by the assessment)

recind

Positive integer. The first age class that fish 'recruit to the fishery'. The default is 0 - ie the first position in the age dimension of naa is age zero

plusgroup

Logical. Does the assessment assume that the oldest age class is a plusgroup?

altinit

Integer. Various assumptions for how to set up the initial numbers. 0: standard, 1: no plus group, 2: temporary fix for MSEtool plus group initialization

fixq1

Logical. Should q be fixed (ie assume the F-at-age array faa is accurate?

report

Logical, if TRUE, a diagnostic will be reported showing the matching of the OM reconstructed numbers at age vs the assessment.

silent

Whether to silence messages to the console.

...

Additional arguments (for all, either a numeric or a length nsim vector):

SRrel Stock-recruit relationship. (1 for Beverton-Holt (default), 2 for Ricker)
R0 unfished recruitment
phi0 unfished spawners per recruit associated with R0 and h. With time-varying parameters, openMSE uses the mean phi0 in the first ageM (age of 50 percent maturity) years for the stock-recruit relationship. Assess2OM will re-calculate R0 and h in the operating model such that the stock-recruit alpha and beta parameters match values implied in the input.
Perr recruitment standard deviation (lognormal distribution) for sampling future recruitment
AC autocorrelation in future recruitment deviates.

Value

An object of class MOM.

Details

Use a seed for the random number generator to sample future recruitment.

Author

Q. Huynh