Assess2MOM: Reads bootstrap estimates from a stock assessment model into...

In Blue-Matter/MSEtool: Management Strategy Evaluation Toolkit

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

Description

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.

Details

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

Value

An object of class MOM.

Author(s)

Q. Huynh

See Also

SS2MOM multiMSE Assess2OM

Blue-Matter/MSEtool documentation built on Nov. 22, 2024, 8:23 p.m.