Assess2OM: Reads bootstrap estimates from a stock assessment model...

View source: R/VPA2OM.R

Assess2OMR Documentation

Reads bootstrap estimates from a stock assessment model (including VPA) into an operating model. Assess2OM is identical to VPA2OM.

Description

A function that uses a set of bootstrap estimates of numbers-at-age, fishing mortality rate-at-age, M-at-age, weight-at-age, length-at-age and Maturity-at-age to define a fully described MSEtool operating model. The user still needs to parameterize most of the observation and implementation portions of the operating model.

Usage

Assess2OM(
  Name = "A fishery made by VPA2OM",
  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,
  nyr_par_mu = 3,
  LowerTri = 1,
  recind = 0,
  plusgroup = TRUE,
  altinit = 0,
  fixq1 = TRUE,
  report = FALSE,
  silent = FALSE,
  ...
)

VPA2OM(
  Name = "A fishery made by VPA2OM",
  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,
  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 operating model.

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 runMSE, e.g., 1 = annual updates.

CurrentYr

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

h

The steepness of the stock-recruitment curve (greater than 0.2 and less than 1, assumed to be close to 1 to match VPA assumption). Either a single numeric or a length nsim vector.

Obs

The observation model (class Obs). This function only updates the catch and index observation error.

Imp

The implementation model (class Imp). This function does not update implementation parameters.

naa

Numeric array [sim, ages, year]. Numbers-at-age [first age is age zero].

faa

Numeric array [sim, ages, year]. Fishing mortality rate-at-age [first age is age zero].

waa

Numeric array [sim, ages, year]. Weight-at-age [first age is age zero].

Mataa

Numeric array [sim, ages, year]. Maturity (spawning fraction)-at-age [first age is age zero].

Maa

Numeric array [sim, ages, year]. Natural mortality rate-at-age [first age is age zero].

laa

Numeric array [sim, ages, year]. Length-at-age [first age is age zero].

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 OM.

Author(s)

T. Carruthers

See Also

SS2OM iSCAM2OM WHAM2OM ASAP2OM


MSEtool documentation built on June 8, 2022, 1:06 a.m.