A simple age-structured model (SCA_Pope) fitted to a time series of catch going back to unfished conditions. Terminal depletion (ratio of current total biomass to unfished biomass) is by default fixed to 0.4. Selectivity is fixed to the maturity ogive, although it can be overridden with the start argument. The sole parameter estimated is R0 (unfished recruitment), with no process error.

  x = 1,
  dep = 0.4,
  SR = c("BH", "Ricker"),
  rescale = "mean1",
  start = NULL,
  prior = list(),
  silent = TRUE,
  opt_hess = FALSE,
  n_restart = ifelse(opt_hess, 0, 1),
  control = list(iter.max = 2e+05, eval.max = 4e+05),



A position in the Data object (by default, equal to one for assessments).


An object of class Data


Depletion value to use in the model. Can be an expression that will be evaluated inside the function.


Stock-recruit function (either "BH" for Beverton-Holt or "Ricker").


A multiplicative factor that rescales the catch in the assessment model, which can improve convergence. By default, "mean1" scales the catch so that time series mean is 1, otherwise a numeric. Output is re-converted back to original units.


Optional named list of starting values. Entries can be expressions that are evaluated in the function:

  • R0 Unfished recruitment

  • vul_par A length-two vector for the age of 95% and 50% fleet selectivity. Fixed to maturity otherwise.


A named list for the parameters of any priors to be added to the model. See details in SCA_Pope.


Logical, passed to MakeADFun, whether TMB will print trace information during optimization. Used for diagnostics for model convergence.


Logical, whether the hessian function will be passed to nlminb during optimization (this generally reduces the number of iterations to convergence, but is memory and time intensive and does not guarantee an increase in convergence rate).


The number of restarts (calls to nlminb) in the optimization procedure, so long as the model hasn't converged. The optimization continues from the parameters from the previous (re)start.


A named list of arguments for optimization to be passed to nlminb.


Other arguments to be passed (not currently used).


An object of class Assessment.


In SAMtool, SSS is an implementation of SCA_Pope with fixed final depletion (in terms of total biomass, not spawning biomass) assumption.


Cope, J.M. 2013. Implementing a statistical catch-at-age model (Stock Synthesis) as a tool for deriving overfishing limits in data-limited situations. Fisheries Research 142:3-14.


Q. Huynh


res <- SSS(Data = Red_snapper)

SSS_MP <- make_MP(SSS, HCR40_10, dep = 0.3) # Always assume depletion = 0.3