RE: recruitment forecast - Public Forums - Stock Synthesis

Dan,

Thank you for the well-formed question. The benchmark (Bmark) years are used for calculating reference points and the forecast (Fcast) years are used for the projection. Thus, if you want to use the new feature of supplying a range of years to define recruitment deviations to be used in creating an average forecast recruitment environment then you should use the Fcast lines. You can read about this in the manual on pages 29-30, available here https://github.com/nmfs-stock-synthesis/ss-documentation/blob/main/SS330_User_Manual.pdf, note that you must use option 3 to make the Fcast years translate into mean recruitment. Hopefully, others will chime in later if I have missed anything.

Kind regards,

Kelli

Thanks Kelly.  That is very helpfully. 

So both lines refers to the year range for annual recruitment deviates  - one for reference points calculation, the other for projection. 

If I could clarify a bit more - Does this  also apply to the regional recruitment distribution parameter which are defined as annual deviates in a multi-area model (not the  annual recruitment deviates parameter)?

 Cheers,

Dan

Dan,

Unfortunately, I am not very well versed in multi-area models. It looks as though the forecast recruitment is unique to growth pattern, see here for the code.

I know that is not very helpful, but hopefully someone who is better at area-specific models will be able to answer your question with more detail. 

Kind regards,

Kelli

Thanks Dan for the good questions and thanks Kelli for a good response.  Let me recap here, from the perspective of the current code which we intend to release soon as 3.30.17.

The first line, for benchmark (aka reference points), does not consider recruitment deviations because these are equilibrium quantities.  The quantities beg_recr_dist, end_recr_dist, on that line refer to the distribution of recruitment among biological entities, seasons, and areas.

The second line for forecast has seen some development recently, as well as some additional warnings to help users avoid incompatible combinations.  Here the concepts of recruitment deviations and recruitment_distribution both apply.  There has been augmentation of the controls for both of these.

This new control, shown below from forecast.ss, controls the mean recruitment in the forecast.  Older versions of SS3 only had option 0:

1 #_Forecast recruitment:  0= spawn_recr; 1=value*spawn_recr_fxn; 2=value*VirginRecr; 3=recent mean from yr range above (need to set phase to -1 in control to get constant recruitment in MCMC).

With this new option 3, the year range comes from the 2nd line that you originally referred to using the values for:  beg_mean recruits, end_recruits

The annual deviations around that mean remain under control of the control file input for the phase of the forecast recruitment deviations.

Recently we realized that the control of the distribution of each forecast recruitment needed to align with the control of the mean forecast recruitment.

So now if you select option 3 to get mean forecast recruitment from the mean of a range of years of historical recruitment, SS3 will also get the mean distribution of those recruitments among bio entities and areas from the same range of years.  Here is where we have added some more warnings if incompatible conditions are detected.

I hope this helps.  Keep the questions coming.  Kelli already included a link into our github repo.  Check it out.

Rick

Thanks Rick for the clear and comprehensive response. If I could just confirm that from the perspective of 3.30.17,  if the area recruitment distribution is defined as a time vary parameter (e.g. simple annual deviations), we could simply use option 3 in the forecast file together with the year range  to determine the average value to go into projection without invoking the additional time-block configuration. Is that correct?

Cheers, 

Dan

Dan,

That is the intention of the model code, but we have only been able to try it out in a limited number of model configurations,  Please let us know if the model does not work as intended in your application.  The code is designed so that recr_dist during the forecast is either a time-varying parameter, or it is set to the mean of a range of prior years.  We'll get a beta of this updated exe posted soon.  Note that SS3 changes often will require an update of your version of r4ss also.