Regime Parameter clarity

[e-perl-NOAA]

In the SS3 course, we had someone ask about the SR regime parameter. In the user manual under Spawner-Recruitment Parameter Setup it says "The SR regime parameter is intended to have a base value of 0.0 and not be estimated." It sounds like a warning to people that the phase should be off and the value in the SR regime parameter should be zero. If you did want to mess around with the regime parameter, would you want the phase to be on to get it to work? If you still want the phase off for the regime parameter when altering this value, we might want to add clarity as to why this is the case (like would it be too much for the model to do regime parameter rec devs AND estimate the parameter?).

[Rick-Methot-NOAA]

I will try to talk about this on Tues webinar if I have time. The base regime value is always 0 and not estimated; it is just the base, Deviations (time-vary parameter of some sort) from the base ARE estimated.

[iantaylor-NOAA]

I agree that the regime parameter can be confusing. There is more information on the regime parameter under Time-varying stock-recruitment considerations: https://nmfs-ost.github.io/ss3-doc/SS330_User_Manual_release.html#time-varying-stock-recruitment-considerations (quoted below).

So a simple first step in improving the documentation would be to provide a link from the initial setup section to that more detailed information. A second helpful step might be to add a real-world example of how the regime parameter has been used.

• The spawner-recruit regime parameter is a modifier on R0. The regime shift parameter line allows for multi-year or environmentally driven deviations from R0 without changing R0 itself. The regime shift base parameter should have a base value of 0.0 and not be estimated (i.e., have a negative phase). Similar to the cohort-growth deviation, it serves simply as a base for adding time-varying adjustments.
• The same algebraic effect on the calculated recruitment can be achieved by different combinations of spawner-recruit parameter options (e.g., changing R0 directly instead of the regime shift parameter). It is recommended to use block, trend or environmental effects on R0 only for long-term effects, and use time-vary effects on the regime shift parameter for transitory but multi-year deviations from R0.
• If the R0 or steepness parameters are time-varying, then the model will use the current year’s parameters to calculate the expected value of recruits as a function of the spawning biomass, then applies the recruitment deviations. If the regime shift parameter is time-varying, then the model applies the change in the regime shift parameter after calculating the expected value of recruits as a function of spawning biomass.

[e-perl-NOAA]

@iantaylor-NOAA Do you happen to know of anyone who might have a real-world example of using the regime parameter?

There is also already a link to that section at the very end of the short paragraph that I initial linked in the issue.

[iantaylor-NOAA]

@e-perl-NOAA, good point. Perhaps I shouldn't have suggested describing a real-world example of the regime parameter since I don't have one to share.

@akatan999, I have some emails from you discussing the SR_regime parameter. Did you end up using it in any assessments that could be briefly summarized in the SS3 documentation?

@rosana-ourens did you end up using the SR_regime parameter in the final western horse mackerel assessment for the period of below-average recruitment? In the email discussion I saw you said that it didn't have much impact on the dynamics but improved the likelihood.

[akatan999]

Dear Ian,

I did some trial with North Sea cod but never got it working well, so unfortunately I don’t have anything that can be helpful.

Cheers

“I had never been salaried and felt that the research should be its own reward” Gorillas in the Mist

Dian Fossey

Massimiliano Cardinale Associate Professor

Sveriges lantbruksuniversitet Swedish University of Agricultural Sciences

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@e-perl-NOAAhttps://github.com/e-perl-NOAA, good point. Perhaps I shouldn't have suggested describing a real-world example of the regime parameter since I don't have one to share.

@akatan999https://github.com/akatan999, I have some emails from you discussing the SR_regime parameter. Did you end up using it in any assessments that could be briefly summarized in the SS3 documentation?

@rosana-ourenshttps://github.com/rosana-ourens did you end up using the SR_regime parameter in the final western horse mackerel assessment for the period of below-average recruitment? In the email discussion I saw you said that it didn't have much impact on the dynamics but improved the likelihood.

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[rosana-ourens]

Hi,

We did not use the SR_regime parameter in the final model for western horse mackerel. As you said, the likelihood improved a bit by including two productivity time-blocks but the benchmark panel was not very convinced with that and decided to remove it.

Best regards, Rosana