Responses to SSC comments

Responses to October 2025 SSC comments

A lapse in funding prevented the November and December 2025 EBS pollock SAFE package. The assessment team therefore did not provide a formal response to the October 2025 SSC comments during that assessment cycle. The responses below describe how the comments can be addressed in the 2026 assessment preparation and later work.

Current status

• The next assessment needs to trace the 2025 RTMB starting model back to the 2024 ADMB source, along with updated survey data, 2025 FT-NIRS ages, the comparison of traditional and FT-NIRS ages, model names, and the document archive.
• Work on Rceattle, SPoRC, natural mortality, selectivity, and age-composition weighting is underway, but these SSC comments remain open.
• Analyses of Russian catches and the recruitment penalty for the 2018 year class remain open.
• Work on the revised AVO index depends on completion and review of the new uncertainty analysis.

Research progress is not treated as a completed SSC response. A comment is complete only after the analysis, results, and explanation have been provided for review.

Model numbering plan

The model number should identify the model’s place in the review record. The software name should be shown separately. Under this plan, Model 23.0 is the 2024 ADMB source and Model 23.1 is its direct RTMB translation check. The newer model names are Model 25.0 (RTMB) for the work begun in 2025 and Model 26.0 (Rceattle) for the development line begun in 2026.

flowchart LR
  A["Model 23.0<br/>2024 ADMB source"] -->|"direct translation<br/>and checks"| B["Model 23.1<br/>RTMB translation check"]
  B --> C["Model 25.0<br/>RTMB line begun in 2025"]
  A -->|"new implementation<br/>and development"| D["Model 26.0<br/>Rceattle line begun in 2026"]
  S["SPoRC<br/>supporting comparison"] -.->|"common tests"| C
  S -.->|"common tests"| D

Figure 1: Proposed numbering and development history for EBS pollock assessment models.

The labels should be used as follows:

• Model 23.0 (ADMB) identifies the accepted source model used in 2024.
• Model 23.1 (RTMB) identifies the direct translation used to check that the new code reproduces Model 23.0. It is a numbered translation check, not a candidate for management advice.
• Model 25.0 (RTMB) is the public name for the RTMB assessment line begun in 2025 at the SSC’s request.
• Model 26.0 (Rceattle) is the public name for the Rceattle development line begun in 2026. Its changes must be listed separately from the change in software. This is the proposed operational model for 2026 management advice.
• SPoRC remains a supporting comparison. The single-region EBS pollock vignette illustrates the bridge from Model 23.0 to SPoRC and identifies the current differences between the implementations. Research on pollock movement and connections between U.S. and Russian waters is progressing. SPoRC should receive a numbered model name only if it is brought forward as an assessment candidate.

For later variants, keep the main number and add a decimal suffix, such as 26.1 or 26.2. Each suffix should represent one clearly documented change. Use the same label in the report, tables, presentations, run folders, and archive.

Comments and responses

Responses to the October 2025 SSC comments on EBS pollock. The SSC comments are summarized from pages 27 to 29 of the final October 2025 SSC report.

SSC comment	Response
Use the 2024 base model as the source for an RTMB implementation, with routine data updates.	Use the accepted Model 23.0 (ADMB) configuration as the scientific source. First check the direct RTMB translation as Model 23.1, then use Model 25.0 (RTMB) for the assessment line begun in 2025. List each new data set and each model change separately. Save the model version, run files, diagnostics, projections, and management quantities used in the report.
Use the updated Groundfish Assessment Program estimates of survey biomass and age composition.	Add the sdmTMB biomass estimates and tinyVAST age compositions as updated survey data. Record the data delivery date, software version, model settings, and input files. Compare the old and new survey series and show whether the change affects the assessment results.
Use FT-NIRS age compositions for the 2025 fishery and surveys.	Document how the FT-NIRS ages were produced, screened, grouped, and assigned to fishery and survey data. Record sample sizes and aging-error matrices. Check the final model input against the source data before fitting the assessment.
Compare traditional microscope ages with FT-NIRS ages and show the effects on model results and management quantities.	Run the same assessment with traditional ages, FT-NIRS ages with one aging-error matrix, and FT-NIRS ages with fleet-specific aging-error matrices. Compare cohort patterns, fits to fishery and survey ages, residuals, recruitment, spawning biomass, reference points, ABC, and OFL. Save the full comparison in the assessment appendix and at a permanent web address.
Revisit the revised AVO index after the new uncertainty analysis has been reviewed.	Wait for the final uncertainty method and review. Then compare the revised point estimates and uncertainty with the current AVO series. Show their effect on model fit, stock estimates, and management quantities before proposing a change to the base model.
Develop a plan with the BSAI Groundfish Plan Team for moving beyond ADMB.	Use the model history and numbering plan above. Compare RTMB, Rceattle, and SPoRC with the same data and a common set of tests. Ask the Plan Team to agree on the tests before selecting the model software for future assessments. Keep the accepted assessment model as the control until a replacement gives stable estimates, sound uncertainty, acceptable retrospective results, and reproducible projections.
Examine the effect of including Russian catches.	First confirm the source, area, years, units, species identification, and uncertainty of the Russian catch estimates. Then run clearly defined catch scenarios. Explain the assumptions about stock movement and population boundaries and show the effects on stock size, reference points, ABC, and OFL.
Explore time-varying natural mortality, selectivity, age-composition weighting, and cohort and temperature effects on weight at age.	Study each topic separately. State the scientific question before fitting a model. For each change, show model fit, parameter uncertainty, retrospective results, projections, and effects on management advice. Keep poorly estimated or unstable models as research results.
Continue work with CEATTLE estimates of natural mortality and consider Rceattle for time-varying mortality.	Test time-varying natural mortality as a sensitivity analysis. Check whether the model can separate mortality changes from recruitment, selectivity, and survey effects. Model software should be chosen from the full set of assessment needs, not from this feature alone.
Explain how the recruitment penalty affects the estimated 2018 year class and why the likelihood profile favored a larger recruitment estimate.	Prepare a likelihood profile for the 2018 recruitment deviation. Show how the recruitment penalty and each data source change across the profile. Explain which parts of the model favor a larger year class and how the estimate affects spawning biomass, reference points, ABC, and OFL.
Clearly identify the models proposed for the assessment, including model numbers.	Use Model 23.0 (ADMB) for the accepted 2024 source, Model 23.1 (RTMB) for the direct translation check, Model 25.0 (RTMB) for the line begun in 2025, and Model 26.0 (Rceattle) for the line begun in 2026. Use the same short names in the report, presentations, run folders, tables, and archive. For every model, list its purpose, parent model, data set, model changes, software version, and review status. State clearly which model is recommended for management advice.
Archive the October and December SAFE documents and presentations.	Archive the October 2025 material that exists and add a short note explaining that the funding lapse prevented the November and December SAFE package. For future reviews, save the Quarto source, rendered reports, presentations, model files, data list, software versions, and file checksums in one dated release.

Earlier responses to 2024 SSC comments

NoteRetained material

The responses below were on the previous version of this page and are retained without changing their scientific claims. They should be checked against the completed analyses and assessment record before they are cited as final 2025 results.

Dynamic Species Environment Models (DSEM) and recruitment mechanisms
The SSC recommended further exploration of DSEM to reconcile contrasting signals such as record larval biomass in 2024, low age-0 abundance, chronically low condition, and increasing adult biomass.
In 2025, exploratory DSEM analyses continue under the ESR framework. No new results are incorporated into the current assessment, but anomalous recruitment indicators are highlighted in the Recruitment section for context.

2026 activity: The Rceattle application presents the DSEM analysis together with preliminary ESP work.

Pollock cannibalism index
The SSC requested extrapolation of the index to biomass consumed.
For 2025, the index is updated. Work is underway to provide biomass-consumed estimates, though results are not yet finalized. This remains a development priority.

Tier 1 vs. Tier 3 classification
The SSC supported Tier 3 classification given reliance on priors and limited data at low stock sizes.
The 2025 assessment maintains Tier 3a status. Tier 1 calculations are not carried forward, consistent with SSC guidance.

Multispecies model outputs
The SSC encouraged use of time-varying mortality or consumption estimates from the multispecies model, noting its strategic role in climate planning.
In 2025, no direct integration of multispecies outputs occurred. These remain under review for potential use in ESP indicators and future assessment development.

Biological observations
The SSC noted low weight-at-age and condition in recent years and emphasized the importance of the 2018 year class.
The 2025 BTS confirms condition remains below average. The 2018 year class continues to dominate spawning biomass but shows expected decline as it ages out of the population.

Selectivity assumptions
The SSC supported the use of the five-year moving average selectivity for projections.
This method is retained in 2025, with updated retrospective diagnostics.

Model status and diagnostics
The SSC endorsed Model 23.0, Tier 3a classification, and ABC equal to the maximum permissible.
Model 23.0 is retained for 2025 with updated data inputs. Tier 3a status and ABC recommendations remain as supported by the SSC.

Additional recommendations

• State-space approach (TMB/RTMB): exploratory work is ongoing.
• Russian proportion/movement: no new estimates available for 2025.
• FT-NIR age validation: further evaluation continues; integration not yet implemented.
• Recruitment penalty (2018 cohort): sensitivity analyses are included; discussion of penalty influence is provided.

Stock-Recruitment relationship The SSC noted reduced influence under Tier 3, but stressed unbiased estimation of recruitment deviates and transparent use of steepness priors.
Recruitment is estimated without bias correction; steepness priors remain meta-analysis based. No Tier 1 analyses are presented.

Documentation request
The SSC requested that the September 2024 SRR document be included as an appendix or linked.
The document has been added as Appendix X in this SAFE.

SSC 2024 comments and 2025 responses

SSC comment	2025 response
Explore use of DSEM for pollock recruitment anomalies	Highlighted anomalies in Recruitment section; exploratory analyses ongoing, no integration yet.
Extrapolate cannibalism index to biomass consumed	Index updated; extrapolated biomass estimates in development, not finalized.
Tier 1 vs. Tier 3 classification	Maintained Tier 3a classification; Tier 1 calculations not carried forward.
Use multispecies model outputs (time-varying M, consumption)	No direct integration in 2025; retained for ESP and future assessment consideration.
Biological observations (low condition, 2018 year class)	2025 BTS confirms below-average condition; 2018 cohort still dominant but declining.
Use of five-year moving average selectivity	Retained for 2025 projections; retrospective diagnostics updated.
Endorse Model 23.0, Tier 3a, ABC=max permissible	Continued use of Model 23.0; Tier 3a classification; ABC set equal to maximum permissible.
Recommendations: state-space approach, Russian distribution, FT-NIR, recruitment penalty	State-space exploration ongoing; no new Russian estimates; FT-NIR evaluation continues; penalty influence discussed with sensitivity runs.
Stock-recruitment relationship	SRR not carried forward; recruitment deviates estimated unbiasedly; steepness prior remains meta-analysis based.
Add Sept 2024 SRR document as appendix	Document included as Appendix X.