Identification of a limit reference point and proposal of an upper stock reference point for Canadian fishery management of Eastern Georges Bank (5Zjm) Haddock (Melanogrammus aeglefinus)
Bibliographic record
Abstract
Haddock (Melanogrammus aeglefinus) on eastern Georges Bank (DFO statistical unit areas 5Zj and 5Zm; EGB) is a Canada/U.S. transboundary species assessed by the Transboundary Resource Assessment Committee (TRAC). A new statistical catch-at-age stock assessment model was developed for EGB Haddock in March 2022. To meet the requirement of Fisheries and Oceans Canada’s Precautionary Approach framework, this document addresses the identification of a limit reference point (LRP) and proposal of an upper stock reference (USR) for Canadian fisheries management of EGB Haddock. Examination of the relationship between spawning stock biomass (SSB) and recruitment shows no evidence of a change in recruitment for the same level of SSB at two different time periods (1931–1954, 1969–2020). Similarly, comparison of surplus production in different time periods does not show evidence of productivity regime shifts. Therefore, the longer time series of data (i.e., 1969–2020) is considered the most appropriate for the calculation of reference points. Multiple candidate LRPs were proposed for peer review, with several deemed inappropriate based on the dynamics of the stock. Brecover, defined as the minimum biomass between 1991 and 1996 that resulted in sustained recovery to historically high levels, was determined to be the most appropriate LRP for EGB Haddock (8,620 mt). EGB Haddock appears to have two distinct groupings in magnitude of recruitment, with large SSB generally resulting in high recruitment and small SSB generally resulting in low recruitment. The proposed USR was calculated using the “Rago--Razor” method based on SSB and recruitment data and is estimated as 26,732 mt. Historical retrospective closed-loop simulation confirmed that the biomass dynamics of EGB Haddock were strongly driven by high recruitment variability over the past two decades. If using LRP and USR as control points in the historical fishery, retrospective closed-loop simulation showed that historical terminal biomass and average yield would be largely invariant to the implementation of alternative harvest control rules and various levels of the specified LRP and USR.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".