An evaluation of fishing mortality reference points under varying levels of population productivity in three Atlantic cod (Gadus morhua) stocks
Bibliographic record
Abstract
Variation in productivity will affect the level of fishing mortality that a population can sustain without decline. We examined three Atlantic cod (Gadus morhua) stocks off Canada for evidence of changing productivity and determined the impact this variation would have on different fishing mortality reference points and their sustainability. Productivity was found to vary greatly over time within all three cod stocks. Under high productivity conditions, G0 (i.e. the potential growth in spawning-stock biomass at a fishing mortality of zero) for the three populations was 20–30%. But under low productivity conditions, G0 was much less. Two of the populations had G0 that was near zero or negative when productivity was low, indicating the possibility of population decline even in the absence of fishing. The degree to which the levels of common fishing mortality reference points (FMSY, FMAX, F0.1, and F40%SPR) changed across productivity periods was variable. All showed significant variation with changing productivity; however, the differences in reference points between productivity periods were generally very small except for FMAX and FMSY. All four reference points examined here were sustainable under conditions of high and average productivity. YPR and SPR reference points do not incorporate recruitment in their calculation. During periods of low productivity, recruitment was reduced and these reference points generally became unsustainable. FMAX was similar to FMSY only under high and average productivity but was not a good proxy for FMSY under lower levels of productivity. Reference points should incorporate recruitment because of its importance in determining the productivity of the stock and should be updated as productivity changes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".