Spatial and temporal differences in fecundity of Atlantic herring (<i>Clupea harengus</i>) off Nova Scotia and consequences for biological reference points
Bibliographic record
Abstract
The relationships between fecundity and size of Atlantic herring (Clupea harengus) were estimated within five different spawning areas off the coast of Nova Scotia in 2019 and 2020. Statistically significant differences in fecundity relative to body weight were observed among spawning areas and between years. Fecundity-at-length on the German Bank spawning ground was 29%–36% and 22%–28% lower than estimates from 2001 and 1970, respectively. Temporal changes in weight- and relative fecundity-at-age resulted in a decrease in the number of eggs-per-recruit (in an equilibrium unfished state) by 50% and a decrease of 27% in the egg production per tonne of spawning stock biomass (SSB) in 2020 relative to 1970. Decreases in SSB-per-recruit and eggs-per-recruit over time resulted in proportional decreases in equilibrium SSB at maximum sustainable yield (MSY); however, the fishing mortality rate (F) at MSY remained relatively stable over time. Total egg production was shown to be disproportional to SSB. Equilibrium SSB at MSY was greater (and F at MSY lower) when estimated using eggs-per-recruit compared to SSB-per-recruit. Failing to account for fecundity and assuming that egg production is proportional to SSB resulted in an overestimate of stock status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".