Temporal declines in fecundity: A study of southern Gulf of St. Lawrence Atlantic herring (<scp><i>Clupea harengus</i></scp>) and implications for potential reproductive output
Bibliographic record
Abstract
Individuals must reproduce to survive and thrive from generation to generation. In fish, the fecundity of individuals and estimates of total reproductive output are critical for evaluating reproductive success and understanding population dynamics. Estimating fecundity is an onerous task; therefore, many populations lack contemporary estimates of fecundity and size-fecundity relationships. However, reproductive dynamics are not static in time; therefore, it is important to develop contemporary fecundity estimates to better inform conservation and management action. To highlight the importance of contemporary fecundity estimates, we examined the fecundity of southern Gulf of St. Lawrence (sGSL) spring and fall spawning Atlantic herring in 2022, developed size-fecundity models, and compared these to historical fecundity estimates and models. Our results suggest that the average fecundity of sGSL spring and fall herring has undergone a substantial temporal decline of approximately 47% and 58%, respectively, since the 1970s and 1980s. The size-fecundity relationships for fall spawning herring have shifted, with fish of a given size exhibiting lower fecundity in 2022 compared to the 1970s. Alternatively, the size-fecundity relationships for spring spawning herring have remained relatively static. Furthermore, simulations highlighted a substantial reduction in potential reproductive output in 2022 compared to 1970 of approximately 32% and 68% for spring and fall spawners, respectively, based on a fixed number of mature females, which may have negative implications for stock rebuilding. Overall, our study provides support for periodic estimates of fecundity in fish populations to better understand temporal changes in reproductive and population dynamics.
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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 | 0.000 | 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".