Interannual variability in size-selective winter mortality of young-of-the-year striped bass
Bibliographic record
Abstract
Abstract Early life stages of fish are characterized by high size-selective mortality rates, with selection generally acting against smaller, slow-growing individuals. Here, we investigate, for the St. Lawrence River striped bass (Morone saxatilis) population, how size of young-of-the-year juveniles (YOYs) affected survival from the pre-wintering period until the following spring, by comparing their otolith daily growth trajectory to that of one-year-old juveniles (OYOs). Otolith growth in the first 50 d after hatch was faster in post- than in pre-winter juveniles in both years, indicating that fast-growing individuals were more likely to survive to the next spring. A larger back-calculated size at age 1 in the 2016 year class compared to that observed in 2017 also suggests interannual variability in size-selective overwinter survival. Our results indicate that the design of YOY abundance surveys aimed at predicting annual recruitment strength needs to account for the effect of size-dependent mortality until the end of the first winter of life, as high abundance of relatively small YOYs in autumn may not necessarily translate into a large number of OYOs in the following spring and thus into high recruitment.
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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) | 0.001 | 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".