Atlantic salmon (<i>Salmo salar</i>) smolt production: the relative importance of survival and body growth
Bibliographic record
Abstract
The complex life history of Atlantic salmon ( Salmo salar ) coupled with interacting abiotic and biotic factors leads to extreme demographic variability across the species’ range. Our goal was to evaluate the relative importance of survival and body growth in determining smolt production across space and time. We used passive integrated transponder tags and capture–mark–recapture analyses to estimate survival, emigration, and growth for six cohorts of presmolt Atlantic salmon in two streams (three cohorts per stream) in New England, USA. We observed remarkable among-cohort consistency in mean monthly survival during a 17-month period from age-0+ autumn to age-2+ spring yet high variability in monthly survival over shorter time intervals (seasons). Despite this latter variability, survival did not translate into among-cohort differences in proportions of age-2+ versus age-3+ smolts. Alternatively, the high variability across seasons and cohorts in mean individual growth rate did lead to differences in within-cohort proportions of age-2+ versus age-3+ smolts (regardless of stream). We conclude that in our two small study streams, variability in growth and size impacted smolt age and, ultimately, smolt production. Density-dependent effects on growth at the scale of the entire study site represent a possible mechanism underlying our observations.
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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".