Habitat-mediated effects of diurnal and seasonal migration strategies on juvenile salmon survival
Bibliographic record
Abstract
Behavioral decisions during periods of vulnerability to predation risk, such as migrations during the juvenile life-history stage, may strongly affect the probability of survival. Habitats through which animals migrate are heterogeneous, and risk-reducing behaviors may be more important in some habitats than others. Using biotelemetry data, diurnal and seasonal riverine migration patterns of >3800 juvenile salmon across 4 species, 12 watersheds, and 5 years were quantified to evaluate possible effects of migration timing on survival from lower river reaches to coastal waters. In small, clear rivers most salmon avoided migrating during daylight hours and average survival of fish migrating at night (55%; 95% confidence limits 50–61%) was twice that of fish migrating in daylight (24%; CL 17–31%). Conversely, in the large, heavily silted Fraser River neither preference for nocturnal travel nor effects of diurnal timing on survival were observed. Early ocean survival was also influenced by the timing of ocean entry, but in opposite directions for fish from the Fraser River and smaller rivers. In the Fraser River, average survival for later migrants (69%; CL 60–77%) was nearly twice that of earlier migrants (38%; CL 33–44%), likely related to seasonal increases in river flow. In contrast, in smaller rivers, average survival for earlier migrants (70%; CL 65–74%) was 3-fold greater than survival for later migrants (19%; 95% CL 14–25%). Together, these results demonstrate that timing decisions affecting survival of juvenile salmon during their migration are likely mediated by landscape characteristics that plausibly influence the risk of predation.
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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".