Tracking anadromous fish over successive freshwater migrations reveals the influence of tagging effect, previous success, and abiotic factors on upstream passage over barriers
Bibliographic record
Abstract
Predicting and mitigating the impact of anthropogenic barriers on migratory fish requires an understanding of the individual and environmental factors that influence barrier passage. Here, the upstream spawning migrations of iteroparous twaite shad Alosa fallax were investigated over three successive spawning migrations in a highly fragmented river basin using passive acoustic telemetry ( n = 184). More fish approached and passed barriers in the lower river reaches than further upstream, with the median cumulative weir passage time of 4.6 (1.8–9.2) days representing 18% of their time in the river. Returning fish in their second year had significantly higher weir passage rates than in their tagging year, with passage rates also positively influenced by previous passage success. Higher water temperatures and river levels also had positive impacts on passage rates. Lower weir passage rates by newly tagged individuals suggest that reliance on within-year passage estimates in telemetry-based barrier impact assessments could result in conservative results, while the higher passage rates of previously successful versus unsuccessful individuals suggest a conserved motivation and/or inherent ability to pass barriers.
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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 | 0.001 | 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".