Patterns and correlates of movement and site fidelity in individually tagged young-of-the-year Atlantic salmon (<i>Salmo salar</i>)
Bibliographic record
Abstract
The literature on stream fish movement offers diverse views on the patterns (restricted vs. nonrestricted), causes (competition vs. habitat use), and consequences (mobile fish of lower vs. equal fitness) of movement. We tagged 320 young-of-the-year Atlantic salmon (Salmo salar) (30.155.3 mm), using relatively noninvasive tagging (elastomers) and recovery (snorkeling) techniques, to test these alternative views. Most fish (mean = 63.8%) stayed in the study sites (10120 m) throughout their respective study season (2874 days). Of the resighted fish, 61.8% moved less than 1 m up- or down-stream and only three fish moved more than 10 m, causing extremely leptokurtic movement curves. Movement and site fidelity were weakly affected by habitat use and competition. Fish originally found in slow water moved farther than fish from fast water, whereas fish found at high population densities were more likely to disappear than fish from low densities. Finally, mobile fish grew as fast or faster than more sedentary fish, supporting the idea that movement can be advantageous and is not just a by-product of density-dependent population regulation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".