Linking individual behaviour and migration success in<i>Salmo salar</i>smolts approaching a water withdrawal site: implications for management
Bibliographic record
Abstract
Seaward migration of immature salmonids (smolts) may be associated with severe mortality in anthropogenically altered channels. Few studies however, have identified distinct behaviours that lead to exposure to adverse habitats or even unsuccessful migration. This study used high resolution telemetry to map migration routes of Atlantic salmon (Salmo salar) smolts approaching a water withdrawal zone associated with an aquaculture facility in a lowland river. Individual smolts were tagged with an acoustic transmitter and released upstream of the water withdrawal zone. A trap was installed downstream of the water withdrawal zone. The trap captured all smolts that passed the water withdrawal zone. The tracking results confirmed previous studies on Pacific salmon showing that Atlantic salmon smolts may perform milling behaviours (i.e. upstream excursions and circular swimming behaviour) in anthropogenically altered channels. Non-milling and milling smolts were compared. Smolts performing milling behaviours covered a larger area (m2) and experienced an increased probability of entering the water withdrawal zone, considered an adverse habitat. Finally, smolts were identified as either passing (67%) or non-passing (33%) the water withdrawal zone based on the recapture data from the trap. In total, 20% of the non-passing smolts entered the aquaculture facility. Several behavioural traits differed between the remaining (80%) non-passing smolts and the passing smolts. In particular, time spent near the water withdrawal zone correlated negatively with the probability of passage. These links between individual behaviours and exposure to adverse habitats and passage probability may be applied to improve management of salmonid populations.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 teacher head, 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".