Large‐scale, seasonal habitat use and movements of yellow American eels in the St. Lawrence River revealed by acoustic telemetry
Bibliographic record
Abstract
Abstract Large‐scale habitat use and movements of yellow American eels (Anguilla rostrata) from the St. Lawrence River were examined using acoustic telemetry from early summer to late fall in 2010 and 2011. Sixty‐seven eels were tagged, and their passage or presence was recorded using fixed acoustic arrays covering a 400 km distance along the St. Lawrence River and Estuary. Sixty‐four per cent of the 67 tagged eels were detected. Most eels were detected at only one array; the closest to their release location and at several occasions during the tracking period, suggesting a high proportion of freshwater residency in the upstream part of the St. Lawrence River. Downstream movements towards the brackish estuary (63–418 km distance) were demonstrated for 16.4% of the eels, particularly for those caught at the most downstream site that is close to the brackish estuary. Our results strongly suggest a lower activity of freshwater resident yellow eels during summer, a behaviour that may be related to day length, which defines time available for their nocturnal foraging. Indeed, yellow eels were detected primarily at night; no effect of moon phase was revealed. Movements in the vicinity of arrays (up to 116 km in the fluvial estuary) were suggested and smaller‐scale movements within Lac St. Louis were demonstrated, highlighting a yellow‐eel home range far more extensive than previously reported in smaller systems. Evidence for within‐season homing and site fidelity is also reported.
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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 | 0.000 |
| 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) | 0.001 | 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".