Why has the American Eel, Anguilla rostrata, declined dramatically in the St Lawrence River but not the Gulf?
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.The collapse of American eel (Anguilla rostrata) populations in the upper St. Lawrence River and Lake Ontario (USLLO) has triggered fears of widespread population failure. We examined 13 hypotheses to explain patterns of eel abundance change in USLLO, elsewhere in the St. Lawrence River basin, and the Gulf of St. Lawrence. Indices for the St. Lawrence Estuary silver eel run and for eastern New Brunswick in the Gulf of St. Lawrence suggested moderate declines. The mussel invasion of Lake Ontario, changes in ship traffic in the Beauharnois Canal, and bottom-water hypoxia in the St. Lawrence Estuary were rejected as causes of eel population change because of timing mismatches or because alternate explanations were more plausible. Hydro turbines, fishing, and possibly chemical contamination directly kill eels, but total anthropogenic mortality from known sources in the St. Lawrence system is likely within ICES targets for resource managers. Large areas of the St. Lawrence River basin are inaccessible to eels due to dams, but current levels of recruitment are too low to fill most habitat above these dams if access were provided. The precipitous decline of eels in USLLO and the moderate decline in downstream St. Lawrence waters can be explained by density-dependent movements within a watercourse, where in times of declining abundance upstream reaches decline sharply while downstream reaches decline modestly. Eel recruitment to the St. Lawrence River or Gulf does not appear to be closely linked to common ocean factors. The long term eel decline in both the River and Gulf (which appears to be reversing in the Gulf) may be due to long-term changes in ocean conditions or to range-wide anthropogenic mortality that reduces total spawner numbers.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.007 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".