Managing the Impacts of Human Activities on Fish Habitat: The Governance, Practices, and Science
Bibliographic record
Abstract
<em>Abstract.</em>—American Eel mortality has increased substantially over the past century due largely to significant cumulative effects of fishing and fish passage through hydro-electric turbines across their range. Nowhere has this been more pronounced than in waters of the St. Lawrence River, Lake Ontario, Ottawa River and associated watersheds. We illustrate this by examining the cumulative effects of hydro-electric facilities on eels migrating downstream through the Mississippi River and Ottawa River, and outline further impacts eels encounter en route to spawn in the Sargasso Sea. The probability of a mature female eel surviving its emigration through the Mississippi and Ottawa River to the upper St. Lawrence River is estimated to be as low as 2.8% due to turbine mortalities alone (2.8–40%). Mortality risk increases as the eel attempts to run the gauntlet of fisheries in the lower St. Lawrence River and the probability of out-migration survival is estimated to be as low as 1.4%. Some mortalities could be mitigated through improved application of existing laws, development of policy requiring consideration of cumulative effects and improved integration among program areas responsible for sustainable management of fisheries, biodiversity, dams and hydro-electric facilities. We recommend changes to policy, procedures and internal organizational structures provided with clear directions, and call for increased accommodation of Aboriginal perspectives.
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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 | 0.001 | 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 | 0.001 | 0.018 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".