Freshwater Fisheries in Canada: Historical and Contemporary Perspectives on the Resources and Their Management
Bibliographic record
Abstract
Abstract.—The Laurentian Great Lakes represent one of the world’s most colossal freshwater ecosystems, comprising five major lakes and seven connecting rivers covering 244,000 km2 in the present-day Canada and United States. The lakes are highly biodiverse with 143 native and 34 established alien species representing colonizations from the Mississippi and Atlantic refugia along with some endemic species. The rich ichthyofauna have supported Indigenous fisheries for millennia, which expanded to commercial fisheries by settlers and now valuable recreational fisheries. Many key fisheries in the Great Lakes have collapsed and many native species have been replaced by introduced alien species. Indeed, overexploitation and invasive alien species remain among the most urgent threats to these freshwater ecosystems along with habitat alteration and pollution and the increasingly urgent temperature warming and changes to water levels associated with climate change. Restoration of native wetlands and tributaries is crucial to the overall function of the Great Lakes and many successes have been hard fought to curb pollution, enhance habitat, and improve overall functioning of the highly modified urban and agricultural coastal wetlands. Educating society and providing clear evidence linking human health and well-being will be crucial to maintaining momentum for further restoration and continued improvement of this unique and critical ecosystem and the economically and culturally important fisheries they support. Management of the Great Lakes will continue to be challenging, but adaptive approaches have already been successful in many cases, and continued investment in improvement will certainly pay off in the long-term.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".