Freshwater Fisheries in Canada: Historical and Contemporary Perspectives on the Resources and Their Management
Bibliographic record
Abstract
Abstract.—The understanding of habitat and its relationship to production and sustainability of fishes and fisheries has evolved over the past 140+ years in Canada. Recognition of the value of fishes and fisheries to Canadian society occurred in 1868 with the creation of the federal Fisheries Act. Habitat was not explicitly mentioned in the original act, and the acknowledgment of the value of habitat to fishes and fisheries was a gradual evolution starting in the late 19th century with determination that certain water flows and temperatures had influence on fishes and fisheries. In Canada, some of the direction and focus balancing competing resource uses and fisheries initially began with the creation of the Commission of Conservation and, subsequently, the National Research Council, both of which supported and funded the development of science for fishes and fisheries management. This paper reviews the evolution of freshwater fisheries habitat science and its applications in Canada from its origins in the early to mid-20th century, its initial focus on lakes and then expansion to streams, landscapes, and aquatic ecosystems, to present day. Habitat as a cornerstone of healthy and productive rivers, lakes, and their fish populations was fully recognized by scientists and resource managers by the late 1970s with the implementation of habitat and ecosystem-based planning processes. The final push for habitat as a major determinant of fishes and fisheries management in Canada occurred in 1988 after modernization of the federal Fisheries Act to include habitat as a major component of sound fishes and fisheries management. This has led to the consideration of broader-scale understanding of lake basins, landscapes and watersheds as fundamental generators and regulators of habitat in lakes and rivers and is ongoing and still evolving today.
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 | 0.000 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".