Freshwater Fisheries in Canada: Historical and Contemporary Perspectives on the Resources and Their Management
Bibliographic record
Abstract
Abstract.—In Canada, freshwater fisheries and their habitat are managed through a combination of federal and provincial authorities that can be traced back to the enactment of the federal Fisheries Act in 1868. While the management of freshwater fisheries has largely been delegated to inland provinces through regulations passed under the Fisheries Act since the early 20th century, the responsibility for the protection of fish habitat under the Fisheries Act remains a federal responsibility. This chapter provides an overview of the legislative and policy context governing the management of freshwater fisheries and their habitat by providing a brief historical perspective, describing the policies that have been applied by Fisheries and Oceans Canada and summarizing the protection afforded to fish and fish habitat via the Fisheries Act and related policies as it currently exists. Obstructions to fish migrations and flow needs for fishes were identified in the late 1800s as threats to fisheries. Habitat degradation and loss were explicitly identified as important threats under the Fisheries Act beginning in 1977. Since then, federal roles, policies and practices took on increasingly broader scope in recognition of the evolving understanding of aquatic ecosystem function. Concern over other threats, such as aquatic invasive species, is mounting, and the cumulative effects of multiple stressors, compounded with the impacts of climate change remain a complex management challenge. The federal government continues to manage threats to fish and fish habitat; through a regulatory approach that prohibits any work, undertaking, or activity that results in the “harmful alteration, disruption, or destruction” of fish habitat. Management approaches to address habitat-related and other threats will continue to evolve. In some cases, new legislative, regulatory, and policy approaches will need to be developed. Provincial, territorial, and other levels of government, including co-management boards, responsible for developing planning and permitting regimes, will continue to play a key role in managing threats to aquatic ecosystems. The numerous factors that can affect freshwaters, however, result in the need for concerted and intentional coordination across, and between, all levels of government (including Indigenous governments), Indigenous rights holders, partners, and stakeholders. Only when these systems work synergistically will freshwater fisheries, and the waters that support them, be sustained into the future.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".