Managing the Impacts of Human Activities on Fish Habitat: The Governance, Practices, and Science
Bibliographic record
Abstract
<em>Abstract.</em>—Canada’s <em>Fisheries Act</em>, the country’s primary law for regulating the harvesting of its marine and freshwater fisheries resources, includes provisions to regulate the impacts of human activities on fish and fish habitat. As a result of these provisions the <em>Fisheries Act </em>represents the main federal statute for protecting freshwater and marine aquatic ecosystems and is considered one of the strongest environmental laws in Canada. This paper outlines the legal and policy frameworks and institutional arrangements for the administration of these provisions of the <em>Fisheries Act</em>. It describes the review process and practices established by Fisheries and Oceans Canada (DFO) for administering the provisions of the <em>Act </em>assigned to the Department’s Fish Habitat Management Program (HMP). It defines the key issues and concerns raised about the delivery of the Fish Habitat Management Program and reviews initiatives undertaken to address these. It suggests that while these have improved delivery of the regulatory responsibilities of the HMP, there is a need for more fundamental changes that will enable it to keep pace with the increasing and cumulative impacts associated with population growth and economic development and create conditions under which human activities and fish and fish habitat can co-exist on a sustainable basis. This paper suggests that such a change must be founded on an ecosystem-based approach and on the application of modern scientific and management principles for regulating impacts to fish and fish habitat. It also describes steps to move forward to demonstrate and instill an ecosystem-based approach.
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 | 0.001 | 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 | 0.003 | 0.034 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".