Evaluating Federal Climate Policies for Freshwater Ecosystem Protection in North America
Bibliographic record
Abstract
Climate change poses a significant threat to freshwater ecosystems, which are vital for maintaining biodiversity, supporting human livelihoods, and providing essential ecosystems services. This paper evaluated the potential effectiveness of federal climate policies of Canada and the United States in protecting freshwater ecosystems amid a changing climate. By examining the National Adaptation Strategy Plan of Canada and the Office of Water Climate Change Adaptation Implementation Plan of the United States, this paper employed a formative evaluation approach to assess policy integration with current scientific knowledge and their potential effectiveness in managing freshwater ecosystems. The methodology included a selection of policies based on their relevance to climate change and freshwater ecosystems, followed by a rapid systematic literature review to gather data on climate impacts and scientific recommendations for climate policies. The analysis applied a formative evaluation approach to assess, a) the integration of current scientific knowledge in policy objectives, and b) to evaluate their potential effectiveness in protecting freshwater ecosystems. Key evaluation criteria included biodiversity conservation and protection, habitat management, stakeholder collaboration, and research and monitoring. The findings revealed that while both policies incorporated significant elements of climate adaptation and mitigation, there were notable gaps in some objectives from the Canadian and American policies regarding stakeholder collaboration. Additionally, the integration of scientific knowledge in policy objectives was fairly consistent, however there were other climate impacts that have not been acknowledged in the policies and could have possibly led to potential inefficiencies in addressing the multifaceted impacts of climate change on freshwater systems. This paper offered recommendations to enhance policy frameworks, emphasize the needs for stronger scientific integration, increased stakeholder involvement and adaptive management strategies that focus on freshwater ecosystems. By addressing these gaps, federal climate policies can be better equipped to ensure the resilience and protection of freshwater ecosystems in North America.
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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 | 0.153 | 0.157 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".