The state of climate change adaptation in Canada's protected areas sector
Bibliographic record
Abstract
Recent suggestions by the World Commission on Protected Areas that conservation actions are likely to fail unless they are adjusted to take account of climate change, emphasize the need for protected areas agencies to begin mainstreaming climate change into policy, planning, and management. This article presents the results of a University of Waterloo and Canadian Council on Ecological Areas survey on the state of climate change adaptation in Canada's protected areas sector, including all federal, provincial, and territorial jurisdictions. Analysis revealed several important findings. First, three quarters of agencies surveyed reported that climate change impacts were already occurring within their respective protected areas systems. Second, climate change was perceived by 94 percent of respondents to be an issue that will substantially alter protected areas policy and planning over the next 25 years. Third, despite the perceived future importance of climate change, little policy, planning, management, or research response is currently being undertaken by most agencies. Overall, with 91 percent of the agencies conceding that they currently do not have the capacity necessary to respond effectively to climate change, the survey revealed an important gap between the perceived salience of climate change and the capacity of protected areas agencies to adapt. Constraints, such as limited financial resources, limited internal capacity, and lack of understanding of real or anticipated climate change impacts, will need to be overcome if Canada's protected areas agencies are to be able to deliver on their various protected areas‐ and biodiversity‐related mandates, such as the perpetual protection of representative elements of Canada's natural heritage, in an era of rapid climate change.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".