Synthesizing and communicating climate change impacts to inform coastal adaptation planning
Bibliographic record
Abstract
Planning for adaptation to climate change requires regionally relevant information on rising air and ocean temperatures, sea levels, increasingly frequent and intense storms, and other climate-related impacts. However, in many regions there are limited focused syntheses of the climate impacts, risks, and potential adaptation strategies for coastal marine areas and sectors. We report on a regional assessment of climate change impacts and recommendations for adaptation strategies in the NE Pacific Coast (British Columbia, Canada), conducted in collaboration with a regional planning and plan implementation partnership (Marine Plan Partnership for the North Pacific Coast), aimed at bridging the gaps between climate science and regional adaptation planning. We incorporated both social and ecological aspects of climate change impacts and adaptations, and the feedback mechanisms which may result in both increased risks and opportunities for the following areas of interest: “Ecosystems”, “Fisheries and Aquaculture”, “Communities”, and “Marine Infrastructure”. As next steps within the region, we propose proactive planning measures including communication of the key impacts and projections and cross-sectoral assessments of climate vulnerability and risk to direct decision-making.
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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 | 0.028 | 0.059 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".