Incorporating climate change adaptation into marine protected area planning
Bibliographic record
Abstract
Climate change is increasingly impacting marine protected areas (MPAs) and MPA networks, yet adaptation strategies are rarely incorporated into MPA design and management plans according to the primary scientific literature. Here we review the state of knowledge for adapting existing and future MPAs to climate change and synthesize case studies (n = 27) of how marine conservation planning can respond to shifting environmental conditions. First, we derive a generalized conservation planning framework based on five published frameworks that incorporate climate change adaptation to inform MPA design. We then summarize examples from the scientific literature to assess how conservation goals were defined, vulnerability assessments performed and adaptation strategies incorporated into the design and management of existing or new MPAs. Our analysis revealed that 82% of real-world examples of climate change adaptation in MPA planning derive from tropical reefs, highlighting the need for research in other ecosystems and habitat types. We found contrasting recommendations for adaptation strategies at the planning stage, either focusing only on climate refugia, or aiming for representative protection of areas encompassing the full range of expected climate change impacts. Recommendations for MPA management were more unified and focused on adaptative management approaches. Lastly, we evaluate common barriers to adopting climate change adaptation strategies based on reviewing studies which conducted interviews with MPA managers and other conservation practitioners. This highlights a lack of scientific studies evaluating different adaptation strategies and shortcomings in current governance structures as two major barriers, and we discuss how these could be overcome. Our review provides a comprehensive synthesis of planning frameworks, case studies, adaptation strategies and management actions which can inform a more coordinated global effort to adapt existing and future MPA networks to continued 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 | 0.017 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".