Expanding marine protected areas to include degraded coral reefs
Bibliographic record
Abstract
Marine protected areas (MPAs) are a commonly applied solution to coral reef degradation, yet coral reefs continue to decline worldwide. We argue that expanding the range of MPAs to include degraded reefs (DR-MPA) could help reverse this trend. This approach requires new ecological criteria for MPA design, siting, and management. Rather than focusing solely on preserving healthy reefs, our approach focuses on the potential for biodiversity recovery and renewal of ecosystem services. The new criteria would help identify sites with the highest potential for recovery and the greatest resistance to future threats (e.g., increased temperature and acidification) and sites that contribute to MPA connectivity. The DR-MPA approach is a compliment rather than a substitute for traditional MPA design approaches. We believe that the DR-MPA approach can enhance the natural, or restoration-assisted, recovery of DRs and their ecosystem services; increase total reef area available for protection; promote more resilient and better-connected MPA networks; and improve conditions for human communities dependent on MPA ecosystem services.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".