Enhancing climate change planning and adaptive management in marine protected areas through targets, thresholds, and social-ecological objectives
Bibliographic record
Abstract
Marine Protected Areas (MPAs) are being deployed globally to protect the Earth’s biodiversity in rapidly changing oceans. Nesting climate change considerations within adaptive MPA management and monitoring is becoming a more common approach, and while climate change is increasingly addressed in MPA planning, implementation gaps remain. This study applied the climate robustness index (CRI) to MPA monitoring plans to assess how climate change is outlined within site- and regional-level plans. Previously developed to assess MPA management plans, the CRI scores plans based on their degree of incorporation of climate change adaptation principles, including core elements of adaptive management. We supplemented our CRI findings for monitoring plans by associating index scores of MPAs in the United States with selected MPA traits, as well as by examining specific physical, ecological, and sociological climate change impacts that were being considered within the monitoring scope of a subset of monitoring plans. We found considerable gaps in actionable targets and thresholds in MPA monitoring plans, consistent with a previous study evaluating MPA management plans, demonstrating that the adaptive management cycle is incomplete in many cases. We consider the importance of completing the adaptive management cycle as a core climate adaptation strategy, and explore the roles of social-ecological objectives and local partnerships as avenues to continue to improve MPA outcomes in a changing world.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.012 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".