Future-proofing the global system of marine protected areas: Integrating climate change into planning and management
Bibliographic record
Abstract
Climate change and its impacts are increasingly threatening the ability of marine protected areas (MPA) to meet their conservation goals. While integration of climate change into planning is critical, a recent global analysis found that relatively few MPAs have incorporated climate change considerations into formal management planning processes. Despite this, sessions and discussions at the Fifth International Marine Protected Areas Congress (IMPAC5) demonstrate that climate-adaptive management already permeates MPA processes, from day-to-day management to design and implementation. Here we review the results of an IMPAC5 knowledge exchange session that brought together a diverse group of MPA managers, Indigenous community representatives, and thought leaders to discuss improved integration of climate change into MPA management and planning. The session demonstrated the vibrancy, diversity, and engagement represented in the dynamic and fast-moving field of MPA climate change management and planning. In addition to sharing unique and diverse perspectives, the session leveraged the experience of experts to identify new and common challenges and gaps. As a result of this session, we present five recommendations, building on previous work, to guide MPA managers in the explicit and successful incorporation of climate adaptation into management planning and implementation. These recommendations hold the goal of ensuring an equitable, adaptive, and robust global MPA system. This review also provides a valuable summary of the vast repository of experience and knowledge of climate adaptive management contained within the MPA management community, and with community and Indigenous partners. Such perspectives are rarely reflected in formal scientific, policy, and management publications.
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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 | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".