Salty stories, fresh spaces: Lessons for aquatic protected areas from marine and freshwater experiences
Bibliographic record
Abstract
Abstract Marine protected areas (MPAs) and freshwater protected areas (FPAs), collectively aquatic protected areas (APAs), share many commonalities in their design, establishment, and management, suggesting great potential for sharing lessons learned. However, surprisingly little has been exchanged to date, and both realms of inquiry and practice have progressed mostly independent of each other. This paper builds on a session held at the 7th World Fisheries Congress in Busan, South Korea, in May 2016, which explored crossover lessons between marine and freshwater realms, and included case studies of four MPAs and five FPAs (or clusters of FPAs) from nine countries. This review uses the case studies to explore similarities, differences, and transferrable lessons between MPAs and FPAs under five themes: (1) ecological system; (2) establishment approaches; (3) effectiveness monitoring; (4) sustaining APAs; and (5) challenges and external threats. Ecological differences between marine and freshwater environments may necessitate different approaches for collecting species and habitat data to inform APA design, establishment and monitoring, but once collected, similar spatial ecological tools can be applied in both realms. In contrast, many similarities exist in the human dimension of both MPA and FPA establishment and management, highlighting clear opportunities for exchanging lessons related to stakeholder engagement and support, and for using similar socio‐economic and governance assessment methods to address data gaps in both realms. Regions that implement MPAs and FPAs could work together to address shared challenges, such as developing mechanisms for diversified and sustained funding, and employing integrated coastal/watershed management to address system‐level threats. Collaboration across realms could facilitate conservation of diadromous species in both marine and freshwater habitats. Continued exchange and increased collaboration would benefit both realms, and may be facilitated by defining shared terminology, holding cross‐disciplinary conferences or sessions, publishing inclusive papers, and proposing joint projects.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.022 |
| Scholarly communication | 0.011 | 0.023 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".