Marine protected areas and marine spatial planning: allocation of resource use and environmental protection for a sustainable and resilient future.
Bibliographic record
Abstract
Mohammed A. QURBAN1*, Lotfi J. RABAOUI1, Abdulnasser S. AL QUTUB1, Silvia AROSSA1, Afrah ALOTHMAN1, Eman SABBAGH1, Carlos GARCIA-SAEZ1,1National Center for Wildlife, Riyadh, Saudi Arabia* Correspondence: mqurban@ncw.gov.sa Seldom is the strong link that exists between Marine Spatial Planning (MSP) and Marine Protected Areas (MPAs) explicitly recognised as is now being done by the National Center for Wildlife (NCW). MSP is the process by which the use of marine space is identified and used to inform development decisions made by regulators. Marine Protected areas that are important for marine conservation are a priority for the NCW. These marine areas are formally designated and have legal protection as MPAs. Where MPAs do not exist in the Saudi Red Sea or the Arabian Gulf, marine plans are of assistance in the identification of areas where they could be sited optimally; taking into account environmental, social, economic and political considerations and existing uses. The Kingdom of Saudi Arabia, has been leading an intensive and extensive effort though the NCW designing and implementing MPAs, and developing a Marine Spatial Planning strategy in both the Arabian Gulf and the Red Sea as part of the Saudi Green Initiative and its 30x30 commitment to contribute to the Kunming-Montreal Global Biodiversity framework, bringing together synergies between Marine Protected Areas and Marine Spatial Planning. Areas such as Farasan Islands Man and Biosphere Reserve and the newly declared Blue Holes and Ras Hatiba in the Red Sea, and the proposed World Heritage site in Gulf of Aqaba and the Northern Red Sea and Jubail and Ras Abu Khamis in the Arabian Gulf are part of these endeavours. MSP includes elements of zoning, with MPAs incorporated as areas where the conservation of biodiversity is a priority. The development of this system of MSP will expand the role and design of individual and networks of MPAs and clarify this role to other user groups and help to reduce conflicts of use and take into account cumulative effects of marine activities to develop a sustainable and resilient-based management of the Kingdom of Saudi Arabia waters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".