Overview of Marine Protected Areas and Sites of Particular Biodiversity Value in the Adriatic—Ionian Region (EUSAIR)
Bibliographic record
Abstract
Marine protected areas (MPAs) are an important tool for conserving biodiversity and ensuring the sustainable use of marine ecosystem services. This study examines the extent of MPAs in the Adriatic-Ionian region (EUSAIR). The analysis focuses on nationally designated marine protected areas and Natura 2000 sites (their marine parts), as well as areas of biodiversity importance that are not officially protected. With a marine area of 484,017 km2, the EUSAIR region has 46 nationally designated marine protected areas and 348 Natura 2000 marine protected areas as of 2021, which together represent a protected area of 16,347 km2 or 3.4% of the region’s total marine area. However, strictly protected areas of IUCN categories I and II account for only 0.07% of the region’s marine area, highlighting a significant gap in achieving global and EU biodiversity targets. In addition, around 30.75% of the marine area is classified as important for biodiversity based on various conservation instruments, but is not legally protected. These findings underline the urgent need for enhanced protection, improved management and stricter conservation measures to achieve the targets of the Kunmingand Montreal Global Biodiversity Frameworks and the EU Biodiversity Strategy 2030, which aims to have 30% of marine areas protected and 10% under strict protection by 2030. Achieving the EU biodiversity targets by 2030 will require a significant expansion of MPAs in the EUSAIR region and intensified efforts to designate new MPAs, integrate existing areas of high biodiversity and ensure effective management consistent with biodiversity conservation objectives.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".