A Regional Review of Marine and Coastal Impacts of Climate Change on the ROPME Sea Area
Bibliographic record
Abstract
The Regional Organization for the Protection of the Marine Environment (ROPME) Sea Area (RSA) in the northern Indian Ocean, which comprises the Gulf, the Gulf of Oman and the northern Arabian Sea, already experiences naturally extreme environmental conditions and incorporates one of the world’s warmest seas. There is growing evidence that climate change is already affecting the environmental conditions of the RSA, in areas including sea temperature, salinity, dissolved oxygen, pH, and sea level, which are set to continue changing over time. The cumulative impacts of these changes on coastal and marine ecosystems and dependent societies are less well documented, but are likely to be significant, especially in the context of other human stressors. This review represents the first regional synthesis of observed and predicted climate change impacts on marine and coastal ecosystems across the ROPME Sea Area and their implications for dependent societies. Climate-driven ecological changes include loss of coral reefs due to bleaching and the decline of fish populations, while socio-economic impacts include physical impacts from sea-level rise and cyclones, risk to commercial wild capture fisheries, disruption to desalination systems and loss of tourism. The compilation of this review is aimed to support the development of targeted adaptation actions and to direct future research within the RSA.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".