Accelerating sea level rise in Africa and its large marine ecosystems since the 1990s
Bibliographic record
Abstract
Sea-level rise poses a significant threat to Africa’s vital coastal ecosystems and the livelihoods of its growing populations. Here we analyze 31 years of satellite altimetry data to quantify sea-level change across Africa’s Large Marine Ecosystems, vast ocean regions of high biological productivity. The rate of rise has accelerated markedly to 4.34 mm/yr since 2010, over four times the 1990s rate. This is primarily driven by two factors: an increase in ocean mass from melting ice sheets accounts for over 80% of the total rise, with the remainder reflecting the expansion of warming ocean water. Regional rates are fastest in the Red Sea and Guinea Current, while increased salinity suppresses the trend in the Mediterranean. 2023 was particularly severe, with record-high sea levels across nearly 40% of Africa’s surrounding ocean. This uneven rise intensifies risks for over 50 million coastal residents, underscoring the urgent need for region-specific adaptation. Sea-level rise in African large marine ecosystem has accelerated markedly since 2010, mostly due to ice sheet loss and land subsidence, with the Red Sea and Guinea Current rising fastest, according to an analysis of 30 years of satellite altimetry data
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".