African Heritage Sites threatened by coastal flooding and erosion as sea-level rise accelerates
Bibliographic record
Abstract
Abstract Important heritage sites along the African coast are at risk from the threats associated with rising sea levels. Here, we quantify the exposure of natural and cultural heritage sites in Africa to coastal flooding and erosion in the 21st century. We develop a comprehensive database of 284 coastal African Heritage Sites (AHS), composed of 213 natural and 71 cultural heritage sites, which is then combined with coastal flooding and erosion projections to assess exposure to coastal extreme events for a moderate (RCP4.5) and high (RCP8.5) greenhouse gas emissions scenario. We find that 56 AHS are presently at risk from a 100-year extreme sea-level event, with a total exposed heritage area of 2,222 km2. Most of the currently exposed AHS are located in Northern and Western Africa. By mid-century, the number of exposed AHS is projected to increase more than 3 times to reach 191 and 198 under moderate and high emissions respectively. In the second half of the century, the number of exposed sites stabilizes, but the median exposed area increases to 6.6 to 8.5 times the present-day value, under moderate and high emissions, respectively. Mitigation from high to moderate emissions will reduce the end-century median exposed area and number of very highly exposed sites by 20% and 25% respectively.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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 | 0.000 |
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 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".