EVIDENCE OF RESILIENCE IN REEF ISLANDS IN RESPONSE TO RISING SEA LEVEL ON HUVADHOO ATOLL, MALDIVES
Bibliographic record
Abstract
Reef islands are at the forefront of concern for future accelerating sea-level rise since their low-lying and isolated nature puts them at higher risk of marine inundation compared to continental coastlines. However, the perceived threat of complete submersion as implied by projected future sea-level rise and current island elevations do not consider the morphologically resilient nature of reef island systems. In particular, the role of sediment supply in the resilience of these islands is still relatively poorly studied. This study presents detailed descriptions of the sedimentary characteristics and stratigraphy of two lagoonal platform islands in Huvadhoo Atoll, Maldives, that formed during periods of Holocene sea-level rise. Island subsurface stratigraphy was reconstructed by analysing the skeletal composition and textural properties of 306 sediment samples from 37 cores extracted across the islands. Island sediments were dominated by coral sands with varied proportions of secondary constituents (molluscs, Halimeda, foraminifera, and crustose coralline algae). Downcore variations in composition show that the proportion of coral sands decrease with depth and the proportion of molluscs and Halimeda increase with depth (with the exception of cores that terminated on lagoon infill). The increased proportion of Halimeda and molluscs in these early island deposits may have resulted from the catch-up growth strategy of the reef during the mid-Holocene highstand as both organisms have high turnover rates and directly contribute to sediment production after death. The sedimentological response of increased Halimeda and molluscs highlights the resilient and dynamic nature of reef islands and the ability of reefs to adjust ecologically to changing sea levels.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/gy3zhqocMGw
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".