Severe Heat Stress Resulted in High Coral Mortality on Maldivian Reefs following the 2015–2016 El Niño Event
Bibliographic record
Abstract
Coral cover worldwide has been declining due to heat stress caused by climate change. Here we report the impacts of the 2015–2016 El Niño mass coral bleaching event on the coral cover of reefs located on central and northern atolls of the Maldives. We surveyed six reef sites in the Alifu Alifu (Ari) and Baa (South Maalhosmadulu) Atolls using replicate 20 m benthic photo transects at two depths per reef site. Live and recently dead coral cover identified from images differed between reef sites and depth. Recently dead corals on average made up 33% of the coral assemblage at shallow sites and 24% at deep sites. This mortality was significantly lower in massive corals than in branching corals, reaching an average of only 6% compared to 41%, respectively. The best predictors of live coral cover were depth and morphology, with a greater percentage of live coral at deep sites and in massive corals. The same predictors best described the prevalence of recently dead coral, but showed inverse trends to live coral. However, there was high variability among reef sites, which could be attributed to additional local stressors. Coral bleaching and resulting coral mortalities, such as the ones reported here, are of particular concern for small island nations like the Maldives, which are reliant on coral reefs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".