Resilience of Central Pacific reefs subject to frequent heat stress and human disturbance
Bibliographic record
Abstract
Frequent occurrences of coral bleaching and associated coral mortality over recent decades have raised concerns about the survival of coral reefs in a warming planet. The El Niño-influenced coral reefs in the central Gilbert Islands of the Republic of Kiribati, which experience years with prolonged heat stress more frequently than 99% of the world's reefs, may serve as a natural model for coral community response to frequent heat stress. Here we use nine years of survey data (2004-2012) and a suite of remote sensing variables from sites along gradients of climate variability and human disturbance in the region to evaluate the drivers of coral community response to, and recovery from, multiple heat stress events. The results indicate that the extent of bleaching was limited during the 2009-2010 El Niño event, in contrast to a similar 2004-2005 event, and was correlated with incoming light and historical temperature variability, rather than heat stress. Spatial and temporal patterns in benthic cover suggest growing resistance to bleaching-level heat stress among coral communities subject to high inter-annual temperature variability and local disturbance, due to the spread of "weedy" and temperature-tolerant species (e.g., Porites rus) and the cloudy conditions in the region during El Niño events.
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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 | 0.000 | 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".