Interactions between local disturbance and climate-driven heat stress on central Pacific coral reefs
Bibliographic record
Abstract
We investigated how local and global stressors affect coral reefs in situ by taking advantage of a latitudinal gradient in the central equatorial Pacific driven by El Niño-Southern Oscillation, where the past frequency of heat stress decreases away from the equator. We compared benthic communities at 40 sites across 4 atolls in the Gilbert Islands, namely in Kiribati (Tarawa and Abaiang) and the Republic of the Marshall Islands (Majuro and Arno), representing gradients in local chronic human disturbance and past frequency of bleaching-level heat stress. A hierarchical clustering analysis found 3 groupings of benthic communities, corresponding to sites with (1) low human influence and frequency of heat stress, (2) low human influence and high frequency of heat stress, and (3) high human influence, suggesting that the effects of intense, ongoing local disturbance may mask the influence of heat stress on coral reef communities. The frequency of heat stress explained 8.0% of the differences in community compositions across all sites (PERMANOVA), while local anthropogenic stressors explained 16.2%, and the combined effects explained 7.0%. Interactions between stressors were multiplicative and acted synergistically to increase the percent cover of macroalgae and the stress-resistant coral Porites rus. The prevalence of P. rus at locally disturbed sites drives the positive relationship between local stress metrics and live coral cover. At the taxon level, half of the multiplicative interactions were antagonistic, suggesting that actions that reduce local stressors may help some coral taxa respond to climate stress, but possibly at the expense of other taxa.
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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".