Towards a multi-stressor theory for coral reefs in a changing world
Bibliographic record
Abstract
Abstract Coral reefs are facing a constant barrage of human impacts, including eutrophication, overharvesting and climate change. While the local effects of overharvesting have been well-studied, regional nutrient loading from anthropogenic activities on land and global climate change-induced disturbances are increasing in magnitude and necessitating cross-scale multi-stressor approaches for coral reef ecology. Here, we expand on longstanding theory to develop an integrated multi-stressor framework for coral reefs. We show that: i) the geometry of a simple, empirically-motivated model suggests nutrients and harvesting can operate similarly, and synergistically, in driving shifts from coral- to algae-dominated reefs, resulting in clear context-dependent management implications; and ii) this same geometry suggests climate-driven coral mortality can drive the presence of long transients and climate-driven alternate states, even in moderately-impacted ecosystems. Reefs seemingly in a “safe space” based on individual stressors may in fact be much more susceptible to increasingly frequent storms and bleaching events in multi-stressor conditions. By integrating these findings with general ecological and theoretical concepts, we suggest that responses in benthic composition may act as “signatures of change” to multi-stressors, allowing us to develop a predictive and generalizable multi-stressor framework for coral reefs under global change. In line with this theory, we detail empirical evidence from Barbados of historical changes in reef composition and multi-stressor impacts within our framework. By bridging coral reef ecology and general ecological concepts, we can better understand ecosystem functioning and resilience in these important yet highly threatened systems. Manuscript Highlights Theoretical understanding of synergistic multi-stressor impacts on coral reefs Unexpected climate-driven alternate states, related to long transients Theoretical framework predicts “signatures of change” based on dominant stressor
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".