Preparing for and managing crown-of-thorns starfish outbreaks on reefs under threat from interacting anthropogenic stressors
Bibliographic record
Abstract
Crown-of-thorns starfish (CoTS) outbreaks rank among the greatest threats to coral throughout the Indo-Pacific. In the future, reefs already stressed by CoTS will be further burdened by overfishing and nutrient loading. How much these two factors will exacerbate CoTS outbreak severity is still uncertain. Furthermore, the CoTS management literature has focused on the Great Barrier Reef, whereas outbreak damage is rising across the Indo-Pacific. Here, we use a metacommunity model to simulate CoTS outbreaks in areas with high and growing levels of fishing pressure and offshore nutrient input. We model outbreaks on reefs adjacent to two cities within the range of CoTS that have less prior literature coverage: Cebu City, Philippines, and Jeddah, Saudi Arabia. We observe that the combination of population increases and urbanization of previously rural areas can drive complex patterns of multi-stressor interaction. We find that CoTS removal on intermediate spatial scales significantly improves regional-scale coral health, and provide guidelines under which each of four CoTS management strategies is optimal for conservation. We find that coral decline due to overfishing can be sharper on reefs with CoTS, and that nutrification can induce a shift from discrete outbreak waves to continuous CoTS presence. Our work shows the importance of long-term planning for reef management, and highlights how reef stressors can interact in potentially unforeseen ways.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".