Habitat suitability models of elkhorn coral provide ecological insight to support coral reef restoration
Bibliographic record
Abstract
Coral reefs are experiencing unprecedented levels of stress from global warming, ocean acidification, fishing, and water pollution. In the Caribbean and Western Atlantic, multiple stressors have resulted in widespread losses of the dominant reef‐building Acroporid corals, two of which are listed as threatened species under the 1973 U.S. Endangered Species Act. In response, active coral reef restoration through the outplanting of live corals has become a widespread intervention technique. To increase restoration success, active coral reef restoration requires significant investment and careful planning, and selection of suitable sites for coral outplanting is an essential early step with considerable influence on restoration outcomes. We applied a maximum entropy model to predict and map habitat suitability for the reef‐building coral species, Acropora palmata , around the island of St. Croix in the U.S. Virgin Islands. Based mostly on bathymetry and benthic habitat type, the highest performing model predicted approximately 21.75 km 2 of the highest probability of suitable habitat, of which over half occurred within existing marine protected areas (MPAs). Outplanted coral at 60% of sites coincided with predicted maximum habitat suitability index values greater than 0.75 and 35% with values greater than 0.90. The model reveals that all three statutory MPAs with shallow water coral reefs have a considerable area (13.24 km 2 ) of predicted high suitability seabed with potential for active A. palmata restoration efforts. The predictive spatial modeling approach provides a cost‐effective tool to inform future coral restoration design and to evaluate the habitat suitability of coral outplanting sites.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".