Tropical fish diversity enhances coral reef functioning across multiple scales
Bibliographic record
Abstract
There is now a general consensus that biodiversity positively affects ecosystem functioning. This consensus, however, stems largely from small-scale experiments, raising the question of whether diversity effects operate at multiple spatial scales and flow on to affect ecosystem structure in nature. Here, we quantified rates of fish herbivory on algal turf communities across multiple coral reefs spanning >1000 km of coastline in the Dominican Republic. We show that mass-standardized herbivory rates are best predicted by herbivore biomass and herbivore species richness both within (α-diversity) and across sites in the region (β-diversity). Using species-diversity models, we demonstrate that many common grazer species are necessary to maximize the process of herbivory. Last, we link higher herbivory rates to reduced algal turf height and enhanced juvenile coral recruitment throughout the ecosystem. Our results suggest that, in addition to high herbivore biomass, conserving biodiversity at multiple scales is important for sustaining coral reef function.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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".