The benefits of herbivory outweigh the costs of bioerosion in a eutrophic coral community
Bibliographic record
Abstract
Abstract Herbivores play an integral part in maintaining the health of coral reefs by suppressing the growth of algae and accumulation of sediment and facilitating coral growth. However, in predator-depleted systems where densities of herbivores are unnaturally high, grazing can have detrimental effects on corals through excessive bioerosion. Yet, these benefits and costs are rarely investigated concurrently, especially in eutrophic systems where grazers may play a disproportionate role. We used a year-long exclusion experiment to elucidate the effect of natural densities of the dominant herbivore (the sea urchin Diadema setosum ) on coral communities in a heavily fished and eutrophic system (Hong Kong, China). To assess benthic community response to grazing, we monitored the survival and growth of three locally abundant coral species ( Pavona decussata, Platygyra carnosus and Porites sp.), algal and sediment accumulation, and bioerosion of coral skeletons across seasons. We found that urchins maintained our experimental coral assemblages, and when excluded, there was a 25 to 75-fold increase in algal-sediment matrix accumulation. Contrary to predictions, there was no general response of corals to urchin presence; Porites sp. survivorship increased while P. decussata was unaffected, and growth rates of both species was unchanged. Surprisingly, P. carnosus experienced higher mortality and bioerosion of up to 33% of their buoyant weight when urchins were present. Therefore, under natural densities, sea urchins clear substrate of algae and sediment, increase survival, maintain growth rates and health of coral assemblages, yet can accelerate the bioerosion of species with porous skeletons following mortality.
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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 | 0.000 |
| 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) | 0.001 | 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".