Coral reef ecosystem functioning: eight core processes and the role of biodiversity
Bibliographic record
Abstract
Coral reefs are in global decline. Reversing this trend is a primary management objective but doing so depends on understanding what keeps reefs in desirable states (ie “functional”). Although there is evidence that coral reefs thrive under certain conditions (eg moderate water temperatures, limited fishing pressure), the dynamic processes that promote ecosystem functioning and its internal drivers (ie community structure) are poorly defined and explored. Specifically, despite decades of research suggesting a positive relationship between biodiversity and ecosystem functioning across biomes, few studies have explored this relationship in coral reef systems. We propose a practical definition of coral reef functioning, centered on eight complementary ecological processes: calcium carbonate production and bioerosion, primary production and herbivory, secondary production and predation, and nutrient uptake and release. Connecting research on species niches, functional diversity of communities, and rates of the eight key processes can provide a novel, quantitative understanding of reef functioning and its dependence on coral reef communities that will chart the transition of coral reefs in the Anthropocene. This will contribute urgently needed guidance for the management of these important ecosystems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".