Multi‐decadal stability of fish productivity despite increasing coral reef degradation
Bibliographic record
Abstract
Abstract Under current trajectories, it is unlikely that the coral reefs of the future will resemble those of the past. As multiple stressors, such as climate change and coastal development, continue to impact coral reefs, understanding the changes in ecosystem functioning is imperative to protect key ecosystem services. We used a 26‐year dataset of benthic reef fishes (including cryptobenthic fishes) to identify multi‐decadal trends in fish biomass production on a degraded coral reef. We converted fish abundances into estimates of community productivity to track the long‐term trend of fish biomass production through time. Following the first mass coral bleaching event in 1998, the abundance, standing biomass and productivity of fish communities remained remarkably constant through time, despite the occurrence of multiple stressors, including extreme sedimentation, cyclones and mass coral bleaching events. Species richness declined following the 1998 bleaching event, but rebounded to prebleaching levels and also remained relatively stable. Although the species composition of the communities changed over time, these new community configurations still maintain a steady level of fish biomass production. While these highly dynamic and increasingly degraded systems can still provide some critical ecosystem functions, it is unclear whether these patterns will remain stable over future decades. Read the free Plain Language Summary for this article on the Journal blog.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".