Tropicalization of temperate reef fish communities facilitated by urchin herbivory and diversity of thermal affinities
Bibliographic record
Abstract
Global declines in structurally complex habitats are reshaping both land and seascapes in directions that may change how biological communities respond to warming. Here, we test whether the widespread loss of kelp habitats through overgrazing by sea urchins changes fish community structure in directions that systematically alter warming sensitivity. We use simulations and comparisons of communities from 5996 sites across 19 ecoregions to test for thermal diversity shifts related to habitat. We find that the realized thermal affinities and ranges of fishes from kelp and urchin barrens differ, but only in regions with high initial response diversity. Fish communities in warm-temperate barrens host relatively more warm-affinity species than neighbouring kelp beds, highlighting that urchin herbivory can exacerbate tropicalization processes. By contrast, relatively cool-affinity species colonize cool-temperate barrens and explain apparent lags with ocean warming in these locations. Evidently, urchins are agents of ecological change with implications for climate resilience.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".