Decoupling linked coral and fish trait structure
Bibliographic record
Abstract
In coral reef systems, increasingly frequent, severe climate change-driven disturbances are responsible for declines in vulnerable species, and a reorganisation of assemblages. Whilst these changes will certainly elicit shifts in ecosystem functioning, how trait distributions and cross-taxon interactions are altered remains largely unmeasured, hampering our ability to predict functional shifts and target management actions to support reef health and recovery. We quantify trait distributions and interactions between habitat-engineering corals affected by a coral-bleaching mortality and associated fished reef fish assemblages. First, we assess changes in the proportional contributions of different traits pre- vs. post-disturbance. We then quantify changes in the trait associations that underpin cross-taxon interactions, and test relationships between coral and fish traits. The effects of reef type and survey atoll on coral trait structure are most influential, and there is a subtle temporal shift over the survey period. The trait structure of the fish assemblage remains stable. This suggests a simplification of the coral assemblage as vulnerable species disappear. The stability of the fish trait assemblage could indicate a lagged response, limited reliance on coral habitat, influence of other drivers or relative resilience. However, when examining traits of both taxa together, we discover that associations between individual coral and fish traits break down over time. We find reduced co-structure between the assemblages’ trait distributions, altering the associations between taxa. Our study signals weakened associations of fishes with their habitat as coral assemblages degrade with climate change, potentially disrupting the ecosystem functions that support services of coral reefs.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".