Temperature and diet effects on omnivorous fish performance: implications for the latitudinal diversity gradient in herbivorous fishes
Bibliographic record
Abstract
Herbivorous fishes show a clear latitudinal diversity gradient, making up a larger proportion of the fish species in a community in tropical waters than in temperate waters. One proposed mechanism that could drive this gradient is a physiological constraint due to temperature. One prediction based on this mechanism is that if herbivorous fishes could shift their diet to animal material, they would be better able to grow, survive, and reproduce in cold waters. We tested this prediction on the omnivore Girella nigricans under different temperature and diet regimes using RNA–DNA ratios as an indicator of performance. Fish had increased performance (100%) at low temperatures (12 °C) when their diet was supplemented with animal material. In contrast, at higher temperatures (17, 22, and 27 °C) fish showed no differences between diets. This indicates that omnivorous fishes could increase their performance at low temperatures by consuming more animal matter. This study supports the hypothesis that a relative increase in the nutritional value of plant material at warmer temperatures could drive the latitudinal diversity gradient in herbivorous fishes.
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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 | 0.000 |
| 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".