Growth, developmental, and size structure responses in tadpole prey under increasing threat from gape-limited newts
Bibliographic record
Abstract
Size variability within a cohort can have profound effects on community ecology and evolution. Although competition for resources generally increases size variability, the effect of (non-consumptive) predation on this demographic trait remains relatively poorly understood. Existing models suggest a positive correlation between growth rate (mediated by resource level) and expression of size variability (as measured by the coefficient of variation) in prey cohorts. We tested this prediction by exposing the tadpoles of the Japanese Forest Green Treefrog (Rhacophorus arboreus (Okada and Kawano, 1924) = Zhangixalus arboreus (Okada and Kawano, 1924)) to the non-lethal presence of gape-limited Japanese Fire-bellied Newts (Cynops pyrrhogaster (Boie, 1826)) at low and high predator densities in an outdoor mesocosm experiment. Tadpole growth rates and periphyton biomass increased with newt density. But in contrast to prediction, elevated growth rates did not increase but, reversely, decreased cohort size variability in the tadpoles. We discuss two potential mechanisms behind this outcome. First, increased resource availability mediated by predator feeding may have reduced the strength of competition, ultimately leading to more evenly distributed resource gains among individuals; second, if smaller individuals grew relatively faster than larger individuals, as to quicken entry to a size refuge against the gape-limited predator, then inter-individual size differences could diminish over time.
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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 | 0.001 |
| 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".