Context-dependent relationships between swimming, terrestrial jumping, and body composition in the amphibious fish <i>Kryptolebias marmoratus</i>
Bibliographic record
Abstract
Understanding the mechanisms that create phenotypic variation within and among populations is a major goal of physiological ecology. Variation may be a consequence of functional trade-offs (i.e. improvement in one trait comes at the expense of another trait) or alternatively may reflect the intrinsic quality of an organism (i.e. some individuals are simply better overall performers than others). There is evidence for both ideas in the literature, suggesting that environmental context may mediate whether variation results from trade-offs or differences in individual quality. We tested this overarching 'context dependence' hypothesis by comparing the aquatic and terrestrial athletic performance of the amphibious fish Kryptolebias marmoratus captured from two contrasting habitats, a large pond and small burrows. Overall, pond fish were superior terrestrial athletes but burrow fish were better burst swimmers, suggestive of a performance trade-off at the population level. Within each population, however, there was no evidence of a performance trade-off. In burrow fish, athletic performance was positively correlated with muscle content and body condition, consistent with the individual quality hypothesis. In pond fish, there was only a relationship between glycolytic white muscle and aquatic burst performance. Notably, pond fish were in better body condition, which may mask relationships between condition and athletic performance. Overall, our data highlight that population-level trends are insufficient evidence for the existence of phenotypic trade-offs in the absence of similar within-population patterns. Furthermore, we only found evidence for the individual quality hypothesis in one population, suggesting that patterns of phenotypic covariance are context dependent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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".