Prolonged survival out of water is linked to a slow pace of life in a selfing amphibious fish
Bibliographic record
Abstract
Metabolic rate and life history traits vary widely both among and within species reflecting trade-offs in energy allocation, but the proximate and ultimate causes of variation are not well understood. We tested the hypothesis that these trade-offs are mediated by environmental heterogeneity, using isogenic strains of the amphibious fish Kryptolebias marmoratus that vary in the amount of time each can survive out of water. Consistent with pace of life theory, the strain that survived air exposure the longest generally exhibited a “slow” phenotype including the lowest metabolic rate, largest scope for metabolic depression, slowest consumption of energy stores, and least investment in reproduction under standard conditions. Growth rates were fastest in the otherwise “slow” strain, however. We then tested for fitness trade-offs between “fast” and “slow” strains using microcosms where fish were held with either constant water availability or under fluctuating conditions where water was absent for half of the experiment. Under both conditions the “slow” strain grew larger and was in better condition, and under fluctuating conditions the “slow” strain produced more embryos. However, the “fast” strain had larger adult population sizes under both conditions, indicating that fecundity is not the sole determinant of population size in this species. We conclude that genetically based differences in pace of life of amphibious fish determine survival duration out of water. Relatively “slow” fish tended to perform better under conditions of limited water availability, but there was no detectable cost under control conditions. Thus, pace of life differences may reflect a conditionally neutral instead of antagonistic trade-off.
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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 | 0.001 | 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".