Compensating for a bad start: compensatory growth across life stages in an organism with a complex life cycle
Bibliographic record
Abstract
Organisms with a complex life cycle are characterized by a life-history shift through metamorphosis and include organisms such as insects and amphibians. They must optimize their use of resources and behaviour across different life stages to maximize their fitness. An interesting question with regard to such life-history shifts is whether growth in the juvenile stage can be compensated for in the adult stage. Here we ask whether emerald damselflies (Lestes sponsa (Hansemann, 1823)) are able to compensate for depressed growth during the juvenile aquatic stage in their terrestrial adult stage. Lestes sponsa emerge at a fixed adult body size, but feed during the adult stage and are thus able to gain mass as adults. We performed a mark–recapture study to answer whether individuals that emerge from metamorphosis with a low mass are able to compensate by subsequent mass gain during the adult stage. Results showed that compensatory mass gain occurred in the adult stage such that small individuals gained more mass than large individuals. We also found that females gained more mass than males. However, individuals that emerged at a low mass still had lower mass as mature adults than individuals that emerged at a high mass, suggesting that compensation was not complete. This suggests that larval ecology and adult fitness are tightly linked and future research should focus more on elucidating the nature of this relationship.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".