Age‐related variation in energy expenditure in a long‐lived bird within the envelope of an energy ceiling
Bibliographic record
Abstract
Energy expenditure in wild animals can be limited (i) intrinsically by physiological processes that constrain an animal's capacity to use energy, (ii) extrinsically by energy availability in the environment and/or (iii) strategically based on trade-offs between elevated metabolism and survival. Although these factors apply to all individuals within a population, some individuals expend more or less energy than other individuals. To examine the role of an energy ceiling in a species with a high and individually repeatable metabolic rate, we compared energy expenditure of thick-billed murres (Uria lomvia) with and without handicaps during a period of peak energy demand (chick-rearing, N = 16). We also compared energy expenditure of unencumbered birds (N = 260) across 8 years exhibiting contrasting environmental conditions and correlated energy expenditure with fitness (reproductive success and survival). Murres experienced an energy ceiling mediated through behavioural adjustments. Handicapped birds decreased time spent flying/diving and chick-provisioning rates such that overall daily energy expenditure remained unchanged across the two treatments. The energy ceiling did not reflect energy availability or trade-offs with fitness, as energy expenditure was similar across contrasting foraging conditions and was not associated with reduced survival or increased reproductive success. We found partial support for the trade-off hypothesis as older murres, where prospects for future reproduction would be relatively limited, did overcome an energy ceiling to invest more in offspring following handicapping by reducing their own energy reserves. The ceiling therefore appeared to operate at the level of intake (i.e. digestion) rather than expenditure (i.e. thermal constraint, oxidative stress). A meta-analysis comparing responses of breeding animals to handicapping suggests that our results are typical: animals either reduced investment in themselves or in their offspring to remain below an energy ceiling. Across species, whether a handicapped individual invested in its own energy stores or its offspring's growth was not explained by life history (future vs. current reproductive potential). Many breeding animals apparently experience an intrinsic energy ceiling, and increased energy costs lead to a decline in self-maintenance and/or offspring provisioning.
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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".