Plasma mammalian leptin analogue predicts reproductive phenology, but not reproductive output in a capital‐income breeding seaduck
Bibliographic record
Abstract
Abstract To invest in energetically demanding life history stages, individuals require a substantial amount of resources. Physiological traits, particularly those related to energetics, can be useful for examining variation in life history decisions and trade‐offs because they result from individual responses to environmental variation. Leptin is a protein hormone found in mammals that is proportional to the amount of endogenous fat stores within an individual. Recently, researchers have confirmed that a mammalian leptin analogue (MLA), based on the mammalian sequence of leptin, is present with associated receptors and proteins in avian species, with an inhibitory effect on foraging and body mass gain at high circulating levels. While MLA has been both quantified and manipulated in avian species, little is currently known regarding whether plasma MLA in wild‐living species and individuals is associated with key reproductive decisions. We quantified plasma MLA in wild, Arctic‐nesting female common eiders (Somateria mollissima) at arrival on the breeding grounds and followed them to determine subsequent breeding propensity, and reproductive phenology, investment, and success. Common eiders are capital‐income breeding birds that require the accumulation of substantial fat stores to initiate laying and successfully complete incubation. We found that females with lower plasma MLA initiated breeding earlier and in a shorter period of time. However, we found no links between plasma MLA levels and breeding propensity, clutch size, or reproductive success. Although little is still known about plasma MLA, based on these results and its role in influencing foraging behaviors and condition gain, plasma MLA appears to be closely linked to reproductive timing and is therefore likely to underlie trade‐offs surrounding life history decisions.
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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".