A Scaling Approach to Understand the Dynamics of Fat and Lean Mass in Refueling Migrant Songbirds Measured by Quantitative Magnetic Resonance
Bibliographic record
Abstract
Fat contributes most of the energy for migratory flight of birds, whereas lean body tissues (muscles and organs) contribute amino acids and water to maintain metabolic and osmotic homeostasis. During refueling at stopover sites, both fat and lean mass are recovered, but the dynamics of this recovery are poorly understood. We used non-invasive quantitative magnetic resonance (QMR) analysis to measure fat and lean mass of > 3,500 individuals of 25 songbird species during six spring and three autumn migration seasons between 2009 and 2019 at Long Point, ON, Canada. We used allometric scaling analysis and linear mixed-effects modeling of body composition data at both the population level (single capture) and the individual level (recapture). In the population-level analysis, lean mass scaled hypoallometrically with body mass, such that for every 20% increase in body mass, lean mass was predicted to increase by 12.1% in spring and 12.8% in autumn. Fat scaled hyperallometrically with body mass, such that for every 20% increase in body mass, fat mass was predicted to increase by 144% in spring and 136% in autumn. At the individual level, these allometric relationships were more extreme. As a result of this differential allometry, at low body masses, lean and fat mass contributes nearly equally to changes in mass, but at high body mass fat deposition becomes progressively more dominant. Spring migrants deposited relatively more fat than autumn migrants, and in autumn juvenile birds tended to have greater lean mass than adults. Our findings show that lean mass deposition during refueling by songbirds is substantial, and in line with the losses of protein expected in flight. The process of fat and lean mass deposition is characterized by non-linear dynamics which are influenced by the current body composition, season, and, to a lesser extent, age. The patterns suggest that the need for dietary protein to rebuild lean mass will be greater when body mass is low, during autumn migration, and in juvenile birds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".