Haematological traits co-vary with migratory status, altitude and energy expenditure: a phylogenetic, comparative analysis
Bibliographic record
Abstract
Aerobic capacity is assumed to be a main predictor of workload ability and haematocrit (Hct) and haemoglobin (Hb) have been suggested as key determinants of aerobic performance. Intraspecific studies have reported increases in Hct and Hb in response to increased workload. Furthermore, Hct and Hb vary markedly among individuals and throughout the annual cycle in free-living birds and it has been suggested that this variation reflects adaptive modulation of these traits to meet seasonal changes in energy demands. We used a comparative dataset of haematological traits, measures of metabolic rate (57 species), and life-history traits (160 species) to test several hypotheses for adaptive variation in haematology in relation to migration and altitude. We then extended these general ideas to test relationships between Hct and basal metabolic rate, daily energy expenditure and activity energy expenditure, using the 57 species that we have metabolic rate information for. We found that at the interspecific level, full migrants have higher Hct and Hb than partial migrants and non-migrants, and that altitude is positively correlated with Hb but not Hct. Hct is positively associated with activity energy expenditure (energy spent specifically on costly activities), suggesting that haematological traits could be adaptively modulated based on life-history traits and that Hct is a potential physiological mediator of energetic constraint.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".