Energetic consequences of sex-related habitat segregation in wintering American kestrels (<i>Falco sparverius</i>)
Bibliographic record
Abstract
Behavioural dominance can cause individuals to use less-preferred habitats, with potentially important life-history consequences. In the American kestrel, Falco sparverius, females exclude males from preferred open areas; I hypothesized that this sex-related habitat segregation leads to energetic consequences for males. I predicted that males would show decreased body condition over winter, while females would not, and that females would maintain larger net-energy surpluses than would males. Working in southeastern Pennsylvania, between 1991 and 1995, I conducted 150 behavioural observations and measured body condition of 235 wintering kestrels. Male kestrels maintained a lower body condition (residuals of a regression of mass vs. size) than did females and showed a decrease in mean body condition over winter, which females did not. I estimated that females had larger daily energy expenditures than did males (248 vs. 195 kJ per bird per day, ratio 1.27) but also had larger daily energy intakes (537 vs. 322 kJ/day, ratio 1.67). Females had larger net energy surpluses than did males (288 vs. 126 kJ/day, ratio 2.27), particularly when temperatures were <0°C. I conclude that differences in energetics are due in part to habitat differences and that males may suffer consequences by being forced to use less-preferred habitats.
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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".