Spatial variation in life‐history trade‐offs results in an ideal free distribution in Black Brant Geese
Bibliographic record
Abstract
Ideal free distribution theory predicts that individuals distribute themselves so fitness is equal among patches. In this paper we evaluate all components of adult fitness to assess the hypothesis that individuals distribute themselves among seven brood-rearing areas so that trade-offs among different life history traits result in equal mean fitness among individuals using different areas. We used estimates of vital rates (clutch size, nest survival, pre-fledging survival, post-fledging survival, juvenile survival, and breeding probability) to estimate brood-rearing-area-specific per capita recruitment rates and survival for adult females. We summed brood-rearing-area-specific per capita recruitment and adult survival to calculate brood-rearing-area-specific estimates of lambda. We found little variation in lambda among brood-rearing areas and lifetime fitness implications of changing brood-rearing area were negligible (< 1% brood-rearing area mean fitness). We conclude that adult female Black Brant distribute themselves in an ideal free manner, resulting in equal fitness among females using these areas.
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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 | 0.002 |
| 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".