Form, function and consequences of density dependence in a long‐distance migratory bird
Bibliographic record
Abstract
The density dependence of demographic parameters and its implications for population regulation have long been recognized. Recent work has revealed potential effects of density on mating systems and sexual selection, but few studies concurrently assess the consequences of density on both demography and sexual selection. Such an approach is important because population processes and individual behaviors can interact to influence population growth and evolutionary trajectories. In this study, we tested the density dependence of breeding success, extra‐pair paternity, and the opportunity for sexual selection in a population of American redstarts Setophaga ruticilla using two different measures of density. To evaluate temporal patterns, we analyzed annual territory density, based on the total number of territories at our study site each year. To evaluate spatial patterns, we analyzed local territory density within years, based on the number of territories surrounding a focal territory. Greater annual density was associated with fewer offspring fledged per female, a reduced mean population rate of fledging success, and a lower relative contribution of extra‐pair paternity to male fitness. Greater local density was associated with fewer offspring fledged, reduced fledgling success, higher rates of nest loss, and higher rates of paternity loss on focal territories. Interestingly, greater local density was also associated with greater nestling mass on focal territories, which could imply that more densely‐packed territories contain superior resources. Overall, our results suggest that the effects of crowding via greater territory density reduce fecundity through increased nest predation, rather than reduced food availability, and increase rates of extra‐pair paternity. Thus, the selective pressures faced by individuals and their reproductive behaviors are likely to differ based on the annual and local density they experience, which may then feed back into population demography.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".