The influence of conspecific and heterospecific neighbours on avian reproductive success
Bibliographic record
Abstract
Abstract We investigated the influence of conspecific and heterospecific neighbours on the reproductive success of mountain bluebirds (Sialia currucoides) and tree swallows (Tachycineta bicolor) over eight breeding seasons. The abundance of heterospecific neighbours was negatively associated with reproductive success in mountain bluebirds but positively associated with reproductive success in tree swallows during the early nesting period (i.e., hatching rate). For bluebirds, conspecific and heterospecific neighbour abundance was associated with higher reproductive success (i.e., fledging rate) during the later stages of the nesting period; the same was true for conspecific abundance for tree swallows. These findings could be explained by either positive behavioural interactions (e.g., shared defence) or by habitat quality. We found contrasting effects of nearest neighbour distance. For both mountain bluebirds and tree swallows, having a tree swallow neighbour in close proximity was positively associated with reproductive success during the early nesting period, while having a mountain bluebird neighbour in close proximity was negatively associated with reproductive success during the late nesting period for mountain bluebirds. Together, these results indicate that the effects of conspecific and heterospecific neighbours on reproductive success are species-specific and vary depending on the phase of reproduction.
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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 | 0.000 | 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".