Breeding dispersal in a resident boreal passerine can lead to short‐ and long‐term fitness benefits
Bibliographic record
Abstract
Abstract Whether an individual disperses or remains site‐faithful between breeding seasons can have important impacts on individual fitness and population dynamics. While several studies have identified factors influencing the probability of breeding dispersal, the consequences of dispersal are much less certain, particularly over an individual’s lifetime. Here, we use 81 cases (13 paired and 55 single dispersals) of breeding dispersal across 55 yr of breeding and re‐sighting data from an individually marked population of Canada jays (Perisoreus canadensis) at the southern edge of their range in Algonquin Provincial Park, Ontario to determine both the short‐ (year after dispersal) and long‐term (lifetime) consequences of breeding dispersal. In the year following dispersal, adults had larger brood sizes and higher nest success compared to the year prior to dispersal. However, when adults dispersed during the fall/winter, they had significantly later lay dates and lower rates of nest success than adults that dispersed during the summer. Additionally, most breeders dispersed to territories of higher quality and individuals that dispersed to a territory of lesser quality experienced lower rates of nest success. Importantly, individuals that dispersed at least once in their lifetime produced an average of 2.7 more young and recruited an average of 0.9 more juveniles into the population compared to individuals that remained site‐faithful. Our study provides rare evidence of both the short‐ and long‐term benefits of breeding dispersal in Canada jays and demonstrates how the timing of dispersal can also have consequences for individual reproductive performance.
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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".