Factors affecting breeding dispersal in the facultatively colonial lesser kestrel: individual experience vs. conspecific cues
Bibliographic record
Abstract
Summary The role of individual experience vs. the use of conspecific cues on breeding dispersal decisions have seldom been determined in colonial birds. We studied causes of breeding dispersal in the lesser kestrel (Falco naumanni), a species that breeds in colonies of variable size as well as solitarily. During a 6‐year study in Spain, we gathered information on 486 subsequent breeding attempts and on 26 explanatory variables which evaluated individual experience, conspecific cues in terms of breeding performance and colony size, and different ecological and populational characteristics. Two decisions were separately analysed: whether or not to disperse, and how far to move. Generalized Linear Mixed Models (GLMMs) allowed us to identify the relative contribution of each explanatory variable while controlling for the non‐independence of individual dispersal decisions across years. Females seemed to disperse more often than males (34% vs. 19%), and both sexes apparently dispersed less with age. However, a GLMM showed that experience (i.e. the number of years a bird bred in a particular colony) was the only factor influencing breeding dispersal. Birds showed higher site fidelity the greater their experience in a colony, which could be related to benefits derived of increased local familiarity. A second GLMM showed that, before birds acquired experience in a particular colony, individual nest failure due to predation and proximity to other colonies increased the probability of dispersal, dispersal being also higher in colonies with poor conspecific breeding success. Furthermore, solitary nesting birds were more prone to disperse and dispersal probability decreased the larger the colony of origin, according to fitness expectations associated with colony size. A GLMM explaining dispersal distances retained two variables – birds dispersed farther the lower the breeding density in the surroundings, and the larger the distance to the nearest colony. Dispersing birds tended to settle within their previous foraging areas (median dispersal distance = 1·6 km), being constrained by the availability of nearby colonies. Lesser kestrels mainly cue on their own breeding performance and experience in a particular colony at the time of taking a dispersal decision. However, inexperienced birds also partially cue on the size and breeding success of their own colonies (but not on the size or breeding performance of other colonies), and birds moved larger distances when dispersing from areas of low populational density. These results support some degree of conspecific attraction.
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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".