Factors affecting breeding dispersal in the facultatively colonial lesser kestrel: individual experience vs. conspecific cues
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it