Spring phenology and timing of breeding in short‐distance migrant birds: phenotypic responses and offspring recruitment patterns in common goldeneyes
Bibliographic record
Abstract
Understanding how organisms adjust breeding dates to exploit resources that affect fitness can provide insights into impacts of climate change on avian demography. For instance, mismatches have been reported in long‐distance migrant bird species when environmental cues experienced during spring migration are decoupled from conditions on breeding grounds. Short‐distance migrant bird species that store reproductive nutrients prior to breeding may avoid or buffer adverse phenological effects. Furthermore, reduced short‐term reproductive success could be offset by higher future recruitment of surviving offspring. We evaluated whether recruitment of locally‐hatched female offspring was related to hatching date alone or strength of mismatched breeding date for 405 individually‐marked adult female common goldeneyes Bucephala clangula (a short‐distance migrant) and their ducklings from a site in central Finland where ice‐out date has advanced by ∼ 2 weeks over 24 yr. Path analyses revealed that older, early‐nesting females with good body condition and larger broods recruited the most female offspring. Offspring recruitment decreased strongly among females that bred late relative to other females in the population each year; the extent of mismatched breeding date, i.e. hatching date scaled to annual ice‐out date, was less influential. Overall, most females advanced breeding dates when ice‐out occurred earlier in spring, but some females exhibited greater flexibility in response to ice‐out conditions than did others. In general, directional selection favoured early breeding over a wide range of ice‐out dates. Our results seem most consistent with a hypothesis that some short‐distance migrant species like goldeneyes have the capacity to track and respond appropriately to changing environmental conditions prior to onset of breeding.
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.
How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".