Ecological drivers of songbird stopover behaviour during autumn migration in eastern New Brunswick
Bibliographic record
Abstract
As songbirds migrate, they must periodically stop to rebuild the energy needed for flight. Individual traits, local habitat characteristics, and the surrounding landscape can affect stopover refuelling and movement, yet the relative importance of endogenous and exogenous factors and the interrelation between refuelling and movement is less well understood owing to the challenge of measuring these aspects concurrently in free-living songbirds. I applied physiological profiling and habitat assessment together with radio telemetry and radar technologies to evaluate key ecological drivers of stopover performance in songbirds. In my first research chapter, I evaluated how refuelling and diel activity differed among five species, testing the hypothesis that refuelling intensity facilitates longer migration. Greater refuelling was associated with longer migration distances after accounting for the negative relationship between refuelling rate and the species-specific onset time of diel activity. In my second research chapter, I combined site-level measurements of invertebrate and migrant abundance with measures of refuelling and behaviour at coastal and inland stopover sites to assess how local habitat, landscape, and individual traits affect stopover performance. Songbird abundance was positively associated with invertebrate abundance, likely resulting from the earlier departure of birds experiencing poor refuelling at arrival. Behaviour and refuelling did not differ between coastal and inland stopover sites. In my third research chapter, resource augmentation was used to experimentally test if food availability affects refuelling and movement differently in the age and morph classes of the White-throated Sparrows (Zonotrichia albicollis). White-striped birds had greater refuelling when resources were augmented, but stopover behaviour did not differ according to treatment. In my final research chapter, I used radar and acoustic monitoring to test if visual and auditory information from volant migrants acts as a cue for departure, and whether sensitivity to these cues differs by age. Departure behaviour was not influenced by the passage of migrants nor by the number of night flight calls, but occurred earlier when wind conditions were more energetically favourable. Together, these studies provide insights into the relationships between refuelling, movement behaviour, and the environment that further our understanding of the migratory stopover behaviour of songbirds.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".