Energetics and Migration in Songbirds: Two Case Studies Examining Energetic Condition and Migration at a Northern Stopover Location
Bibliographic record
Abstract
Migration is an energy-intensive behavior undertaken in both spring and fall by billions of songbirds to reach distant breeding and wintering grounds. Stopover habitats, particularly those located near ecological barriers that birds must cross, provide key locations where birds can stop and refuel during migration. A bird’s energetic condition affects its behavior at stopover locations; in spring, birds may accumulate energy reserves at locations en route to breeding grounds for tasks other than migration. This two-part study examined different aspects of the energetic condition of songbirds at a northern stopover location on the south shore of Lake Ontario. First, banding data for 12 Parulidae species were analyzed, and I found that arrival date, sex, and season explained some of the variation in the energetic condition of birds arriving at this location. My results suggest that there is possibly a reproductive advantage for spring migrants to arrive with energy reserves. Second, I found that energetic condition affects the orientation of White-throated Sparrows (Zonotrichia albicollis), mainly in the spring. However, like other studies of sparrows in captivity, I found bimodal orientation along the migratory axis, which makes it difficult to predict migratory orientation based on energetic condition. Both of these studies demonstrate that songbird behavior during migration is complex, variable, and worthy of further study.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".