Nonbreeding season movements of a migratory songbird are related to declines in resource availability
Bibliographic record
Abstract
Abstract There have been an increasing number of observations of itinerancy in migratory songbirds, where individuals move among 2 or more widely separated areas during the “stationary” nonbreeding season. Knowledge of such movements and an understanding of what drives them are important for predicting how migratory populations will respond to environmental change. In this study, we investigated nonbreeding movements of the Tree Swallow (Tachycineta bicolor), an aerial insectivore that breeds across North America and spends the nonbreeding season around the Gulf of Mexico, Florida, Mexico, Central America, and the Caribbean. With year-round tracking data obtained from 133 light-level geolocators deployed at 12 breeding sites ranging from Alaska to Nova Scotia to North Carolina, we show that 44% of individuals made at least one large-scale movement (range: 301–1,744 km) within the nonbreeding range. The frequency of itinerancy decreased with longitude, such that 75% of individuals made a movement in the western portion of the nonbreeding range compared to only 31% in the east. Using the Normalized Difference Vegetation Index (NDVI) as a proxy for resource availability, we found that when individuals did move, they were more likely to move from sites where resources were deteriorating faster (a more negative change in NDVI prior to departure) than their destination sites. There was also evidence that individuals moved to destination sites with higher NDVI and temperature in the autumn, but not in the winter. Our results suggest movements of Tree Swallows during the nonbreeding season are influenced by resource availability, but because not all individuals used multiple nonbreeding sites, the density of individuals at a site and the level of competition may have also been a factor influencing nonbreeding season movements.
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 | 0.000 | 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) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".