Stopover regions, phenology, and spatiotemporal group dynamics of adult and juvenile common terns <i>Sterna hirundo</i> from inland lakes in North America
Bibliographic record
Abstract
Understanding the behavior of migratory birds can help determine levels of connectivity and inform conservation actions for species of conservation concern. The common tern Sterna hirundo is a long‐distance migratory seabird that is considered a species of conservation concern in the North American Great Lakes region and that has experienced significant declines in breeding numbers across large lakes in Manitoba. To better understand the movement ecology of common terns, we used data from multiple tracking technologies (solar geolocation, GPS tracking, and Motus radio tracking) obtained from individuals (n = 83) across five breeding colonies on four inland lakes in North America. We identified key stopover regions used during southward migration and explored how demographics and social interactions influence connectivity. We identified three key stopover regions (Lake Erie, the southern Atlantic Coast, and Florida) and documented, for the first time, differences in post‐natal and post‐breeding migration for inland nesting terns. Juveniles arrived, on average, three weeks later than unrelated adults to their first major staging area. Although adult female arrival to and departure from Lake Erie was similar to adult males, female schedules became significantly earlier than males as southward migration progressed. Using a graph network to describe the spatiotemporal associations among adults from the same inland lake, individuals appeared to be highly connected, meeting up in different regions throughout the non‐breeding season, suggesting that social interactions may play an important role in maintaining spatial connectivity. Despite differences in migration schedules by sex and arrival to the first major staging area by age class, birds appeared to rely on the same key stopover regions during southward migration. The stopover regions identified in this study can help identify potential bottlenecks and guide future research aimed at assessing the impacts of climate change and human disturbance on common terns breeding in North America.
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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) | 0.001 | 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 | 0.001 |
| 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".