Major stopover regions and migratory bottlenecks for Nearctic-Neotropical landbirds within the Neotropics: a review
Bibliographic record
Abstract
Summary Nearly 300 species of landbirds, whose populations total billions, migrate between the Neotropics and North America. Many migratory populations are in steep decline, and migration is often identified as the greatest source of annual mortality. Identifying birds’ needs on migration is therefore central to designing conservation actions for Nearctic-Neotropical migratory birds; yet migration through the Neotropics is a significant knowledge gap in our understanding of the full annual cycle. Here, we synthesise current knowledge of Neotropical stopover regions and migratory bottlenecks, focusing on long-distance, migratory landbirds that spend the boreal winter in South America. We make the important distinction between “true” stopover—involving multi-day refuelling stops—and rest-roost stops lasting < 24 hours, citing a growing number of studies that show individual landbirds making long stopovers in just a few strategic areas, to accumulate large energy reserves for long-distance flights. Based on an exhaustive literature search, we found few published stopover studies from the Neotropics, but combined with recent tracking studies, they describe prolonged stopovers for multiple species in the Orinoco grasslands (Llanos), the Sierra Nevada de Santa Marta (Colombia), and the Yucatan Peninsula. Bottlenecks for diurnal migrants are well described, with the narrowing Central American geography concentrating millions of migrating raptors at several points in SE Mexico, Costa Rica, Panama and the Darién. However, diurnally migrating aerial insectivores remain understudied, and determining stopover/roost sites for this steeply declining group is a priority. Despite advances in our knowledge of migration in the Neotropics, we conclude that major knowledge gaps persist. To identify stopover sites and habitats and the threats they face, we propose a targeted and collaborative research agenda at an expanded network of Neotropical sites, within the context of regional conservation planning strategies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".