Recent advances in understanding migration systems of New World land birds
Bibliographic record
Abstract
Our understanding of migratory birds' year‐round ecology and evolution remains patchy despite recent fundamental advances. Periodic reviews focus future research and inform conservation and management; here, we take advantage of our combined experiences working on Western Hemisphere avian migration systems to highlight recent lessons and critical gaps in knowledge. Among topics discussed are: (1) The pipeline from pure to applied researchers leaves room for improvement. (2) Population limitation and regulation includes both seasonal and between‐season interactions. (3) The study of movements of small‐bodied species remains a major research frontier. (4) We must increase our understanding of population connectivity. (5) With few exceptions, population regulation has barely been investigated. (6) We have increasingly integrated landscape configuration of habitats, large‐scale habitat disturbances, and habitat quality impacts into models of seasonal and overall demographic success. (7) The post‐breeding season (late summer for latitudinal migrants) is increasingly appreciated for its impacts on demography. (8) We recognize the diverse ways that avian brood parasites, nest predators, and food availability affect demography. (9) Source–sink and meta‐population models help us understand migratory avian distributions among fragmented habitats. (10) Advances in modeling have improved estimates of annual survival and fecundity, but for few species. (11) Populations can be limited by ecological conditions in winter, but habitat needs are poorly known for most species at this time. (12) Migration tends to occupy broad spatial fronts that may change seasonally or when migrants cross major barriers. (13) En route conditions can limit migrant populations; linking migration habitat quality indicators to fitness or population consequences presents a major challenge. (14) A variety of intra‐tropical Neotropical migration patterns are recognizable, but almost nothing is known about these systems beyond descriptions of a few typical species' movements. (15) Global climate change scenarios predict range and phenology shifts of Neotropical migrant bird populations that must be considered in conservation plans. Future studies will depend on new technologies and the integration of modeling with sophisticated, large‐spatial‐scale measurement and parameter estimation; whether the pace of research and management involving migratory birds can match the growth of environmental threats remains to be seen.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".