Connectivity of wood thrush breeding, wintering, and migration sites based on range‐wide tracking
Bibliographic record
Abstract
Many migratory animals are experiencing rapid population declines, but migration data with the geographic scope and resolution to quantify the complex network of movements between breeding and nonbreeding regions are often lacking. Determining the most frequently used migration routes and nonbreeding regions for a species is critical for understanding population dynamics and making effective conservation decisions. We tracked the migration of individual Wood Thrushes (Hylocichla mustelina) (n = 102) from across their range with light-level geolocators and, for the first time, quantified migration routes and wintering regions for distinct breeding populations. We identified regional and species-level migratory connectivity networks for this declining songbird by combining our tracking results with range-wide breeding abundance estimates and forest cover data. More than 50% of the species occupied the eastern wintering range (Honduras to Costa Rica), a region that includes only one-third of all wintering habitat and that is undergoing intensive deforestation. We estimated that half of all Wood Thrushes in North America migrate south through Florida in fall, whereas in spring approximately 73% funnel northward through a narrow span along the central U.S. Gulf Coast (88-93°W). Identifying migratory networks is a critical step for conservation of songbirds and we demonstrated with Wood Thrushes how it can highlight conservation hotspots for regional populations and species as a whole.
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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) | 0.000 | 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) | 0.000 | 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".