Light-level tracking of Northern Waterthrush ( Parkesia noveboracensis ): lessons learned from wintering ground deployments
Bibliographic record
Abstract
The limited understanding of spatial and temporal patterns across the full annual cycle of long-distance migrants remains a crucial gap in the ability to describe their life history and inform conservation efforts. The Northern Waterthrush (<em>Parkesia noveboracensis</em>), for example, winters in the Caribbean and northern South America and breeds across eastern North America. Little information exists pertaining to their migratory routes, behavior, or migratory connectivity. Here, we describe migratory patterns derived from light-level geolocators deployed on Northern Waterthrushes wintering in Puerto Rico. We found that birds stopped in the northern Greater Antilles before migrating along the Atlantic coast to their breeding sites as far north as Quebec, Canada. Variability in transition events (sunrise/sunset) due to shading of the light sensor led to large uncertainty in breeding location estimates. However, we were able to use the raw light-level data to infer the phenology of migration. Northern Waterthrushes departed Puerto Rico on 24 April (± 8.1 d) and arrived on the breeding grounds on 17 May (± 10.4 d), suggesting that spring migration lasts approximately 23 (± 3.6) d. We also used raw light-level data during the breeding season to infer nesting behavior, which allowed us to identify individuals as breeding females and describe their nesting phenology. Together, these results offer new information about the migratory routes for Northern Waterthrushes and demonstrate how light-level geolocators deployed on the wintering grounds can be used to sex monochromatic species and infer life history information during the breeding season.
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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".